Master of Technology (M.Tech.) in Electronics and ...

Master of Technology

(M.Tech.)

in

Electronics and Telecommunication Engineering

Scheme with Description

Academic Year 2020-21

Department of Electronics and Telecommunication Engineering

Ramrao Adik Institute of Technology

Ramrao Adik Institute of Technology, Nerul, Navi Mumbai.


2

Semester I

Subject Code Subject Name

Teaching Scheme

(Contact Hours/week) Credits Assigned

Theory Pract. Tut. Theory Pract. Tut. Total

MTETC101 Statistical Signal Processing 03 -- -- 03 -- -- 03

MTETC102 Broadband Wireless Technology 03 -- -- 03 -- -- 03

MTETDLO101X Department Level Elective-1 03 -- -- 03 -- -- 03


MTILO101X Institute Level Elective-1 03 -- -- 03 -- -- 03

MTETDLOL101X Department Level Elective-1 Lab -- 02 -- -- 01 -- 01


Total 15 04 -- 15 02 -- 17



3


Examination Scheme

Theory Marks Term

Work

Pract.

/Oral Total

In-Sem Evaluations End

Sem

Exam

Exam

Duration

(in Hrs)

IA1 IA2

Avg.

of 2

IAs

Mid

Sem

Exam

MTETC101 Statistical Signal Processing 20 20 20 20 60 02 -- -- 100

MTETC102 Broadband Wireless Technology 20 20 20 20 60 02 -- -- 100

MTETDLO101X Department Level Elective-1 20 20 20 20 60 02 -- -- 100


MTILO101X Institute Level Elective-1 20 20 20 20 60 02 -- -- 100

MTETDLOL101X Department Level Elective-1 Lab -- -- -- -- -- -- 25 25 50


Total 100 100 100 100 300 -- 50 50 600



4

Semester II


Teaching Scheme (Contact

Hours/week) Credits Assigned


MTETC201 Advanced Digital Communication 03 -- -- 03 -- -- 03

MTETC202 RF and Microwave Engineering 03 -- -- 03 -- -- 03



MTILO202X Institute Level Elective-2 03 -- -- 03 -- -- 03



Total 15 04 -- 15 02 -- 17



5


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Sem

Exam

Exam

Duration

(in Hrs) IA1 IA2

Avg.

of 2

IAs

Mid

Sem

Exam

MTETC201 Advanced Digital Communication 20 20 20 20 60 02 -- -- 100

MTETC202 RF and Microwave Engineering 20 20 20 20 60 02 -- -- 100



MTILO202X Institute Level Elective-2 20 20 20 20 60 02 -- -- 100



Total 100 100 100 100 300 -- 50 50 600



6

Department Electives for Semester – I & II

Semester

I

Semester

I

Semester

II

Semester

II

Department Elective I

MTETDLO101X

Department Elective II

MTETDLO102X

Department Elective III

MTETDLO203X

Department Elective IV

MTETDLO204X

Estimation and Detection Theory

MTETDLO1011

Wireless Optical Communication

MTETDLO1021

Error Correcting Codes

MTETDLO2031

MIMO Wireless Communication

MTETDLO2041

Ad-hoc Wireless Networks

MTETDLO1012

Next Generation Networks

MTETDLO1022

Network Performance Modeling

and Simulation

MTETDLO2032

Network & Cyber Security

MTETDLO2042

Advanced Digital Signal Processing

MTETDLO1013

Artificial Intelligence & Machine

Learning

MTETDLO1023

Image Processing and Computer

Vision

MTETDLO2033

Data Science

MTETDLO2043

Computational Electromagnetics

MTETDLO1014

Microwave Circuits

MTETDLO1024

Antenna Analysis & Synthesis

MTETDLO2034

Microwave Measurements &

Design

MTETDLO2044



7

Institute Electives for Semester – I & II

Semester

I

Semester

II

Institute Elective I

MTILO101X

Institute Elective II

MTILO202X

Optimization Techniques in Problem Solving

MTILO1011

Research Methodology

MTILO2021

Cyber and Data Laws

MTILO1012

Probability and Random Variables

MTILO2022

Product Lifecycle Management

MTILO1013

Project Management

MTILO2023

Entrepreneurship Development and

Management

MTILO1014

Disaster Management and Mitigation Measures

MTILO2024

Renewable Energy Systems

MTILO1015

Financial Management

MTILO2025

Design of Experiments

MTILO1016

IPR and Patenting

MTILO2026



8

Semester III


Teaching Scheme



MTETS301 Special Topic Seminar -- 06 -- -- 03 -- 03

MTETD302 M. Tech Thesis Dissertation I -- 24 -- -- 12 -- 12

Total -- 30 -- -- 15 -- 15


Examination Scheme

Theory Marks

Term

Work

Pract.

/ Oral Total


Sem

Exam IA1 IA2

Avg.

of 2

IAs

MTETS301 Special Topic Seminar -- -- -- -- 50 50 100

MTETD302 M. Tech Thesis Dissertation I -- -- -- -- 50 50 100

Total -- -- -- -- 100 100 200



9

Semester IV


Teaching Scheme


Theory Pract. Tut. Theory Pract Tut. Total

MTETD401 M. Tech Thesis Dissertation II -- 30 -- -- 15 -- 15

Total -- 30 -- -- 15 -- 15


Examination Scheme

Theory Marks

Term

Work

Pract/

Oral Total


Sem

Exam IA1 IA2

Avg.

of 2

IAs

MTETD401 M. Tech Thesis Dissertation II -- -- -- -- 100 100 200

Total -- -- -- -- 100 100 200



10

Syllabus

for

Semester I



11

Subject Code Subject Name Theory

Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETC101 Statistical Signal

Processing 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total

In-Sem Evaluations End Sem

Exam

Exam Duration

(in Hrs) IA1 IA2 Avg. of 2

IAs

Mid Sem

Exam

MTETC101 Statistical Signal

Processing 20 20 20 20 60 02 -- -- 100

Course Pre-requisite:

Matrix theory

Fundamentals of probability

Signals and systems

Course Description:

This course helps students to understand basic concepts of probability theory, Random variables, Random processes, discrete- and continuous-time random processes Analysis and processing of random signals, Response of linear systems to random signals, Response of linear systems to random signals, it explores the topic of estimation and its performance evaluation.



12

Course Objectives:

The aim of this course is to provide knowledge of statistical techniques necessary to explain and explore the important applications

in signal processing and telecommunication.

Course Outcome:

Learners will be able to:

CO1: Understand the basics of linear algebra in communication engineering.

CO2: Apply appropriate statistical tools for handling the design and analysis of systems that involve randomness.

CO3: Analyze random processes for LTI systems and estimation theory.

CO4: Analyze LTI systems for random inputs

CO5: Understand estimation problem and use appropriate technique

CO6: Evaluate performance of estimators for the given problem.

Module No. Detailed Content Hrs. CO

1

Linear Algebra Concepts

Positive definite matrix, matrix representation of least squares, geometry of linear equations, four

fundamental subspaces of linear operator, properties of matrix inverses, results on matrix rank,

pseudo inverses, matrix condition number, singular value decomposition (SVD) and Principal

component analysis (PCA).

9 CO1

2

Review of Random Variables

Random variables, distribution and density function, functions of random variables, sums of

independent random variables, central limit theorem, Discrete and mixed random variables. 5 CO2



13

Textbooks and References:

1. Dimitris. G. Manolakis, Vinay Ingale, and Stephen M. Kogon, “Statistical and Adaptive Signal Processing”, Artech House, Inc.,

2005.

2. Steven M. Kay, “Fundamentals of Statistical Signal Processing: Estimation Theory Vol 1”, Prentice Hall, Englewood Cliffs, NJ,

2010.

3. A. Papoulis and S.U. Pillai, “Probability, Random Variables and Stochastic Processes”, 4th Edition, McGraw-Hill, 2002.

4. H. Stark and J. W. Woods, “Probability and Random Processes with Applications to Signal Processing”, 3rd ed., Pearson

Education.

5. Todd K. Moon and Wynn C. Stirling, “Mathematical Methods and Algorithms for Signal Processing”, Pearson Education, Inc., 2000.

3

Discrete-time Random Processes

Discrete time stochastic process, stationarity, random signal variability, time averages,

ergodicity, autocorrelation function of a real WSS process and its properties, cross-correlation

function, frequency domain description of stationary process, general correlation matrices,

correlation matrices from random process and correlation matrices of stationary process.

5 CO3

4

Analysis and processing of random signals

Linear time invariant system with WSS process as an input: stationarity of the output, auto-

correlation and power-spectral density of the output; examples with white-noise as input; linear

shift-invariant discrete-time system with WSS sequence as input, examples of random processes:

white noise process and white noise sequence; Gaussian process.

8 CO4

5

Principles of Estimation Theory

Estimation in signal processing, the mathematical estimation problem, assessing estimator

performance, unbiased and consistent estimators, confidence interval, efficient estimator,

minimum variance unbiased estimation and existence of minimum variance unbiased estimator.

7 CO5

6

Estimator Accuracy Considerations

Cramer-Rao lower bound (CRLB) theorem, computation of CRLB for different examples and

general CRLB for signals in white-Gaussian noise. 5 CO6



14

Evaluation Scheme:

1) In-Semester Assessment:

Assessment consists of two Internal Assessments (IA1, IA2) out of which; one should be compulsory class test (on minimum

02 Modules) and the other is a class test / assignment on case studies / course project.

Mid Semester Examination (MSE) will be based on 40-50% of the syllabus.

2) End-Semester Examination:

Question paper will comprise of full syllabus.

In the question paper, weightage of marks will be proportional to the total number of

lecture hours as mentioned in the syllabus.



15


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETC102 Broadband Wireless Technology 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETC102 Broadband Wireless

Technology 20 20 20 20 60 02 -- -- 100


Wireless communication

Computer Communication Networks

Course Description:

In this course, the students will be trained to understand mobile radio communication principles, recent trends adopted in cellular

systems and wireless standards. Learners will be able to discuss the cellular system design and technical challenges, analyze Mobile

radio propagation, fading, diversity concepts and the channel modelling, design parameters, link design, smart antenna, beam forming

and MIMO systems, Multiuser Systems, CDMA, WCDMA network planning and OFDM Concepts, applications of wireless systems

and standard.



16

Course Objectives:

The aim of this course is

To expose the students to understand mobile radio communication principles

To study the recent trends adopted in cellular systems and wireless standards.

Course Outcomes:


CO1: Understand the cellular system design and technical challenges.

CO2: Analyze Mobile radio propagation, fading, diversity concepts and the channel modelling.

CO3: Evaluate the design parameters and link design.

CO4: Evaluate and analyze smart antenna, beamforming and MIMO systems.

CO5: Analyze Multiuser Systems, CDMA, WCDMA network planning and OFDM Concepts.

CO6: Summarize the principles and applications of wireless systems and standard.

Module No. Detailed Content Hrs.

CO

1

Introduction to Wireless Communication:

The Cellular concept, System design, Capacity improvement in cellular systems, Co channel

interference reduction. Intelligent cell concept and applications. Technical Challenges.

06 CO1

2

Mobile Radio Propagation:

Reflection, Diffraction. Fading. Multipath Propagation. Channel modelling, Diversity

Schemes and Combining Techniques.

06 CO2

3 Design Parameters at the Base Station: Practical link budget design using path loss models.

Network design. 05 CO3



17

4 Design Parameters for Smart antenna systems: Beam forming. MIMO Systems. MIMO

antenna 05 CO4

5

Multiuser Systems:

CDMA- Principle, RAKE receiver.Link capacity, Power control, WCDMA-Network planning,

MC-CDMA, OFDM.

10 CO5

6 Cellular mobile communication beyond 3G: UMTS, WLAN, WPAN, WMAN, Ultra

Wideband communications, 4G and beyond 4G. 07 CO6


1. A.F. Molisch, “Wireless Communications”, Wiley, 2005.

2. A. Goldsmith, “Wireless Communications”, Cambridge University Press, 2005.

3. P. Muthu Chidambara, Nathan, “Wireless Communications”, PHI, 2008.

4. Ke-Lin Du, M. N. S. Swamy, “Wireless Communication Systems”, Cambridge University

Press, 2010.

5. K. Fazel, S. Kaiser, “Multi-carrier and Spread Spectrum Systems”, Wiley, 2003

6. S.G. Glisic, “Advanced Wireless Communications”, 4G Technologies, Wiley, 2004.

7. W. C. Y. Lee, “Mobile Communication Engineering”, 2nd ed., McGraw- Hill, 1998.

8. S.G. Glisic, “Adaptive CDMA”, Wiley, 2003.

Evaluation Scheme:


Assessment consists of two Internal Assessments (IA1, IA2) out of which; one should be compulsory class test (on

minimum 02 Modules) and the other is a class test / assignment on case studies / course project.




18







19


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO1011 Estimation and Detection Theory 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLO1011 Estimation and

Detection Theory 20 20 20 20 60 02 -- -- 100

Course Pre-requisite: Course on computer programming

Course on calculus

Probability Theory and Random Processes

Course Description:

The aim of this course is to enable the student to understand the basic principles of random signal processing, spectral estimation methods

and their applications different signal detection and estimation methods such as Bayesian parameter estimation, optimal filtering, linear

estimation, and Wiener/Kalman filtering etc. used in communication system design and the implications of proper synchronization

methods for proper functioning of the system.



20

Course Objectives:

The aim of this course is:

To enable the student to understand the basic principles of random signal processing, spectral estimation methods and their

applications.

To enable the student to understand the different signal detection and estimation methods used in communication system design and

the implications of proper synchronization methods for proper functioning of the system.

Course Outcome: Learners will be able to:

CO1: Summarize the fundamental concept on Statistical Decision Theory and Hypothesis Testing.

CO2: Summarize the various signal estimation techniques with additive noise.

CO3: Summarize with Bayesian parameter estimation.

CO4: Compare optimal filtering, linear estimation, and Wiener/Kalman filtering.

CO5: Construct Wiener and Kalman filters (time discrete) and state space models.

CO6: Demonstrate the signal detection procedures.


1 Binary hypothesis testing; Bayes, minimax and Neyman-Pearson tests. Composite hypothesis testing. 05 CO1

2

Signal detection in discrete time:

Models and detector structures. Coherent detection in independent noise. Detection in

Gaussian noise. Detection of signals with random parameters.

06

CO2



21

3

Detection of stochastic signals.

Performance evaluation of signal detection procedures, Tests for Stationarity and

Ergodicity. 06 CO3

4

Bayesian parameter estimation;

MMSE, MMAE and MAP estimates. Non-random parameter estimation. Exponential

families. Completeness theorem. ML estimation. Information inequality. Asymptotic

properties of MLEs.

08 CO4

5 Signal detection in continuous time:

Detection of deterministic signals in Gaussian noise. Coherent detection in white

Gaussian noise. 08 CO5

6 Estimator Accuracy Considerations:

Cramer-Rao lower bound (CRLB) theorem, computation of CRLB for different

examples, general CRLB for signals in white-Gaussian noise 06 CO6


1. H. V. Poor, “An Introduction to Signal Detection and Estimation”, 2nd ed., Springer, 1994.

2. B. C. Levy, “Principles of Signal Detection and Parameter Estimation”, Springer, 2008.

3. H. L. Vantrees, “Detection, Estimation and Modulation theory”, Part I, Wiley,1987.

4. M. D. Srinath & P. K. Rajasekaran, “Statistical Signal Processing with Applications”, Wiley, 1979.

5. J. C. Hancock & P.A. Wintz, “Signal Detection Theory”, Mc-Graw Hill, 1966.

Evaluation Scheme:







22







23


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL1011 Estimation and Detection Theory

Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLOL1011 Estimation and

Detection Theory Lab -- -- -- -- -- -- 25 25 50

List of Suggested Experiments:

Any 8 experiments based on the entire syllabus.

Assessment:

End Semester Examination: Practical/Oral examination is to be conducted by a pair of an internal and an external examiner.



24


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO1012 Ad-hoc Wireless Networks 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLO1012 Ad-hoc Wireless

Networks 20 20 20 20 60 02 -- -- 100

Course Pre-requisite: • Computer Networks • Wireless Networks

Course Description:

The aim of this course is to let the students to understand the Wireless adhoc and sensor Network, major challenges and designing

issues in designing wireless sensor and adhoc networks, various MAC and routing protocols, Heterogeneous network architecture

including MANET, WLAN, Cellular Networks.

Course Objectives:

The aim of this course is to let the students • To understand the Wireless adhoc and sensor Network. • To understand the major challenges and designing issues in designing wireless sensor and adhoc networks. • To understand various MAC and routing protocols in wireless sensor and adhoc networks. • To Understand Heterogeneous network architecture including MANET, WLAN, Cellular Networks.



25


CO1: Understand the concept of adhoc network.

CO2: Understand the wireless sensor networks and their applications.

CO3: Evaluate performance of various protocols in wireless sensor and adhoc networks.

CO4: Analyze the different pattern for Wireless network.

CO5: Understand TCP performance over adhoc network.

CO6: Evaluate design consideration of cellular Network and WSN.


1

Introduction Adhoc Network

Challenges and Applications of MANET, Architecture and Challenging

technologies.Wireless LAN, Wireless PAN, Wireless BAN. 06 CO1

2

Wireless Sensor Network

Design issues and application of sensor Network, Sensing and Communication Range,

Energy and Clustering of sensors, Wireless mesh Network.

05 CO2

3

Routing in Adhoc Networks

Introduction, Topology-Based versus Position-Based Approaches, Topologies-Based

Routing Protocols, Position-Based Routing, Other Routing Protocols.

05

CO3

4

Broadcasting, Multicasting, Geocasting and QoS in MANET

Introduction, The Broadcast Storm, Multicasting, Geocasting, QOS requirements, objectives

and Architecture. 10 CO4



26

5

Integrating MANETs, WLANs and Cellular Networks

Introduction, Ingredients of a Heterogeneous, Architecture, Protocol Stack, Comparison of

the Integrated Architectures.

07 CO5

6

Design Consideration in Sensor Network

Introduction, Classifications of WSNs, MAC Layer, Routing Cognitive Radio based sensor

Networks. Nano Sensor Networks.

06 CO6


1. Cordeiro, Agrawal, “Adhoc & Sensor Networks Theory and Applications”, Cambridge University Press India Pvt. Ltd, Edition

2010.

2. C. Siva Ram Murthy and B. S. Manoj, “Adhoc Wireless Networks Architecture and Protocols”, Pearson.

3. Houda Labiod, “Adhoc & Sensor Networks”, Wiley.

4. Vijay Garg, “Wireless Communication and Networking”, Elsevier Inc.

5. Manvi, Kakkasageri, “Wireless and Mobile Networks, Concepts and Protocols”, 2nd ed., Wiley.

Evaluation Scheme:











27


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL1012 Ad-hoc Wireless Networks Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLOL1012 Ad-hoc Wireless

Networks Lab -- -- -- -- -- -- 25 25 50


1. To study briefly Simulator or Software NS2, NS3, MATLAB/SCILAB, NETSIM, etc.

2. Implementation /Simulation of any two Routing Protocols in Adhoc Networks.

3. Implementation /Simulation of any two Routing Protocols in Wireless Sensor Networks.

4. Implementation /Simulation of any two MAC Protocols in Wireless Sensor Networks.

5. Case study on Cognitive Radio based sensor Networks.

6. Case study on Nano Sensor Networks.

7. Study and Implementation of technical paper from the reputed Journal related to Adhoc and Wireless Sensor Networks by using

any Simulator/tool.

8. Virtual lab experiments on WSN.

9. Implementing one hardware project related to WSN.

Any 8 experiments have to be performed.

Assessment:




28


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO1013 Advanced Digital Signal Processing 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLO1013 Advanced Digital Signal

Processing 20 20 20 20 60 02 -- -- 100


Discrete Time Signal Processing

Course Description:

The aim of this course is to provide in-depth treatment on methods and techniques in Power spectrum estimation, Adaptive filtering,

Wavelet transforms, applications of Signal Processing to real world problems, implement adaptive filters for a given application;

study and apply the techniques of power spectrum estimation and wavelet theory for various applications, Multirate DSP, Spectrum

estimation & analysis, Computer architecture for signal processing, apply Signal processing tools to biomedical signal processing

and musical sound Processing.



29

Course Objective:

The aim of this course is to provide in-depth treatment on methods and techniques in

Power spectrum estimation.

Applications of Signal Processing to real world problems

Course Outcomes:

Learners will be able to…

CO1: Know the sampling process in time and frequency domain and quantization effect in DSP.

CO2: Design the FIR and IIR filter for the specific applications.

CO3: Implement adaptive filters for a given application.

CO4: Know the concept of multirate signal processing and implement the filter bank for given

applications.

CO5: Study and apply the techniques of power spectrum estimation for various applications.

CO6: Apply Signal processing tools to biomedical signal processing and musical sound Processing.


1

Sampling and Finite precision Effect Analog to digital converter, Digital to analog converter, Random Signals, Sampling

theorem, Aliasing effect, Quantization, oversampling.

6 CO1

2 Filter Design and Filter Structures

Finite Impulse Response filter design and Infinite Impulse Response filter design, FIR

and IIR Implementation.

6 CO2

3 Multirate DSP

Interpolation, Decimation, Filter-bank Design and Polyphase structure. 8 CO3

4 Optimal Filtering of Random Signals

Prediction, Wiener filters, LMS and RMS adaptive filters. 6 CO4



30

5 Power Spectrum Estimation

Non-parametric and parametric methods, Periodogram of signals. 8 CO5

6 Applications of ADSP

To Biomedical signals processing, audio and Image processing 5 CO6


1. Emmanuel C. Ifeachor, Barrie W. Jervis, “Digital Signal Processing, A Practical Approach”, Pearson Education.

2. Alan V. Oppenheim, Ronald Schafer, “Discrete Time signal Processing”, Pearson Education.

3. J. Proakis, D. G. Manolakis, D. Sharma, “Digital Signal Processing, Principles, algorithms and applications”, Pearson Education.

4. Robert Schilling, Sandra Harris, “Fundamentals of Digital Signal Processing using MATLAB”, Cengage Learning.

5. S. K. Mitra, “Digital Signal Processing”, Tata McGraw Hill, 2001.

6. Chen, “Digital Signal Processing”, Oxford University Press.

7. K. Padmanabhan, “A Practical Approach to Digital Signal Processing”, New Age International.

Evaluation Scheme:











31


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL1013 Advanced Digital Signal Processing

Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration

(in Hrs) IA1 IA2 Avg. of

2 IAs

Mid Sem

Exam

MTETDLOL1013 Advanced Digital Signal

Processing Lab -- -- -- -- -- -- 25 25 50


1. To demonstrate the application of Periodogram.

2. To Study ECG denoising using Discrete Fourier transform.

3. To find various bands in EEG signal from IIR and FIR filtering

4. To study QRS Interval Identification.

5. To find formants from the voiced signal using power spectral estimation of speech signal.

6. To study system identification using adaptive least mean square estimation.

7. Estimation of formant in speech signal using Power Spectrum estimation.

8. Study of spectrum estimation.


Assessment:




32


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO1014 Computational Electromagnetics 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLO1014 Computational

Electromagnetics 20 20 20 20 60 02 -- -- 100


Electromagnetic Field Theory

Course Description:

This course will enable the students to understand numerical methods for solving Maxwell’s equations both static and electrodynamic

Introduction to finite difference, finite element and integral equation methods, and applied linear algebra. After the completion of this

course the student will be able to understand one-dimensional scalar wave equation, concept of Maxwell’s equations and Yee algorithm,

variational and Galerkin methods and model several engineering applications.

Course Objectives:


To expose students to the numerical methods for solving Maxwell’s equations both static and electrodynamic and introduce them

to the finite difference, finite element and integral equation methods, and elements of applied linear algebra.



33

Course Outcomes:

After the completion of this course the student will be able to:

CO1: Understand the fundamentals of Electromagnetics.

CO2: Apply finite difference method in solving electrodynamics problems.

CO3: Apply finite element method in solving electrodynamics problems.

CO4: Understand and apply the method of moments.

CO5: Analyze and model several electrical devices and equipment.

CO6: Understand several hybrid methods to solve Multiphysics problems.


01

Introduction to electromagnetic fields:

Review of vector analysis, electric and magnetic potentials, boundary conditions,

Maxwell’s equations, diffusion equation, Poynting vector, wave equation.

8 CO1

02

Finite Difference Method (FDM):

Finite Difference schemes, treatment of irregular boundaries, accuracy and stability of FD

solutions, Finite-Difference Time-Domain (FDTD) method.

7 CO2

03

Finite Element Method (FEM):

Overview of FEM, Variational and Galerkin Methods, shape functions, lower and higher

order elements, vector elements, 2D and 3D finite elements, efficient finite element

computations.

7 CO3

04

Method of Moments (MOM):

Integral formulation, Green’s functions and numerical integration, other integral methods:

boundary element method, charge simulation method.

5 CO4



34

05

Applications: Low frequency and high frequency electrical devices, static / time-harmonic

/ transient problems in transformers, rotating machines, waveguides, antennas, scatterers. 6 CO5

06

Special topics: Hybrid methods, coupled circuit – field computations, electromagnetic –

thermal and electromagnetic – structural coupled computations, solution of equations. 6 CO6


1. M. N. O. Sadiku, “Computational Electromagnetics with MATLAB”, 4th ed., Milton: Chapman and Hall/CRC, 2018.

2. M. V. K. Chari and S. J. Salon, “Numerical methods in electromagnetism”, Academic Press, 2000.

3. M. N. O. Sadiku, “Numerical techniques in electromagnetics”, CRC Press, 1992.

Evaluation Scheme:











35


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL1014 Computational Electromagnetics

Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


2 IAs

Mid Sem

Exam

MTETDLOL1014 Computational

Electromagnetics Lab -- -- -- -- -- -- 25 25 50


1. Demonstrate the flux lines of a permanent magnetic in 2D using FEMM (open source) Tool.

2. Understand basic commands, plotting, solving equations and Matrix Operations in MATLAB.

3. Solve a numerical problem with FEM method using MATLAB.

4. Solve a numerical problem with FDTD method using MATLAB.

5. Solve a numerical problem with MOM using MATLAB.

6. Obtain the radiation pattern of a half wave dipole antenna using FEM simulation software (any).

7. Design a microstrip patch antenna using FEM Simulation Software (any).

8. Mini-Project: Solve any design/research problem in the domain of Electrical Engineering using Electromagnetic Simulation tools

(any).


Assessment:




36


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO1021 Wireless Optical Communications 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLO1021 Wireless Optical

Communications 20 20 20 20 60 02 -- -- 100


Analog & Digital Communication

Fiber optics

Course Description:

This subject provides the in-depth know ledge in Optical Wireless Communication systems. It covers the emerging Optical wireless

communication trends and their applications. Learners will be able to Interpret the principles of Optical wireless communication

devices and systems, Model the channel for indoor and outdoor OWC systems and analyze the impact of modulation techniques on

bandwidth and power efficiency, free space optical communication and Laser satellite communication, coded modulation techniques

for OWC, coded MIMO and CDMA techniques in FSO, principle of Visible Light, Infrared Communications and utilization of OWC

in sensor networks.



37

Course Objectives:

This subject provides the in-depth know ledge in Optical Wireless Communication systems.

It covers the emerging Optical wireless communication trends and their applications.

Course Outcome:


CO1: Understand the principles of Optical wireless communication systems.

CO2: Understand the concept of OWC channels

CO3: Analyze the impact of modulation techniques on bandwidth and power efficiency.

CO4: Understand the concept of free space optical communication and Laser satellite

communication.

CO5: Evaluate the coded modulation techniques for OWC, coded MIMO and CDMA techniques

in FSO.

CO6: Understand the principle of Visible Light, Infrared Communications and utilization of

OWC in sensor networks.


1

Introduction to Optical Wireless Communication:

Optical communication systems, wireless access, Need of Optical Wireless Communication

(OWC), block diagram, challenges, Application. 06 CO1

2

Optical Wireless Communication:

Indoor optical wireless communication channel, LOS propagation mode, Spherical and

Gaussian wave model-outdoor channel, Attenuation Beam Wander 06 CO2



38

3

Modulation Schemes:

Analogue intensity modulation, Digital baseband-pulse modulation, subcarrier intensity

modulation, optical polarization shift keying, BER performance analysis. 05 CO3

4

Free space optical communications:

Introduction, operating principles, characteristics, QoS and availability, FSO OFDM

communication, FSO underwater, Free space optical networks, laser satellite communication. 06 CO4

5

Coded modulation techniques for OWC:

Coded MIMO for OWC- Indoor OWC MIMO channel-Point to point OW MIMO

communications-MIMO FSO-Wireless optical CDMA Communication System-System

description-indoor wireless optical CDMA-FSO CDMA.

08 CO5

6

Visible light communications:

VLC principle, VLC system model- system implementation, VLC applications Infrared

optical wireless communications - Optical wireless in sensor networks- FSO Sensor networks. 08 CO6


1. Z. Ghassemlooy, W. Popoola, S. Rajbhandari, “Optical Wireless Communications Systems and channel modelling with

MATLAB”, CRC press, Taylor & Francis, 2013.

2. Shlomi Armon, John R. Barry, Geroge K. Karagiannidis, Robert Schober, Murat Uysal, “Advanced Optical Wireless

Communication Systems”, Cambridge university press, 2012.

3. Heinz, Phd. Willebrand, “Free Space Optics”, Sams, 1st ed., 2001.

4. Stamatioas V. Kartalopouls, “Free space optical Networks for Ultra Broadband services”, John Wiley & Sons, 2011.

5. Morris Katzman, “Laser Satellite Communication”, Prentice Hall Inc., New York, 1991.

6. Roberto Ramirez-Iniguez, Sevia M. Idrus, Ziran Sun, “Optical wireless communications: IR for wireless connectivity”, CRC Press,

Taylor and Francis Group, 2007.



39

Evaluation Scheme:











40


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL1021 Wireless Optical Communications

Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


2 IAs

Mid Sem

Exam

MTETDLOL1021 Wireless Optical

Communications Lab -- -- -- -- -- -- 25 25 50


1. Performance analysis of optical link in presence of group velocity dispersion.

2. Performance Analysis of Optical Link with Different Sources.

3. Performance Analysis of Optical Link with Different Detectors.

4. Study and Implementation of technical paper from the reputed Journal related to and Wireless Optical Communication by using

any Simulation software.

5. Case study on Free Space Optical underwater communications.

6. Case study on laser satellite communication.

7. Case study on Optical wireless in sensor networks.

8. Mini project on Visible Light Communication.

9. Virtual lab expt.


Assessment:




41


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO1022 Next Generation Networks 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLO1022 Next Generation

Networks 20 20 20 20 60 02 -- -- 100


Computer Networks

Wireless Networks

Mobile Communication

Course Description:

This course will aid to develop enquiring minds and encourage curiosity about the paradigm shift from circuit switched network to

packet switched network, advancement in networks field, new technologies in telecommunication, Wireless NG Technologies, NGN

Standards, components of NGN architecture, Control and Signaling Protocols for NGN, Migration of PSTN networks to NGN,

Transition of IP networks to NGN, IPv6, NGN Evolution.



42

Course Objectives:


To relate the paradigm shift from circuit switched network to packet switched network.

To apply the advancement in networks field.

To examine new technologies in telecommunication.

To appraise the NGN Standards

Course Outcome:


CO1: Relate and compare the core differences between traditional and latest telecommunication

technologies.

CO2: Analyze, implement and apply the components of NGN architecture with NGN standards.

CO3: Design systems meeting out the requirements of the recent standards.

CO4: Deal with network extensions and next generation architecture Wireless, mobile, sensor.

CO5: Meet out the industry requirements for man power in next generation networks.

CO6: Contribute towards the enhancement of the existing wireless technologies.


1

Next Generation Technologies, Networks and Services

Introduction, Next Generation (NG) Technologies, Wire line NG Technologies,

FTTP, Long-Haul Managed Ethernet.

05 CO1

2

Wireless NG Technologies

Long Term Evolution (LTE), Enhanced HSPA Evolution Data Optimized (EVDO),

Ultra Mobile Broadband (UMB), SDR and cognitive radio, IoT, VOIP, IPTV, Quality

08 CO2



43

of Services, Quality of Experiences in NGN.

3

Next Generation Multiservice Technology Overview

MPLS &QoS, MPLS services and components, Overview of VPN, layer 2 VPN, layer

3 VPN.

06 CO3

4

ITU NGN Standards and Architectures

Main drivers to Next Generation Networks – NGN, ITU NGN standards, All-IP

network concept for NGN, NGN control architectures and protocols (TISPAN),

Numbering, naming and addressing for all NGN.

06 CO4

5

Control and Signalling Protocols for NGN

(SIP, Diameter) NGN security (AAA, identity management), Service convergence

Fixed-Mobile Convergence (FMC) in NGN, IP Multimedia, Subsystem (IMS) for

NGN.

08 CO5

6

Transitionto NGN and FutureEvolution

Migration ofPSTNnetworks toNGN, Transition ofIPnetworks to NGN, IPv6, NGN

Evolution.

06 CO6


1. Vijay Garg, “Wireless communication and Networking”, ELSEVIER Inc.

2. “Next Generation Telecommunications Network”, Parliament office of Science and Technology (Postnote). Dec 2007, No. 296 Ref.

www.parliament.uk.

3. ITU Manual.

4. Thomas Plevyak, Veli Sahin, “Next Generation Telecommunications Networks, Services and Management”, ISBN: 978-0-470-

57528-4, Wiley-IEEE Press.

5. Hwa Chen, Mohsen Guizani. Hsiao, “ Next Generation Wireless Systems and Networks”, Wiley.

6. Jyh- Cheng Chenand, Tao Zhang, “IP-Based Next-Generation Wireless Networks: Systems, Architectures, and Protocol”, Wiley.

http://www.parliament.uk/



44

Evaluation Scheme:











45


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL1022 Next Generation Networks Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLOL1022 Next Generation

Networks Lab -- -- -- -- -- -- 25 25 50



Assessment:




46


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO1023 Artificial Intelligence and Machine

Learning 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


2 IAs

Mid Sem

Exam

MTETDLO1023 Artificial Intelligence and

Machine Learning 20 20 20 20 60 02 -- -- 100

Course Prerequisites:

Probability & Statistics

Linear Algebra

Course Description:

This course helps students to introduce soft computing concepts and techniques and foster their abilities in designing appropriate

technique for a given scenario, soft computing based solutions for real-world problems, non-traditional technologies and fundamentals

of artificial neural networks, fuzzy sets, fuzzy logic, genetic algorithms, hand-on experience on MATLAB to implement various

strategies, various machine learning algorithms and techniques with a modern outlook focusing on recent advances, programmed in

various IOT nodes.



47

Course Objectives:

To enable students to understand different techniques related to Machine Learning.

To make students become acquainted with sequential decision-making methods in ML.

To gain basic knowledge about the key algorithms and theory that forms the foundation of machine learning.

Course Outcomes: Learners will be able to…

CO1: To understand basic concepts of AI.

CO2: To apply probability and statistical theory for AI and ML.

CO3: To understand basic concepts of ML.

CO4: To analyze clustering and SVM and gain basic knowledge about the key algorithms.

CO5: To understand fundamental concepts of Neural Networks.

CO6: To study and design applications for Signal Processing based on ML and AI.


01 AI Basics:

Terminology of AI, how to choose AI project, Workflow of AI project. 07 CO1

02 Probability and Statistical theory for AI and ML:

Probability Theory, Statistics and Linear Algebra Refresher, what is AI and Machine Learning? 03 CO2

03

Machine Learning Basics:

Supervised Learning, Unsupervised Learning, Classification and Regression, Cost Function,

Problem formulation, Linear Regression, Logistic Regression.

10 CO3

04 Introduction to clustering, SVM:

K- mean clustering, k-Nearest Neighbor Estimator, Support Vector Machine. 08 CO4



48

05

Neural Networks:

McCulloch and Pitts models of neuron, Types of activation functions, Single layer and

multilayer perceptron.

06 CO5

06

Applications of Machine Learning and AI:

Applications of ML and AI in Image, Audio, Speech, Music Signal processing. 05 CO6


1. Ethem Alpaydi, “Introduction to Machine Learning”, Second Edition, The MIT Press, 2015.

2. Shai Shalev-Shwartz and Shai Ben-David, “Understanding Machine Learning: From Theory to Algorithms”, Cambridge University

Press, 2014.

3. Christopher Bishop, “Pattern Recognition and Machine Learning”, Springer, 2006.

4. Ian Goodfellow, Yoshua Bengio, Aaron Courville, “Deep Learning (DL)”, MIT Press, 2016. (individual chapters freely available

online).

5. Mitchell, Tom, “Machine Learning”, Tata McGraw-Hill, 2017.

6. Russell and Norvig, “Artificial Intelligence”, Third Edition, Prentice Hall, 2015.

7. John D. Kelleher, Brian Mac Namee, and Aoife D'Arcy, “Fundamentals of Machine Learning for Predictive Data Analytics:

Algorithms, Worked Examples, and Case Studies”, MIT Press, 2015.

Evaluation Scheme:





http://www.springer.com/in/book/9780387310732

https://www.deeplearningbook.org/



49







50


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL1023 Artificial Intelligence and Machine

Learning Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


2 IAs

Mid Sem

Exam

MTETDLOL1023 Artificial Intelligence and

Machine Learning Lab -- -- -- -- -- -- 25 25 50


1. Linear Regression

2. Logistic Regression

3. KNN Clustering

4. K-mean clustering

5. Support Vector Machine and Kernels

6. Multilayer Perceptron

7. Convolutional Neural Networks

8. Application of Machine Learning

(Image Classification, Speech Recognition, Music Information Retrieval)


Assessment:




51


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO1024 Microwave Circuits 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration (in

Hrs) IA1 IA2 Avg. of 2

IAs

Mid Sem

Exam

MTETDLO1024 Microwave

Circuits 20 20 20 20 60 02 -- -- 100


Microwave Engineering

RF Design

Course Description:

In this course students will understand and apply microwave frequency design concept and impart knowledge on design and

implementation of high frequency transceiver system, analyze various components of microwave frequency communication system

architecture, understand the impact of different design parameters in transceiver circuit design, besides developing an insight to make

use of several high frequency design techniques.



52

Course Objective: The aim of this course is to let the students obtain

To explain microwave frequency design concept and impart knowledge on design and implementation of high frequency

transceiver system.

To develop an ability to analyze various components of microwave communication system architecture.

To develop an ability to analyze different design parameters of transceiver circuit design, besides developing an insight to make

use of several high frequency design techniques.

To utilize the various microwave circuit design concepts in designing the microwave transceiver systems.

Course Outcomes:


CO1: Understand the microwave frequency design concept.

CO2: Apply knowledge on design and implementation of high frequency Transceiver system.

CO3: Analyze various components of microwave frequency communication system architecture.

CO4: Analyze the impact of different design parameters in transceiver circuit design, besides

developing an insight to make use of several high frequency design techniques.

CO5: Evaluate the various microwave circuit design concepts in designing the microwave

transceiver systems.

CO6: Understand the operations of microwave integrated circuits.


01

Introduction to Microwave circuits: Scattering parameters, Impedance matching lumped and

distributed parameters, RF Behavior of Passive Components: High Frequency Resistors, High-

Frequency Capacitors, High-Frequency Inductors. Foundations of Microstrip lines, Striplines,

06 CO1



53

Higher modes in microstrips and striplines, Slotlines, Coplanar waveguides, Coplanar strips,

Microstrip discontinuities and bends.

02

Microwave Planar Filters: Periodic structures, Filter design by the Image Parameter method,

Filter design by the Insertion Loss method, Filter transformations, Filter implementation,

Stepped-Impedance Low-Pass filters, Coupled line filters, Filters using coupled resonators.

07 CO2

03

Transistor Amplifier Design: Characteristics of Amplifiers, Amplifier Power Relations: RF

source, Transducer Power Gain, Additional Power Relations, Stability Considerations: Satbility

Circles, Unconditional Stability, Stabilization Methods, Constant Gain: Unilateral Design,

Unilateral Figure of Merit, Bilateral Design, Operating and Available Power Gain Circles.

Noise Figure Circles, Constant VSWR Circles. Broadband, High Power and Multistage

Amplifiers.

07 CO3

04

Microwave Oscillator Design: Basic Oscillator Model, Negative Resistance Oscillator,

Feedback Oscillator Design, Design Steps, Noise characterization, Fixed Frequency

Oscillators, Dielectric Resonator Oscillators, YIG-Tuned Oscillators, Voltage Controlled

Oscillators, Gunn Element Oscillator.

07 CO4

05

Different Microwave Nonlinear Circuits: Mixers: Basic Concepts, Frequency Domain

Considerations, Single-Balanced Mixer Double-Balanced Mixer, Switches: Pin Diode

switches, FET switches, MEMS switches;Variable attenuators, Phase shifters, Detectors. 06 CO5

06

Microwave Integrated Circuits: Hybrid MICs: Definition, Characteristics, Comparison with

conventional circuits, fields of application and limitations and criteria for the choice of substrate

material, thin film hybrid circuits, thick film hybrid circuits, artwork, mask making,

photolithography, resistor stabilization, sawing, brazing process, wire bonding. Monolithic

MICs: Definition, substrate structure, doping by ion implantation ohmic contact, metal resistive

layers, gate metal, dielectric second level metal, dielectric and air bridge vias, substrate vias,

final wafer process steps.

06 CO6



54


1. David Pozar, “Microwave Engineering”, 4th Edition, Wiley 2011.

2. Guillermo Gonzalez, “Microwave transistor amplifier design: Analysis and Design”, Pearson Education, 2008.

3. Reinhold Ludwig and Pavel Bretchko, “RF Circuit Design Theory and Applications”, Pearson Education, 2004,

4. E.H.Fooks, R.A.Zakarevicius, “Microwave Engineering Using Microstrip Circuits”, Prentice-Hall.

5. Misra, D.K., “Radio-frequency and Microwave Communication Circuits”, John Wiley & Sons.

6. Reinmut K. Hoffman, “Handbook of Microwave Integrated Circuits”, Artech House.

7. Franco di Paolo, “Networks and Devices using Planar Transmission Lines”, CRC Press.

Evaluation Scheme:











55


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL1024 Microwave Circuits Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLOL1024 Microwave

Circuits Lab -- -- -- -- -- -- 25 25 50


1. To study Microstrip Transmission Lines using Electromagnetic simulator.

2. To study Strip Transmission Lines using Electromagnetic simulator.

3. To study Coplanar waveguide Transmission Lines using Electromagnetic simulator.

4. To study Matching Network Design using Electromagnetic simulator.

5. To design lumped element matching using ZY charts and to verify result using Vsmith software.

6. To study Planar Filters using simulation using HFSS

7. To Study High frequency passive component simulation using ADS.

8. To study Network Analysis of two port network by S-parameter using VAN.

9. To study Microwave transistors using Simulator.

10. To study Amplifier Linear Performance using simulators.


Assessment:




56

Subject

Code Subject Name

Theory

Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTILO1011 Optimization Techniques in Problem

Solving 03 -- -- 03 -- -- 03

Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTILO1011 Optimization Techniques in

Problem Solving 20 20 20 20 60 02 -- -- 100


Basic Matrix manipulation and probability theory.

Microsoft Excel

C Programming

Course Description:

The course introduces the concepts of decision making and problem solving. It delves into optimization techniques used to solve real

life problems in engineering, manufacturing and management. It looks at LPP problems, their formulation and solutions. It looks at

concepts of sensitivity analysis using algorithms like Simplex Method and Dual Simplex Method. It delves into aspects that are relevant

in solving problems using algorithms. Classes of real-life problems like transportation, assignment, job sequencing, replacement and

inventory management. It introduces to concepts of game theory, queuing and Monte Carlo Simulation techniques.



57

Course Objectives:

To familiarize the students with optimization techniques

To understand and be able to apply deterministic and probabilistic techniques for solving real world decision-making problems

Course Outcomes: At the end of the course learner will able to

CO1: Understand and apply optimization, decision making and problem solving for real life.

CO2: Formulate and solve linear programming problems.

CO3: Develop algorithms and solve transportation and assignment problems.

CO4: Analyze Queuing Systems.

CO5: Analyze and solve 2 person games.

CO6: Use probabilistic formulation for Monte-Carlo simulations


1

Introduction to Optimization Optimization techniques and Decision making. Applications. Limitations. Fundamental

Matrix Manipulations. Fundamental Probability techniques. 5 CO1

2

Linear Programming Introduction, Linear Programming Problem, Requirements of LPP, Mathematical

Formulation of LPP, Graphical method, Simplex Method, Special cases in Simplex, Penalty

Cost Method or Big M-method, Two Phase Method, Duality, Primal – Dual construction,

Symmetric and Asymmetric Dual, Weak Duality Theorem, Complimentary Slackness

Theorem, Main Duality Theorem, Dual Simplex Method, Sensitivity Analysis, Post-

Optimal Analysis. Introduction to Integer Programming. Introduction to Revised Simplex

Method.

10 CO2

3

LPP Applications

Transportation Problem: Formulation, solution, unbalanced Transportation problem.

Finding basic feasible solutions – Northwest corner rule, least cost method and Vogel’s

approximation method. Optimizing using MODI method.

6 CO3



58

Assignment Problem: Introduction, Mathematical Formulation of the Problem, Hungarian

Method Algorithm, Processing of n Jobs Through Two Machines and m Machines,

Graphical Method of Two Jobs m Machines Problem, Routing Problem, Travelling

Salesman Problem.

4

Queuing Models Formulation of Queing Model. Types of Queues, MM1: ∞∞ queue model and calculation

of probabilities. Analysis of the queuing system and calculation of parameters. 6 CO4

5

Game Theory Competitive games, rectangular game, saddle point, minimax (maximin) method of optimal

strategies, value of the game. Solution of games with saddle points, dominance principle.

Rectangular games without saddle point – mixed strategy for 2 X 2 games, 2Xn and mX2

games.

6 CO5

6

Simulation Introduction, Methodology of Simulation, Simulation Procedure, Application of Simulation

Monte-Carlo Method: Introduction, Monte-Carlo Simulation, Applications of Simulation,

Advantages of Simulation, Limitations of Simulation.

6 CO6

Text Books: 1. Taha, H.A., "Operations Research - An Introduction", Prentice Hall, (7th Edition), 2002.

2. Hiller, F. S. and Liebermann, G. J., "Introduction to Operations Research", Tata McGraw Hill,

2002.

Reference Books: 1. S. D. Sharma, “Operations Research”, Kedar Nath Ram Nath, Meerut.

2. P. K. Gupta, Man Mohan, “Operations Research, KantiSwarup”, Sultan Chand & Sons.



59

Evaluation Scheme:











60


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTILO1012 Cyber and Data Laws 03 -- -- 03 -- -- 03

Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration (in


IAs

Mid Sem

Exam

MTILO1012 Cyber and Data

Laws 20 20 20 20 60 02 -- -- 100


Data Security

Course Description:

This Course gives Introduction to the Cyber World and Cyber Law, Regulatory Framework such as International Legal Regime,

International legal regime relating to E-Commerce and Domestic Legal Regime. What is Cybercrime, Kinds of cybercrimes and

relevant provisions under Information Technology Act 2000 Indian Penal Code? Also addresses the Important Issues in Global E-

commerce, Issues relating to Access, Trust, Privacy and Security, Consumer Protection and so on.

Course Objectives:

To understand and identify different types cybercrime and cyber law

To recognized Indian IT Act 2008 and its latest amendments

To learn various types of security standards compliances



61


CO1: Understand the concept of cybercrime and its effect on outside world

CO2: Interpret and apply IT law in various legal issues

CO3: Apply various tools used for cyber-crime for investigation

CO4: Distinguish different aspects of cyber law & its compliance

CO5: Apply and analysed IT Acts for current cyber crimes

CO6: Apply Information Security Standards compliance during software design and development.


1 Introduction to Cybercrime: Cybercrime definition and origins of the world, Cybercrime and

information security, Classifications of cybercrime, Cybercrime and the Indian ITA 2000, A

global Perspective on cybercrimes.

6 CO1

2

Cyber offenses & Cybercrime Social egg attacks, Cyber stalking, Botnets, Attack vector, Credit

Card Frauds in Mobile and Wireless Computing Era, Security Challenges for wireless Devices,

Authentication Service Security, Attacks on Mobile/Cell Phones, Mobile Devices: Security

Implications for Organizations, Organizational Measures for Handling Mobile, Devices-Related

Security Issues, Organizational Security Policies and Measures in Mobile Computing Era, Laptops

6 CO2

3

Tools for Cyberline Methods, Phishing, Password Cracking, Key loggers and Spywares, Virus

and Worms, Steganography, Covert channels, storage and timing covert channels, counter

measures for covert communication, DoS and DDoS Attacks, SQL Injection, Buffer Over Flow,

Attacks on Wireless Networks, Identity Theft -ID Theft

6 CO3

4

The Law of IT Compliance How to conduct investigations: Cooperation with investigations,

Numerous Examples of Fraud (PostMordems), Securities Fraud, Federal Sentencing Guidelines,

Codes of Ethics, Hotlines, Reporting, Whistleblowing, Employee Monitoring, Entrapment, Raids

& Seizures Electronic Banking , The Need for an Indian Cyber Law.

5 CO4



62

5 Indian IT Act Cyber Crime and Criminal Justice: Penalties, Adjudication and Appeals Under the

IT Act, 2000, IT Act. 2008 and its Amendments 8 CO5

6 Information Security Standard compliances, Information Security Standard compliances SOX,

GLBA, HIPAA, ISO, FISMA, NERC, PCI. 8 CO6

Text books:

1. Sood, “Cyber Laws Simplified”, McGraw Hill.

2. Anthony Reyes, “Cyber Crime Investigations: Bridging the Gaps Between Security Professionals, Law Enforcement, and

Prosecutors”, Syngress Publishing, 2007.

3. Nina Godbole, Sunit Belapure, “Cyber Security”, Wiley India, New Delhi.

Reference books:

1. Suresh T. Vishwanathan, “The Indian Cyber Law”, Bharat Law House, New Delhi.

2. Bare Act, “The Information technology Act, 2000”, Professional Book Publishers, New Delhi.

3. Prashant Mali, “Cyber Law & Cyber Crimes”, Snow White Publications, Mumbai.

4. Nina Godbole, “Information Systems Security”, Wiley India, New Delhi.

5. Kennetch J. Knapp, “Cyber Security & Global Information Assurance”, Information Science Publishing.

Evaluation Scheme:











63


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTILO1013 Product Lifecycle Management 03 -- -- 03 -- -- 03

Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTILO1013 Product Lifecycle

Management 20 20 20 20 60 02 -- -- 100


None

Course Description:

The purpose of the course of to provide an overview of how IT tools and systems are used to create and manage product information and

knowledge, from identification of customers’ need to product retirement. In particular, the course focuses on the advanced use of computer

models, information, and knowledge in the product realisation process. This course aims to develop these skills. In particular, the course

is aimed towards students from the master programs Product Development, Product Engineering, Industrial Engineering

Course Objectives:

To familiarize the students with the need, benefits and components of PLM.

To acquaint students with Product Data Management & PLM strategies.

To give insights into new product development program and guidelines for designing and developing a product.

To familiarize the students with Virtual Product Development



64

Course Outcomes: At the end of the course learner will able to,

CO1: Gain knowledge about phases of PLM, PLM strategies and methodology for PLM Feasibility study and PDM implementation.

CO2: Illustrate various approaches and techniques for designing and developing products.

CO3: Apply product engineering guidelines / thumb rules in designing products for molding, machining, sheet metal working etc.

CO4: Acquire knowledge in applying virtual product development tools for components, machining and manufacturing plan.

CO5: Integration of environmental aspects in product design.

CO6: Carry out Life Cycle Assessment and Life Cycle Cost Analysis.


1

Introduction to Product Lifecycle Management (PLM): Product Lifecycle Management

(PLM), Need for PLM, Product Lifecycle Phases, Opportunities of Globalization, Pre-PLM

Environment, PLM Paradigm, Importance & Benefits of PLM, Widespread Impact of PLM,

Focus and Application, A PLM Project, Starting the PLM Initiative, PLM Applications.

PLM Strategies: Industrial strategies, Strategy elements, its identification, selection and

implementation, Developing PLM Vision and PLM Strategy, Change management for PLM.

09

CO1

2

Product Design: Product Design and Development Process, Engineering Design,

Organization and Decomposition in Product Design, Typologies of Design Process Models,

Reference Model, Product Design in the Context of the Product Development Process,

Relation with the Development Process Planning Phase, Relation with the Post design

Planning Phase, Methodological Evolution in Product Design, Concurrent Engineering,

Characteristic Features of Concurrent Engineering, Concurrent Engineering and Life Cycle

Approach, New Product Development (NPD) and Strategies, Product Configuration and

Variant Management, The Design for X System, Objective Properties and Design for X Tools,

Choice of Design for X Tools and Their Use in the Design Process.

08 CO2

3 Product Data Management (PDM): Product and Product Data, DM systems and importance,

Components of PDM, Reason for implementing a PDM system, financial justification of PDM, 04 CO3



65

barriers to PDM implementation.

4

Virtual Product Development Tools: For components, machines, and manufacturing plants,

3D CAD systems and realistic rendering techniques, Digital mock-up, Model building, Model

analysis, Modeling and simulations in Product Design, Examples/Case studies.

06 CO4

5

Integration of Environmental Aspects in Product Design: Sustainable Development,

Design for Environment, Need for Life Cycle Environmental Strategies, Useful Life Extension

Strategies, End-of-Life Strategies, Introduction of Environmental Strategies into the Design

Process, Life Cycle Environmental Strategies and Considerations for Product Design.

06 CO5

6

Life Cycle Assessment and Life Cycle Cost Analysis: Properties, and Framework of Life

Cycle Assessment, Phases of LCA in ISO Standards, Fields of Application and Limitations of

Life Cycle Assessment, Cost Analysis and the Life Cycle Approach, General Framework for

LCCA, Evolution of Models for Product Life Cycle Cost Analysis.

06 CO6

Text and Reference Books:

1. John Stark, “Product Lifecycle Management: Paradigm for 21st Century Product Realisation”, Springer-Verlag, 2004. ISBN:

1852338105.

2. Fabio Giudice, Guido La Rosa, AntoninoRisitano, “Product Design for the environment-A life cycle approach”, Taylor & Francis

2006, ISBN: 0849327229.

3. Saaksvuori Antti, Immonen Anselmie, “Product Life Cycle Management”, Springer, Dreamtech, ISBN: 3540257314.

4. Michael Grieve, “Product Lifecycle Management: Driving the next generation of lean thinking”, Tata McGraw Hill, 2006, ISBN:

0070636265.

Evaluation Scheme:







66







67

Subject

Code Subject Name

Theory

Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTILO1014 Entrepreneurship Development and

Management 03 -- -- 03 -- -- 03

Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


2 IAs

Mid Sem

Exam

MTILO1014 Entrepreneurship Development

and Management 20 20 20 20 60 02 -- -- 100


None

Course Description:

To familiarize the participants with the concept and overview of entrepreneurship with a view to enhance entrepreneurial talent. To

impart knowledge on the basics of entrepreneurial skills and competencies to provide the participants with necessary inputs for

creation of new ventures. To explore new vistas of entrepreneurship in 21st century environment to generate innovative business

ideas.

Course Objectives:

To motivate the students to become and/or work for entrepreneurship and start-ups

To understand and be able to apply processes, problem-solving techniques and legal clauses for success in venture



68


CO1: Understand the ideation process and the importance of innovative thinking.

CO2: Develop Business plans, financial analysis and perform market analysis for their venture.

CO3: Familiarize with Legal matters.

CO4: Understanding government schemes and support.

CO5: Prepare proper pitch for funding.

CO6: Use tools and techniques for solving problems.


1 Ideation: Idea Identification and Assessment. Idea Validation. Documentation of Ideas and

Feasibility Analysis. Introduction to Entrepreneurship and Business Startups. 6 CO1

2

Business Planning and Financial Basics: Learn how to build an effective Business Plan for

your venture. Understand the fundamentals of finance & accounting comprising of financial

statements. Break-even analysis. Risk Assesment. Marketing Plans, Management and

Personnel, Start-up Costs and Financing as well as Projected Financial Statements. Capital and

itsImportance to the Entrepreneur Starting a New Business, Buying an Existing Business, New

Product Development, Business Growth.

9 CO2

3

Legal Foundations: Define the right legal foundation for your company and explore

fundamentals like Company Registration, Compliances and Patents. Entrepreneur Law and its

Relevance to Business Operations.

6 CO3

4

Government support: Indian Environment for Entrepreneurship: key regulations and legal

aspects , Schemes and policies of the Ministry of MSME, role and responsibilities of various

government organisations, departments, banks etc., Role of State governments in terms of

infrastructure developments and support etc., Public private partnerships, National Skill

development Mission, Credit Guarantee Fund, PMEGP, discussions, group exercises etc.

6 CO4



69

5

Fund Raising: Company valuation, Fundraising, Equity Management. Role of Money and

Capital Markets in Entrepreneurial Development: Contribution of Government Agencies in

Sourcing information for Entrepreneurship.

6 CO5

6

Small Business Achieving Success: In The Small Business:Stages of the small business life

cycle, four types of firm-level growth strategies, Options – harvesting or closing small business

Critical Success factors of small business rectangular games without saddle point – mixed

strategy for 2 X 2 games, 2Xn and mX2 games.

6 CO6

Text Books: 1. Poornima Charantimath, “Entrepreneurship development: Small Business Enterprise”, Pearson

Education.

2. Robert D Hisrich, Michael P Peters, Dean A Shapherd, “Entrepreneurship”, latest edition, The

McGraw Hill Company.

3. Dr TN Chhabra, “Entrepreneurship Development”, Sun India Publications, New Delhi.

4. Dr CN Prasad, “Small and Medium Enterprises in Global Perspective, New century Publications”,

New Delhi.

Reference Books: 1. “Law and Practice relating to Micro, Small and Medium enterprises”, Taxmann Publication Ltd.

2. Kurakto, “Entrepreneurship- Principles and Practices”, Thomson Publication.

Evaluation Scheme:







70







71


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTILO1015 Renewable Energy Systems 03 -- -- 03 -- -- 03

Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration (in


IAs

Mid Sem

Exam

MTILO1015 Renewable Energy

Systems 20 20 20 20 60 02 -- -- 100


Environmental Study

Fundamentals of Energy

Course Description:

This course gives the importance of Renewable energy systems or sources, wind energy, solar photovoltaic and thermal systems, solar

PV and thermal systems, biomass energy, other energy sources. It also includes the tidal energy: energy from the tides, barrage and

non-barrage tidal power systems. The wave energy: energy from waves, wave power devices. With this course knowledge one can

innovate new system that can generate energy from natural sources.

Course Objectives: To impart knowledge on the various topics namely,

Recognize current and possible future role of renewable energy sources.

Adequate inputs on a variety of issues in harnessing renewable Energy.

Awareness’ about renewable Energy Sources and technologies.



72

Course Outcome: Upon the completion of this course, learners will be able to:

CO1: Understand the renewable energy sources.

CO2: Analyze wind power plants.

CO3: Understand and analyse Solar Photo Voltaic (SPV) systems.

CO4: Explore the use of biomass energy as a renewable energy source.

CO5: Apply Knowledge of working principle of geothermal energy systems.

CO6: Evaluate and explore the capability of tidal, hydrogen and hybrid energy systems


1

Global and National Energy Scenario:

Overview of conventional & renewable energy sources, need, potential &development of

renewable energy sources, types of renewable energy systems, Future of Energy Use, Global

and Indian Energy scenario, Energy for sustainable development, renewable electricity and key

elements, Global climate change, CO2 reduction potential of renewable energy- concept of

Hybrid systems.

08 CO1

2

Wind Energy

Power in the Wind, Nature of the wind, Wind Energy Conversion, Wind Data and Energy

Estimation, Site selection, Types of wind turbines, Wind farms, Wind Generation and Control,

classification of wind, characteristics, offshore wind energy, Types of Wind Power Plants

(WPPs), Components of WPPs, Working of WPPs, Grid integration issues of WPPs, Hybrid

systems, wind energy potential and installation in India.

08 CO2

3

Solar Energy

Solar energy system, Solar Radiation, Availability, Measurement and Estimation, Solar

Thermal Conversion Devices and Storage, Solar Electrical Power Generation, general Solar

Photo Voltaic (SPV) system components and their characteristics, Stand alone and Grid

Connected SPV systems.

08 CO3



73

Textbooks:

1. S. P. Sukhatme and J. K. Nayak, “Solar Energy: Principles of Thermal Collection and Storage”,

3rd Edition, TMH, New Delhi.

2. John Twidell and Tony Weir, “Renewable Energy Resources”, 2nd ed., Taylor and Francis, 2013.

3. G.D. Rai, “Non-Conventional Energy Sources”, Khanna Publishers.

Reference Books:

1. Godfrey Boyle, “Renewable Energy”, oxford University, press, 3rd edition, 2013.

2. Ahmed, Zobaa, Ramesh C Bansal, “Handbook of renewable technology”, World scientific, Singapore.

3. Ramesh & Kumar, “Renewable Energy Technologies”, Narosa.

4. Chetong Singh Solanki, “Renewable energy technologies: A practical guide for beginners”, PHI.

5. B.H. Khan, “Non-conventional energy source”, 2nd ed., TMH.

6. Karlsson, Kenneth Bernard, Skytte, Klaus Morthorst, “Integrated energy systems modeling”, Published in DTU International

Energy Report, 2015.

Solar Photovoltaic systems: Basic Principle of solar photovoltaic conversion, types of PV

Systems, Types of Solar Cells, Photovoltaic cell concepts: Cell, module, array, PV Module I-V

Characteristics, Efficiency & Quality of the Cell, series and parallel connections, maximum

power point tracking, applications.

4

Biomass Energy

Introduction, Biomass resources, Principles of Bio-Conversion, Biomass Cogeneration,

Environmental Benefits, Anaerobic/aerobic digestion, types of Bio-gas digesters, gas yield,

combustion characteristics of bio-gas, utilization for cooking.

05 CO4

5 Geothermal Energy: Resources, types of wells, methods of harnessing the energy, potential in

India. 03 CO5

6

Other Energy Sources

Tidal Energy: Energy from the tides, Types of Tidal power systems, wave power devices, Ocean

Thermal Energy Conversion (OTEC).

Hydrogen Production and Storage: Principle of working, various types, construction and

applications, Energy Storage System. Hybrid Energy Systems.

07 CO6



74

Evaluation Scheme:











75


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTILO1016 Design of Experiments 03 -- -- 03 -- -- 03

Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration (in


IAs

Mid Sem

Exam

MTILO1016 Design of

Experiments 20 20 20 20 60 02 -- -- 100


Probability Statistics

Course Description:

This course objective is to learn how to plan, design and conduct experiments efficiently and effectively, and analyze the resulting data

to obtain objective conclusions. Both design and statistical analysis issues are discussed. Opportunities to use the principles taught in the

course arise in all aspects of today’s industrial and business environment. Applications from various fields will be illustrated throughout

the course. All experiments are designed experiments; some of them are poorly designed, and others are well-designed. Well-designed

experiments allow you to obtain reliable, valid results faster, easier, and with fewer resources than with poorly-designed experiments.

You will learn how to plan, conduct and analyze experiments efficiently in this course.

Course Objectives:

To impart students a holistic view of the fundamentals of experimental designs, analysis tools and techniques, interpretation and

applications.



76

Learn how to plan, conduct and analyze experiments efficiently.

Course Outcome: Upon completion of this course, the students will be able to:

CO1: Understand the fundamentals of experiments and its uses.

CO2: Analyze experimental designs such as randomized block design, Latin square, factorial and fractional factorial designs.

CO3: Understand and explore multifactor experiments.

CO4: Analyze special experimental designs.

CO5: Analyze response surface methodology.

CO6: Apply Taguchi method in analyzing experimental data


1

Experimental Design Fundamentals

Importance of experiments, experimental strategies, basic principles of design, terminology,

ANOVA, steps in experimentation, sample size, normal probability plot, linear regression

model.

08 CO1

2

Single Factor Experiments

Completely randomized design, Randomized block design, Latin square design Statistical

analysis, estimation of model parameters, model adequacy checking, and pair wise

comparison tests.

08 CO2

3

Multi Factor Experiments

Two and three factor full factorial experiments, 2K factorial Experiments, Confounding

and blocking designs. 08 CO3



77

Textbooks:

1. Montgomer, D.C., “Design and analysis experiments”, John Wiley and sons 2003.

2. Nicolo Belavendram, “Quality by design: Taguchi techniques for industrial experimentation”, prentice hall, 1995.

Reference Books:

1. Phillip J. Rose, “Taguchi techniques for quality engineering”, McGraw Hill, 1996.

Evaluation Scheme:









4

Special Experimental Design

Special experimental design, Fractional factorial design, nested designs, Split plot design. 04 CO4

5

Introduction to Response Surface Methodology:

Experiments with random factors, rules for expected mean squares, approximate F- tests. 04 CO5

6

Taguchi Method

Steps in experimentation, design using Orthogonal arrays, data analysis, Robust design

control and noise factors, S/N ratios, parameter design, and case studies.

07 CO6



78

Syllabus

for

Semester II



79


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETC201 Advanced Digital Communication 03 -- -- 03 -- -- 03

Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETC201 Advanced Digital

Communication 20 20 20 20 60 02 -- -- 100


Digital communication

Random Signal Analysis

Course Description:

This course will build the fundamentals of modern communication system and an ability to analyze and design digital communication

systems. Evaluate the detection and estimation of signals in the presence of noise. Explain the characteristics of fading channels.

Course Objectives:

The aim of this course is to let the students obtain

Fundamentals of modern communication system

Ability to analyze and design digital communication systems



80


CO1: Explain and implement different source coding techniques.

CO2: Analyze waveform receivers for coherent communication.

CO3: Analyze waveform receivers for non-coherent communication.

CO4: Describe and design of band-limited channels.

CO5: Evaluate the detection and estimation of signals in the presence of noise.

CO6: Explain the characteristics of fading channels.


1

Source Coding

Average, mutual information & entropy, Coding for discrete sources, The Lempel

algorithm (LZ-77, LZ-78, LZW), Coding for analog sources -Temporal waveform

coding, Spatial waveform coding.

06 CO1

2

Coherent Communication with Waveforms

Binary cross-correlation receivers, Matched filter receivers, M-ary waveform receivers,

Time-sampling approach, Karhunen-Loeve (K-L), Expansion approach, Whitening

approach, Real and complex signal models, Effect of Data Imperfect Carrier

Synchronization, Effect of Data Imperfect bit synchronization

07 CO2

3

Non-Coherent Communication with Waveforms

Non-Coherent receivers in random phase channels, Optimum M-FSK receivers, Non

coherent receivers in random amplitude and phase. 07 CO3

Channels

Optimum receivers in Rayleigh channels, Optimum receivers in Rician channels



81

4

Signal Design for Channel and Equalization

Design of band limited signals with controlled ISI, Symbol by symbol sub optimum

detection, Introduction to linear equalizer, Mean-square error (MSE) criterion, Iterative

equalization and decoding, Introduction to adaptive equalization, The LMS Algorithm.

07 CO4

5

Optimum Detection and Estimation

Noise vector in signal space, Bayes detection of received signal, Decision region &

minimum error probability, Optimum detection of several special comm. Signals. 06 CO5

6

Non-linear & linear estimation

Fading Channels, Signal time spreading, Time variance of channel caused by motion,

Mitigating the degradation effects of fading. 06 CO6


1. John G.Proakis, “Digital Communication”, 3rd edition, McGraw –Hill International Editions.

2. Marvin K. Simon, Sami M Hindei, William C Lindesy, “Digital Communication Techniques: Signal Design & Detection”, PHI

Learning Private Limited.

3. Bernard Sklar, Pabitra Kumar Ray, “Digital Communications: Fundamental & Application”, 2nd Edition, Pearson Publication.

4. Theodore S. Rappaport, “Wireless communication principles and practice”, 2nd Edition, Pearson Publication.

Evaluation Scheme:







82







83


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETC202 RF and Microwave Engineering 03 -- -- 03 -- -- 03

Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETC202 RF and Microwave

Engineering 20 20 20 20 60 02 -- -- 100


Wave Theory and Propagation

Antenna Theory

Electromagnetics Engineering

Course Description:

This course will provide state-of-art knowledge in RF circuits and microwave systems. It provides introduction to microwave

engineering, high power microwaves and milli-meter wave technologies. It presents various methodologies presently prevalent for

the design of active and passive RF circuits. It will also provide knowledge of computer aided design tools for analysis and design of

microwave circuits and devices.



84

Course Objectives:


To provide state-of-art knowledge of elements in RF and microwave engineering.

To expose students to the current and future RF and microwave technologies.

Course Outcome:


CO1: Understand the microwave engineering fundamentals.

CO2: Analyze and design passive lines and impedance matching networks.

CO3: Understand the operation of various microwave passive and semiconductor devices.

CO4: Understand the operation of various microwave tubes.

CO5: Develop skills of planning, design and deployment of microwave networks.

CO6: Understand the areas of Millimeter-wave technology.


1

Introduction to Microwaves

Microwave Frequency Bands, Characteristics and Applications. Introduction to

High Power Microwaves, Operating Regimes, systems and applications. S-

parameters: Properties and characterization.

06 CO1

2

Passive Lines and Impedance Matching Network Design

Strip lines, Microstrip lines and coupled lines: Analysis and design.

Design of Impedance matching network using lumped and distributed

parameters.

06 CO2

3

Microwave Passive and Semiconductor Devices

Passive Devices: E-plane, H-plane and Magic Tees, Hybrid ring, Directional

couplers, Attenuators and Ferrite devices.

08 CO3



85

Semiconductor Devices: Diodes: Varactor, PIN, Tunnel, Point Contact, Schottky

Barrier, Gunn, IMPATT, TRAPATT, and BARITT. Transistors: BJT, Hetro

junction BJT, MESFET, and HEMT.

4

Microwave Tubes

Two Cavity Klystron and Reflex Klystron. Helix Travelling Wave Tube,

Backward Wave Oscillator, Cylindrical Magnetron. Relativistic Magnetrons and

Vircators.

08 CO4

5

Microwave Network Design and Deployment

Spectrum management, Interference effects and frequency shaping, Microwave

system engineering, Digital microwave radio, Digital multiplexing, Cabling and

signal termination, Field surveys.

05 CO5

6

Introduction to millimeter-wave technology:

Millimeter-wave frequency bands, Millimeter Wave Characteristics, application of

mm-waves, Channel Performance at 60 GHz, Gigabit Wireless Communications,

Development of Millimeter Wave Standards, Coexistence with Wireless Backhaul,

atmospheric losses, Propagation and path losses, Friis equation, link budget and

power budget calculation.

06 CO6


1. David Pozar, “Microwave Engineering”, 4th ed., Wiley Publication.

2. Matthew M. Radmanesh, “Radio Frequency and Microwave Electronics”, Pearson

Education.

3. James Benford et. al, “High Power microwave Devices”, 2nd ed., Series in Plasma Physics, Taylor and Francis.

4. F. Giannini, G. Leuzzi, “Non-linear Microwave Circuit Design”, Wiley Publication.

5. Harvey Lahpamer, “Microwave Transmission Networks Planning, Design and Deployment”, 2nd ed., Tata McGraw Hill.



86

Evaluation Scheme:











87


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO2031 Error Correcting Codes 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration (in


IAs

Mid Sem

Exam

MTETDLO2031 Error Correcting

Codes 20 20 20 20 60 02 -- -- 100


Digital Communication

Applied Mathematics

Course Description:

This course will provide students provide students a sound knowledge of traditional and modern coding theory, the motivation behind

synthesis of channel coding techniques. Students will design channel codes for the physical layer and storage applications and also design

new channel codes for wired/wireless communication systems.

Course Objectives: The aim of this course is

To provide students a sound knowledge of traditional and modern coding theory, the motivation behind synthesis of channel coding

techniques.



88


CO1: Mathematical analysis of different types of Information sources.

CO2: Understand mathematical structure for an information channel.

CO3: Determine the minimum number of bits per symbol required to represent the source & maximum rate at for reliable communication.

CO4: Design channel codes for the physical layer and storage applications.

CO5: Design new channel codes for wired/wireless communication systems.

CO6: Design burst-correcting codes.


1

Entropy and Information:

Structure in Randomness, First Concepts of Probability Theory, Units of Entropy Joint

Probability Distribution Functions, Conditional Probability and Bayes’ Theorem,

Conditional Probability Distributions and Conditional, Entropy Information Sources,

Memoryless Information Sources, Markov Sources and n-gram Models, Stationary

Distributions, Entropy of Markov Sources, Sequences of Symbols, The Adjoint Source of

a Markov Source, Extensions of Sources, Infinite Sample Space.

7 CO1

2

Information channels:

BSC and BEC Channels, Mutual Information, Noiseless and Deterministic Channels,

Additivity of Mutual Information, Channel Capacity, Continuous Channels and Gaussian

Channels Information Capacity Theorem, Rate Distortion Theory.

6 CO2

3

Source Coding:

Instantaneous Codes, The Kraft Inequality and McMillan’s Theorem, Average Length and

Compact Codes, Shannon’s Noiseless Coding, Fano Coding, Huffman Coding, Arithmetic

Coding, Higher-order Modelling.

6 CO3



89

4

Fundamentals of Channel Coding

Code Rate, Decoding Rules, Hamming Distance, Bounds on, Maximal Codes and Perfect

Codes, Error, Shannon’s Fundamental Coding Theorem.

7 CO4

5

Error-Correcting Codes

Linear Codes, Encoding and Decoding, Codes Derived from Hadamard Matrices, Cyclic

Codes, Encoding and Decoding of Cyclic Codes, Convolutional Codes, Binary

Convolutional Codes, Decoding Convolutional Codes, The Viterbi Algorithm, Sequential

Decoding, Trellis Modulation, Turbo Codes.

7 CO5

6 Burst-correcting Codes

Burst of Errors, BCH codes, Reed-Solomon Codes. 6 CO6


1. Roberto Togneri , Christopher J. S. deSilva, “Fundamentals of Information Theory and Coding Design”, Taylor and Francis e-

Library, 2006.

2. Shu Lin & Daniel J. Costello Jr., “Error Control Coding” Prentice Hall, Second Edition, 2004.

3. S. B Wicker, “Error Control Systems for Digital Communication and Storage”, Prentice Hall International, 1995.

4. Blahut R. E, “Theory and Practice of Error Control Codes”, Addisson Wesley, 1983.

5. Blahut R.E., “Algebraic codes for Data transmission”, Cambridge University Press, 2003.

Evaluation Scheme:







90







91


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL2031 Error Correcting Codes Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLOL2031 Error Correcting

Codes Lab -- -- -- -- -- -- 25 25 50


1. To study various probability density functions

2. To simulate Binary Symmetric Channel and calculate Bit Error Rate

3. Simulation of Repetition encoding and decoding and the calculation of its BER

4. Study and Implementation of Cyclic Codes using Simulation Method

5. Study and Implementation of Linear Block Coding and error detection and correction

6. Study and Implementation of BCH codes.

7. Study and implementation of REED Solomon codes.

8. Study and implementation of Technical paper from reputed Journal by using simulation tools.


Assessment:




92


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO2032 Network Performance Modeling and

Simulation 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


2 IAs

Mid Sem

Exam

MTETDLO2032 Network Performance

Modeling and Simulation 20 20 20 20 60 02 -- -- 100


Analog Communication

Digital Communication

Course Description:

This subject helps to understand the importance of Modelling and simulation. It also gives an ability to explain the architecture,

functioning capabilities of various communication networks. Compare different parameters used for communication systems and

study their impact on communication system. Explain the architecture, functioning capabilities of various communication networks.

Demonstrate an ability to evaluate design challenges and constraints issues associated with communication system.



93

Course Objective:


Understand the importance of Modelling and simulation

An ability to explain the architecture, functioning capabilities of various communication networks.

Course Outcomes: Learners will be able to…

CO1: Understand role of simulation and modelling.

CO2: Understand various Simulation Methodology.

CO3: Demonstrate an ability to evaluate design challenges and constraints issues associated with communication system.

CO4: Generations of various data signals and random numbers.

CO5: Explain the architecture, functioning capabilities of Simulation.

CO6: Explain the architecture, functioning capabilities of various communication networks.


1

Introduction

Concept of simulation and modelling, Roles of Simulation, Types of Simulation, Limits

of Simulation, Simulation Languages (High Level versus Low Level), Real-time

Simulation.

08 CO1

2

Simulation Methodology

Problem solving in Simulation Environment, Performance evaluation techniques,

Parameters Estimation, What-if Questions, Design, Validation Error Sources in

Simulation, Validation, Consistency, Replication, Elimination of Initial Bias, Variance

Reduction Techniques Design of Simulation Experiment: Data Stream Selection,

Simulation Length of Run, Simulation Sampling Frequency.

08 CO2



94

3

Digital Issues in Simulation

Quantization, Number representation, Underflow, Overflow, Processing Delay, Signal

Scaling.

05 CO3

4

Generation of Data Signals, Random Numbers and Processes

Data Sources, Symbol Mapping, Pulse Shaping, Pseudo Random Numbers, Generation

of Random Numbers, Generation of Random Variables using Common Distributions,

Generation of Random Processes, Generation of Correlated Noise.

08 CO4

5

Monte Carlo Methods Representation of Signals and Systems in Simulation

Fundamental Concepts, Monte Carlo Estimations, Monte Carlo Integration,

Convergence. 05 CO5

6

Representation of Signals and Systems in Simulation

Analog / Discrete, Baseband / Passband, Deterministic / Stochastic, Time Domain /

Frequency, Elements of Communication Systems, Basic building blocks. 05 CO6


1. W.H. Tranter, K.S. Shanmugan, T.S. Rappaport, K.L. Kosbar, “Principles of Communication systems Simulation with Wireless

Applications”, Prentice Hall.

2. M.C. Jeruchim, P.Balaban, K.S. Shanmugan, “Simulation of Communication Systems, Modeling, Methodology and

Techniques”, Cluwer Academic Publishers, 2nd Edition 2002.

3. F.M. Gardner, J.D. Baker, “Simulation Techniques, Models of Communications, Signals and Process”, John Wiley & Sons Inc.

1974.

4. J.G. Proakis, M. Salehi, G. Bauch, “Contemporary Communication Systems Using Matlab and Simulink”, CL-Engineering 2003.



95

Evaluation Scheme:











96


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL2032 Network Performance Modeling

and Simulation Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam

Duration (in

Hrs) IA1 IA2

Avg. of

2 IAs

Mid Sem

Exam

MTETDLOL2032

Network Performance

Modeling and Simulation

Lab

-- -- -- -- -- -- 25 25 50


1. Study and Analysis of different types of Analog Communication Circuit using Simulation Software (any two circuits).

2. Study and Analysis of different of Digital Communication Systems using Simulation Software (any three).

3. Study and Analysis of Frequency hopped Spread Spectrum System.

4. Study and Analysis of Direct Sequence Spread Spectrum System.

5. Study and Designing of Equalizers for Digital Communication.

6. Study of Eye Pattern using Simulation.

7. Study and Implementation of Convolution Codes using Simulation.

8. Study and Implementation of Cyclic Codes using Simulation Method.

9. Study and Implementation of Linear Block Codes using Simulation.

10. Study and Implementation of Optimum Receiver used for Digital Communication.

11. Study and Implementation of Lempel Algorithm using Simulation.



97

12. Study and Design of Band Limited Signals with controlled ISI.


Assessment:




98


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO2033 Image Processing and Computer

Vision 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLO2033 Image Processing and

Computer Vision 20 20 20 20 60 02 -- -- 100


Digital Signal Processing

Digital Image Processing

Course Description:

This subject helps to review image processing techniques for computer vision, understand shape and region analysis. It also helps to

understand Hough Transform and its applications to detect lines, circles, ellipses. To understand three-dimensional image analysis

techniques. Implement fundamental image processing techniques required for computer vision. Develop applications using computer

vision techniques.



99

Course Objective: The aim of this course is to let the students obtain

To review image processing techniques for computer vision.

To understand shape and region analysis.

To understand the Hough Transform and its applications to detect lines, circles, ellipses.

To understand three-dimensional image analysis techniques.

To understand motion analysis.

To study some applications of computer vision algorithms.

Course Outcomes:


CO1: Implement fundamental image processing techniques required for computer vision.

CO2: Analyze shapes, regions and Implement boundary tracking techniques.

CO3: Apply Hough Transform for line, circle, and ellipse detections.

CO4: Apply 3D vision techniques.

CO5: Implement motion related techniques.

CO6: Develop applications using computer vision techniques.


1

Image Processing Foundations

Review of image processing techniques, Classical filtering operations, thresholding

techniques, edge detection techniques, corner and interest point detection, mathematical

morphology, texture.

06 CO1



100

2

Shapes and Regions

Binary shape analysis, connectedness, object labeling and counting, size filtering, distance

functions, skeletons and thinning, deformable shape analysis, boundary tracking

procedures, active contours, shape models and shape recognition, centroidal profiles,

handling occlusion, boundary length measures. boundary descriptors, chain codes, Fourier

descriptors, region descriptors, moments.

07 CO2

3

Hough Transform

Line detection, Hough Transform (HT) for line detection, foot-of-normal method, line

localization, line fitting, RANSAC for straight line detection, HT based circular object

detection, accurate center location, speed problem, ellipse detection, Case study: Human

Iris location, hole detection, generalized Hough Transform (GHT), spatial matched

filtering, GHT for ellipse detection, object location, GHT for feature collation.

07 CO3

4

3D Vision

Methods for 3D vision, projection schemes, shape from shading, photometric stereo, shape

from texture, shape from focus, active range finding, surface representations, point-based

representation, and volumetric representations.

06 CO4

5

3D Object recognition and motion

3D object recognition, 3D reconstruction, introduction to motion, triangulation, bundle

adjustment, translational alignment, parametric motion, spline-based motion, optical flow,

layered motion.

05 CO5



101

5

Applications

Application: Photo album, Face detection, Face recognition, Eigen faces, Active

appearance and 3D shape models of faces Application: Surveillance, foreground-

background separation, particle filters, Chamfer matching, tracking, and occlusion,

combining views from multiple cameras, human gait analysis Application: In-vehicle

vision system: locating roadway, road markings, identifying road signs, locating

pedestrians.

08 CO6

Textbooks and References: 1. D. L. Baggio et al., “Mastering OpenCV with Practical Computer Vision Projects”, Packt Publishing, 2012.

2. E. R. Davies, “Computer & Machine Vision”, Fourth Edition, Academic Press, 2012.

3. Jan Erik Solem, “Programming Computer Vision with Python: Tools and algorithms for analyzing images”, O'Reilly Media, 2012.

4. Mark Nixon and Alberto S. Aquado, “Feature Extraction & Image Processing for Computer Vision”, Third Edition, Academic

Press, 2012.

5. R. Szeliski, “Computer Vision: Algorithms and Applications”, Springer 2011.

6. Simon J. D. Prince, “Computer Vision: Models, Learning, and Inference”, Cambridge University Press, 2012.

Evaluation Scheme:











102


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL2033 Image Processing and Computer

Vision Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


2 IAs

Mid Sem

Exam

MTETDLOL2033 Image Processing and

Computer Vision Lab -- -- -- -- -- -- 25 25 50


1. Implement image Pre-processing and Edge detection

2. Implement camera calibration methods

3. Implement Projection

4. Determine depth map from Stereo pair

5. Construct 3D model from Stereo pair

6. Implement Segmentation methods

7. Construct 3D model from defocus image

8. Construct 3D model from Images

9. Implement optical flow method



103

10. Implement object detection and tracking from video

11. Face detection and Recognition

12. Object detection from dynamic Background for Surveillance

13. Content based video retrieval

14. Construct 3D model from single image


Assessment:




104


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO2034 Antenna Analysis and Synthesis 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLO2034 Antenna Analysis and

Synthesis 20 20 20 20 60 02 -- -- 100


● Electromagnetic Theory

● Computational Electromagnetics

● Antenna Theory

● Microwave Engineering

Course Description:

The aim of this course is to provide knowledge of advanced antennas and radiating systems applicable to broadband, mobile

communications and smart antenna applications, state-of-art knowledge in microstrip antennas and also explain various methodologies

presently prevalent for design of microstrip antennas. To enable students to make design decisions in microstrip antenna arrays. Correlate

the fundamental design of an antenna to advanced communication applications.



105

Course Objectives:

The aim of this course is to provide knowledge of advanced antennas and radiating systems applicable to broadband, mobile

communications and smart antenna applications.


CO1: Understand planar antennas.

CO2: Design planar array.

CO3: Understand the design of broadband antennas.

CO4: Analyze the operation of aperture antennas.

CO5: Apply array theory.

CO6: Evaluate role of antennas for mobile communication.


1

Planar Antennas

Microstrip rectangular and circular patch antennas- Analysis and design, feeding

methods, circularly polarized microstrip antennas, Broadbanding techniques, and printed

slot antennas.

08 CO1

2

Planar Antenna Array

Linear array; Broadside and end fire arrays; Self and mutual impedance of between

linear elements, grating lobe considerations, Array factor, beamwidth, directivity.

Microstrip patch arrays and feed networks, Electronic scanning.

10 CO2



106

3

Broadband & Aperture Antennas

Folded dipole, Sleeve dipole, Biconical antenna- Analysis, characteristics, matching

techniques, Yagi array of linear elements and printed version, Log-periodic dipole array.

Frequency Independent Antennas- Planar spiral antenna, Log periodic dipole array,

Fractal Antennas, Field equivalence principle, Babinet’s principle, Rectangular

waveguide, horn antenna, parabolic reflector antenna, Travelling wave antennas.

10 CO3

4

Antenna Synthesis

Continuous Sources, Schelkunoff Polynomial Method, Fourier Transform Method

Broadband Dipoles and Matching Techniques, Biconical Antenna, Triangular Sheet,

Bow-Tie, Cylindrical Dipole, Folded Dipole, Discone and Conical Skirt Monopole,

Matching Techniques.

08 CO4

5

Diversity Schemes & Combining Techniques:

Macroscopic diversity scheme, Microscopic diversity scheme – Space diversity, Field

diversity, Polarization diversity, Angle diversity, Frequency diversity and time diversity

scheme, Combining techniques for Macroscopic diversity, Combining techniques for

Microscopic diversity – Selective combining, Switched combining, Maximal ratio

combining, equal gain combining and feed combining technique.

06 CO5

6

Smart Antennas & Antennas for mobile communication

Smart-antenna analogy, Signal Propagation, Antenna beamforming, Handset antennas,

Base station antennas. Beam steering and antennas for MIMO applications; Active

microstrip antennas.

06 CO6



107


1. C. A. Balanis, “Antenna Theory and Design”, John Wiley & Sons, 1997.

2. J.D. Kraus, “Antennas”, McGraw-Hill, 1988.

3. R.A. Sainati, “CAD of Microstrip Antennas for Wireless Applications”, Artech House, 1996.

4. R. Garg, P. Bharhia, I. Bahl, and A. Ittipiboo, “Microstrip Antenna design Handbook”,

Artech House.

5. J. R. James, P.S. Hall and C.Wood, “Microstrip Antennas: Theory & Design”, Peter Peregrinns , UK.

6. Jordan, E.C. and Balmain, K.G., “Electromagnetic Waves and Radiating Systems”, 2nd ed., Prentice-Hall of India.

7. Stutzman, W.L. and Thiele, H.A., “Antenna Theory and Design”, 2nd ed., John Wiley & Sons.

8. Elliot, R.S., “Antenna Theory and Design”, Revised edition, Wiley IEEE Press.

Evaluation Scheme:











108


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL2034 Antenna Analysis and Synthesis Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLOL2034 Antenna Analysis and

Synthesis Lab -- -- -- -- -- -- 25 25 50


1. To study different antenna parameters using PC based automated antenna measurement technique.

2. To study and measure different antennas using MATLAB code.

3. To study and measure Input Impedance of an Antenna.

4. To study different parameters of Pyramidal and Conical Horn antennas.

5. To study and measure array antenna characteristics.

6. To simulate and test different parameters of Rectangular Microstrip antenna by EM software.

7. To simulate and test different parameters of Circular Microstrip antenna by EM software.

8. To simulate and test different parameters of Microstrip Monopole antenna by EM software.

9. To simulate and test different parameters of Pyramidal Horn antenna by EM software.

10. To study and measure different antennas using Vector network analyzer (VNA).



109


Assessment:




110


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO2041 MIMO Wireless Communications 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLO2041 MIMO Wireless

Communications 20 20 20 20 60 02 -- -- 100


Wireless Communication

Course Description:

This subject provides an introduction to multiple antennas based wireless communications. The course covers fundamentals of multiple‐

input multiple‐output (MIMO) communication system. The basic quantities like diversity, coding gain, array gain are introduced. The

error rate of the MIMO systems is analyzed in detail. The concept of transmit and receive diversity, beamforming and combining, and

space‐time block code are also thoroughly explained. The precoder design and multiuser MIMO is also covered.



111

Course Objectives:

To understand an introduction to multiple antennas based wireless communications.

To apply fundamentals of multiple‐input multiple‐output (MIMO) communication system.

To apply basic quantities like diversity, coding gain, array gain.

To analyze error rate of the MIMO systems in detail.

To understand the concept of transmit and receive diversity, beamforming and combining, and space‐time block code.

To evaluate precoder design and multiuser MIMO.

Course Outcome:


CO1: Understand fundamentals of MIMO Wireless Systems.

CO2: Apply MIMO information Theory. CO3: Analyze space-time coding and error analysis in MIMO systems.

CO4: Evaluate linear STBD.

CO5: Understand the performance of MIMO receivers.

CO6: Understand Multiuser MIMO systems


1

Introduction:

Introduction to MIMO wireless systems and space‐time diversity, Diversity-

multiplexing trade-off, transmit diversity schemes, advantages and applications of

MIMO systems.

06 CO1

2

Analytical MIMO channel models & Power allocation in MIMO systems:

Uncorrelated, fully correlated, separately correlated and keyhole MIMO fading

models, parallel decomposition of MIMO channel, Uniform, adaptive and near

08 CO2



112

optimal power allocation

3

MIMO channel capacity:

Capacity for deterministic and random MIMO channels, Capacity of I.I.D.,

separately correlated and keyhole Rayleigh fading MIMO channels, MIMO

channel, MIMO information theory, Uniform, Error probability analysis.

10 CO3

4

Space-Time codes:

Advantages, code design criteria, Alamouti space-time codes, SER analysis of

Alamouti space-time code over fading channels, Space-time block codes, Space-

time trellis codes, Performance analysis of Space-time codes over separately

correlated MIMO channel, Space-time turbo codes.

10 CO4

5

MIMO detection:

ML, ZF, MMSE, ZF-SIC, MMSE-SIC, LR based detection, BER performance of

ZF receiver, transmit beamforming in MISO systems, BER of Alamouti coded

system, singular value decomposition (SVD), SVD in MIMO.

08 CO5

6

MIMO wireless communications:

Spatial modulation, MIMO based cooperative communication and cognitive radio,

multiuser MIMO, cognitive-femtocells and large MIMO systems for 5G wireless.

06 CO6


1. R. S. Kshetrimayum, “Fundamentals of MIMO Wireless Communications”, Cambridge University Press, 2017.

2. E. G. Larsson and P. Stoica, “Information Theory, Space‐Time Block Coding for Wireless Communications”, Cambridge

University Press, 2003.

3. Paulraj, R. Nabar and D. Gore, “Introduction to Space‐Time Wireless Communications”, Cambridge Univ. Press, 2003.

4. A. Chokhalingam and B. S. Rajan, “Large MIMO systems”, Cambridge University Press, 2014.

5. B. Kumbhani and R. S. Kshetrimayum, “MIMO Wireless Communications over Generalized Fading Channels”, CRC Press, 2017.

6. T. L. Marzetta, E. G. Larsson, H. Yang and H. Q. Ngo, “Fundamentals of Massive MIMO”, Cambridge University Press, 2016.



113

Evaluation Scheme:











114


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL2041 MIMO Wireless Communications

Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


2 IAs

Mid Sem

Exam

MTETDLOL2041 MIMO Wireless

Communications Lab -- -- -- -- -- -- 25 25 50


1. To Study and Compare various Modulation Schemes for MIMO in Wireless Communication.

2. To Study and implement coding and diversity gain for MIMO

3. To Study and implement Spatial multiplexing OFDM with MIMO

4. To Study 4*4 TAS SM MIMO System

5. To Study Narrowband MIMO System for 2*2 MIMO

6. To Study Frame Detection & Frequency Offset Correction.

7. To Study Synchronization and Channel Coding in OFDM Systems.

8. To Study Alamouti Space – Time codes for MIMO

9. To Study Analytical MIMO Channel model(iid model)



115

10. Vlab experiment on MIMO in Wireless Communication

11. Study and Implementation of technical paper from the reputed Journal related to MIMO

in Wireless Communication by using any Simulator/tool


Assessment:




116


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO2042 Network and Cyber Security 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLO2042 Network and Cyber

Security 20 20 20 20 60 02 -- -- 100


Computer Communication Networks

Operating System

Probability Theory and Random Processes

Course Description:

In this course students are introduced to advanced techniques to implement security mechanisms using IDS, Firewall, and Antivirus

and Biometrics, Incident handling and Forensics. Describe security threats and apply security techniques using cryptosystems. Explain

the key terms and concepts in cyber law, intellectual property and cybercrimes, trademarks and domain theft. Build and configure

firewall and intrusion detections systems using GNU open source security tools.



117

Course Objectives:


To introduce advanced techniques to implement security mechanisms using IDS, Firewall, and Antivirus and Biometrics, Incident

handling and Forensics

To discuss security implications on Organizations, security standards and Cyber laws.

Course Outcome:


CO1: Understand the broad set of technical, social & political aspects of Cyber Security.

CO2: Describe security threats and apply security techniques using cryptosystems.

CO3: Explain the key terms and concepts in cyber law, intellectual property and cyber crimes, trademarks and domain theft.

CO4: Build and configure firewall and intrusion detections systems using GNU open source security tools.

CO5: Incorporate approaches for incident analysis and response, for risk management and best practices and digital evidence

collection, and evidentiary reporting in forensic acquisition.

CO6: Recognized the role security management plays in cyber security defense.


1

Introduction to Network and Cyber Security

Need for network security, Attacks and Their classification, Network Vulnerabilities and

control, Security services and mechanisms, Impact of Security on Enterprises, Risk Factors

and Cost Analysis.

5

CO1



118

2

Cryptography andCryptosystems

Classical and modern cryptography, stream and block ciphers, Message digest, digital

signature, digital certificate, certificate authority, cryptanalysis,

DES/AES/RSA/RC4/MD5/SHA algorithms, Secure protocols SSL, IPSec, VPN, PKI,

Implementing security using symmetric and Public-Key cryptography.

6 CO2

3

Ethical Hacking and Network Differences

Cybercrimes, Cybercriminals, Cyberoffences, Cybercrimes in Mobile and Wireless

Devices, Tools and Methods used in Cybercrimes, Network reconnaissance, scanning and

sniffing, gaining access, Security Technologies: Firewall, IDS and Antivirus, Reverse

proxy, L7 content filtering firewall, NAT & reverse proxy, Firewall deployment and

limitations, selection of firewalls. Performance analysis of firewall, Signature and Anamoly

based IDSs, IDS deployment, zone diagram, performance analysis of IDS, strengths and

limitations of IDS, Biometrics for security.

6 CO3

4

Cybersecurity Principles and best Practices

Layered Defense, Surveillance and Reconnaissance Outsider/Internal Threat

Protection, Privacy, Intellectual Property, Professional Ethics, Freedom of Speech, Fair

User and Ethical Hacking, Trademarks, Internet Fraud, Electronic Evidence.

8 CO4

5

Cybersecurity Implications on Organizations, Standards and Cyber laws

Risk Management: Asset Evaluation and Business Impact Analysis, Risk Identification,

Risk Quantification, Risk Response Development and Control Security Policy,

Compliance, and Business Continuity, Cyber Incident Preparation: Incident Detection and

Analysis, Containment, Eradication, and Recovery ,Proactive and Post- Incident Cyber

Services, Forensics: Forensic Technologies, Digital Evidence Collection, Evidentiary

Reporting, The Indian IT Act and new amendments.

8 CO5

6

System Security and Case Study

Security Operations Center (SOC), Network Operations Center (NOC), Network Security

Audit, SET, Biometric Security, Digital Immune System, Cloud Security. Wi-Fi Security,

Mobile and Cellular Security.

6 CO6



119


1. Behrouz Forouzan, “Cryptography and Network Security”, McGraw Hill Publications.

2. Pfleeger and Pfleeger, “Security in Computing”, Pearson Publications.

3. M. Whitman, “Management of Information Security”, Cengage Publications.

4. B. Menezes, “Network Security and Cryptography”, Cengage Learning India.

5. Matt Bishop, “Computer Security”, Pearson Publication.

6. William Stallings, “Cryptography and Network Security”, Pearson publications.

7. Nina Godbole, “Cyber Security”, John Wiley Publications.

8. Mark Stamp and Deven Shah, “Information Security: Principles and Practice”, 2nd edition.

9. Houston Carr and Charles Snyder, “Data Communication & Network Security”, McGraw-Hill Publication.

Evaluation Scheme:











120


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL2042 Network and Cyber Security Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLOL2042 Network and Cyber

Security Lab -- -- -- -- -- -- 25 25 50



Assessment:




121


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO2043 Data Science 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration (in


IAs

Mid Sem

Exam

MTETDLO2043 Data Science 20 20 20 20 60 02 -- -- 100


Matrix theory

Linear Algebra

Basic Set theory

Course Description:

This subject enable student to understand different techniques related to data science. It also makes students become acquainted with

numerical methods and matrix computation strategies, gain basic knowledge about the key algorithms and theory that forms the

foundation of data science. Apply the algorithms to a real-world problem, optimize the models learned and report on the expected

accuracy that can be achieved by applying the models.



122

Course Objective:


To enable students to understand different techniques related to data science.

To make students become acquainted with numerical methods and matrix computation strategies.

To gain basic knowledge about the key algorithms and theory that forms the foundation of data science.

Course Outcomes:


CO1: Understand the fundamentals data analysis.

CO2: Analyze predictive modeling as applied to data science.

CO3: Analyze fitting model to data.

CO4: Understand model performance parameters and its use.

CO5: Apply and explore data visualization methods.

CO6: Analyze and create data analysis applications.


1

Introduction to data science:

Ubiquity of data opportunities, Data Processing and Big Data, Data Understanding and

Preparation, Data querying

Data Warehousing, Regression Analysis

06 CO1

2

Introduction to predictive Modeling from correlation to supervised segmentation:

Fundamental concepts: Identifying informative attributes, - correlation, attribute / variable

selection, Select Informative attributes – attribute selection with information gain. 08 CO2



123

3

Fitting model to data:

Finding optimal model parameters based on data, optimizing objective function, Loss

function, linear discriminant function for scoring and ranking instances, Class probability

estimation and logistic regression, Nonlinear functions.

07 CO3

4

Overfitting and its Avoidance:

Generalization, fitting and overfitting, complexity control, Holdout data, why is overfitting

Bad? Holdout Evolution to Cross Validation, Leaning Curves Overfitting avoidance and

complexity control, General methods for overfitting for parameter Optimization.

05 CO4

5

Decision analytic Thinking:

Various evaluation matrix, Estimation Cost and Benefits, creating baseline methods for

comparison. Plain Accuracy and its problem, Confusion Matrix, Problem with unbalance

data.

05 CO5

6

Visualizing Model Performance:

Visualization of model performance of model performance under various kind of

uncertainty, Profit curves, cumulative response curve, lift curve.

Area Under the ROC Curve (AUC).

08 CO6


1. B. L. S. Prakasa Rao, “A First Course in Probability and Statistics”, World Scientific, Cambridge University Press India, 2009.

2. L. Elden, “Matrix Methods in Data Mining and Pattern Recognition”, SIAM, Philadelphia, 2007.

3. L. N. Trefethen and David Bau, “Numerical Linear Algebra”, SIAM, Philadelphia, 1997.

4. D. S. Watkins, “Fundamentals of Matrix Computation”, 2nd Edition, Wiley, 2002.

5. Ian Goodfellow and Yoshua Bengio and Aaron Courville. “Deep Learning (DL)”, MIT Pess, 2016 (individual chapters freely

available online).

6. Mitchell, Tom, “Machine Learning” Tata McGraw-Hill, 2017.

7. Russell and Norvig, “Artificial Intelligence”, Third Edition, Prentice Hall, 2015.

https://www.deeplearningbook.org/



124

Evaluation Scheme:











125


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL2043 Data Science Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration (in


IAs

Mid Sem

Exam

MTETDLOL2043 Data Science

Lab -- -- -- -- -- -- 25 25 50


1. Introduction to python tool for data analytics science

2. basic statistics and visualization in python

3. implement linear and logistic regression

4. naive bayesian classifier

5. implement svm / decision tree classification techniques

6. implement clustering techniques

7. simulate principal component analysis

8. simulate singular value decomposition

9. visualize data using any plotting framework



126


Assessment:




127


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLO2044 Microwave Measurement & Design 03 -- -- 03 -- -- 03


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETDLO2044 Microwave

Measurement & Design 20 20 20 20 60 02 -- -- 100


● Electromagnetic Theory

● Computational Electromagnetics

● Antenna Theory

● Microwave Engineering

Course Objectives:

The aim of this course is to understand the concepts of microwave network analysis, Methods and limitation of different microwave

parameter measurement, understanding of Vector network analyzer, design various impedance matching devices and knowledge of

passive microwave components. Learners will also be able to apply basic microwave laboratory set up along with measurement of

parameters and apply VNA in the measurement of S parameters of different microwave devices.



128

Course Objectives:

The aim of this course is to understand the concepts of microwave network analysis, Methods and limitation of different microwave

parameter measurement, understanding of Vector network analyzer, design various impedance matching devices and knowledge of

passive microwave components.

Course Outcome:


CO1: Understand gain proficiency regarding microwave circuit concepts.

CO2: Understand the relation between different parameters in microwave circuits.

CO3: Design impedance matching networks.

CO4: Understand passive microwave components.

CO5: Apply basic microwave laboratory set up along with measurement of parameters.

CO6: Apply VNA in the measurement of S parameters of different microwave devices


1

Introduction: Introduction to microwave circuit concepts, Relation between [s], [z], [y]

parameter, Microwave circuits & theorems, Impedance matching, Passive microwave

components

8 CO1

2

Wavelength, Impedance, Power and Frequency Measurement: Methods of

wavelength measurements- Equivalent circuit of Cavity wave meters, Typical wave

meters, resonant cavities, Impedance measurement techniques, Reflectometer, Methods

of power measurements- bolometer, bridge balance technique, Calorimetric watt

meters, Methods of frequency measurements direct method - Interpolation method,

Standard wave reflectors, Measurement of reflection coefficient, Low, Medium, High

VSWR measurements, Standing wave pattern, Slotted Line section and its limitation.

10 CO2



129

3

Material Characterization through Microwave Measurements: Reflection Methods:

Coaxial-Line Reflection Method, Free-Space Reflection Method, Measurement of Both

Permittivity and Permeability Using Reflection Methods, Transmission/Reflection

Methods: Theory for Transmission/Reflection Methods, Coaxial AirLine Method

,Hollow Metallic Waveguide Method, Surface Waveguide Method , Free-Space Method,

Resonator Methods: Dielectric Resonator Methods, Coaxial Surface-Wave Resonator

Methods, Split-Resonator Method, Planar-Circuit Methods: Introduction, Stripline

Methods, Microstrip Methods, Coplanar-Line Methods.

10 CO3

4

Vector Network Analyzer: Vector Network analyzer, Concept and description,

Reflection and Transmission measurements, magnitude and Phase, measurement of S-

Parameters, SWR and Impedances measurements, errors and corrections.

08 CO4

5 Antennas measurements: Experimental set ups for measurement of radiation patterns,

gain, phase polarization, terminal impedance. 06 CO5

6

Microwave Integrated Circuit (MIC) Measurement: MIC Measurement, Testing and

Applications: MIC measurement system, measurement techniques – S parameter

measurement, noise measurement, MIC applications.

06 CO6


1. J.L. Altmen, D van, “Microwave circuit”, Nostrand Co., Inc.

2. R. E. Collins, “Foundations for microwave engineering”, John Wiley & Sons.

3. R. N. Ghosh, “Microwave Circuit Theory and Analysis”, McGraw Hill.

4. L. F. Chen, C. K. Ong, C. P. Neo, V. V. Varadan, Vijay K. Varadan, “Microwave Electronics: Measurement and Materials

Characterization”, John Wiley.

5. Joel P. Dunsmore, “Microwave Component Measurements (with Advanced VNA Techniques)”, Course Slides/Lab Handouts.

6. R.J. Collier, “Skinner, Microwave Measurements”, A.D. (3rd Edition).

7. Scott A. Wartenberg, “RF Measurements of Die and Packages”.

8. Gary E. Evans, “Antenna Measurement Techniques”.



130

Evaluation Scheme:











131


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTETDLOL2044 Microwave Measurement & Design

Lab -- 02 -- -- 01 -- 01


Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


2 IAs

Mid Sem

Exam

MTETDLOL2044 Microwave Measurement

& Design Lab -- -- -- -- -- -- 25 25 50


1. To study and measure Wavelength, Impedance and frequency.

2. To study and measure S-parameter with Vector Network Analyzer

3. To study Material Characterization through Microwave Measurements.

4. To study and measure Microwave Active Components.

5. To study and measure antenna characteristics.

6. To study and measure characterization of Amplifier through S-parameter measurements.

7. To study and measure Power spectrum, noise and non-linearity of Amplifier.

8. To study PCB manufacturing for microwave circuits and antennas.

9. To study and test characterization of circuits through RF probes.

10. To study and test high frequency antenna characterization in anechoic chamber.



132


Assessment:




133


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTILO2021 Research Methodology 03 -- -- 03 -- -- 03

Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration (in


IAs

Mid Sem

Exam

MTILO2021 Research

Methodology 20 20 20 20 60 02 -- -- 100

Course Pre-requisite: None

Course Description:

The objective of this course is to understand the Research Process and Methodology. It is aimed to enable students to identify research

problems and develop approaches for solving the research problems. It also introduces techniques for data collection, analysis and

interpretation. In this way this course enables the students to perform research.

Course Objectives:

To understand Research and Research Process

To acquaint students with identifying problems for research and develop research strategies

To familiarize students with the techniques of data collection, analysis of data and interpretation

To understand and apply different techniques for formulating research problem



134

Course Outcomes: - At the end of the course learner will able to

CO1: Understand basics of research concepts including objectives, issues and problems

CO2: Summarize and compare different types of research

CO3: Prepare a preliminary research design for projects in their subject matter areas

CO4: Accurately collect, analyze and report data

CO5: Present complex data or situations clearly

CO6: Review and analyze research findings

Module

No. Detailed Content Hrs. CO

1

Introduction and Basic Research Concepts

1.1 Research – Definition; Concept of Construct, Postulate, Proposition, Thesis, Hypothesis, Law,

Principle.Research methods vs Methodology

1.2 Need of Research in Business and Social Sciences

1.3 Objectives of Research

1.4 Issues and Problems in Research

1.5 Characteristics of Research:Systematic, Valid, Verifiable, Empirical and Critical.

07 CO1

2

Types of Research

2.1. Basic Research

2.2. Applied Research

2.3. Descriptive Research

2.4. Analytical Research

2.5. Empirical Research

2.6 Qualitative and Quantitative Approaches

07 CO2

3

Research Design and Sample Design

3.1 Research Design – Meaning, Types and Significance

3.2 Sample Design – Meaning and Significance Essentials of a good sampling

3.3 Stages in Sample Design Sampling methods/techniques Sampling Errors

07 CO3



135

4

Research Methodology

4.1 Meaning of Research Methodology

4.2. Stages in Scientific Research Process:

A. Identification and Selection of Research Problem

B. Formulation of Research Problem

C. Review of Literature

D. Formulation of Hypothesis

E. Formulation of research Design

F. Sample Design

G. Data Collection

H. Data Analysis

I. Hypothesis testing and Interpretation of Data

J. Preparation of Research Report

08 CO4

5

Formulating Research Problem

5.1 Considerations: Relevance, Interest, Data Availability, Choice of data,

5.2 Analysis of data, Generalization and Interpretation of analysis 05 CO5

6

Outcome of Research

6.1 Preparation of the report on conclusion reached

6.2 Validity Testing & Ethical Issues

6.3 Suggestions and Recommendation

05 CO6

Text and Reference Books:

1. Dawson, Catherine, “Practical Research Methods”, New Delhi, UBS Publishers Distributors, 2002.

2. Kothari, C.R., “Research Methodology-Methods and Techniques”, New Delhi, Wiley Eastern

Limited, 1990.

3. Kumar, Ranjit, “Research Methodology-A Step-by-Step Guide for Beginners”, 2nd ed.,

Singapore, Pearson Education, 2005.

4. Best and Kahn, “Research Methodology”, PHI Limited.



136

5. Garg, B.L., Karadia, R., Agarwal, F. and Agarwal, “An introduction to Research Methodology, RBSA

Publishers, U.K., 2002.

6. Sinha, S.C. and Dhiman, A.K., “Research Methodology”, EssEss Publications, 2 volumes, 2002.

Evaluation Scheme:








lecture hours as mentioned in the syllabus



137


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTILO2022 Probability and Random Variables 03 -- -- 03 -- -- 03

Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTILO2022 Probability and Random

Variables 20 20 20 20 60 02 -- -- 100


Basic probability theory.

Basics of Numerical Analysis

Course Description:

Concepts in probability and random variables/ processes play a fundamental role in understanding various aspects of in different

domains and problems. Characterizing of several real-life events and problems requires knowledge of principles of random variables

and processes. This course is designed to serve as a basic course towards introducing the students to various aspects of probability from

the perspective of problem solving. Thus, it will focus on basic concepts in probability, distribution, random variables and random

processes.



138

Course Objectives:

To familiarize the students with statistical techniques for rela life problems.

To understand and be able to apply probabilistic techniques for solving real world decision making problems.


CO1: Test the correlation between the given databases.

CO2: To prepare and set up the regression models for the datasets.

CO3: Analyze the time series and build the models for time series.

CO4: Understand the concepts of probability.

CO5: Analyze and understand the discrete and continuous distributions.

CO6: Apply the knowledge of testing on data and samples.


1

Correlation

1.1 Definition, meaning and uses of Correlation

1.2 Scatter Diagram, Merits and limitations, Graphic method

1.3 Covariance, properties of covariance, limitations

1.4 Difference between variance and co-variance

1.5 Karl Pearson’s Coefficient of correlation (r), properties and examples

1.6 Spearman’s Rank correlation coefficient (R) (with repeated and non-repeated

ranks) properties and examples

06 CO1

2

Regression Analysis

2.1 Definition, meaning and uses of regression analysis

2.2 Difference between Correlation and regression

2.3 Regression Models (lines of regression)

07 CO2



139

2.4 Fitting of line of regression of Y on X

2.5 Fitting of line of regression of X on Y

3

Analysis of Time Series

3.1 Meaning, essential requirements and main objective of Time series

3.2 Components of time series

3.3 Additive and Multiplicative models of Time series

3.4 Fitting of straight line (first degree) trend by least square methods

3.5 Fitting of parabolic (second degree) trend by least square methods

3.6 Fitting of exponential (𝑦 = 𝑎𝑏𝑥) trend by least square methods

07 CO3

4

Probability

4.1 Definition and basics of probability, conditional probability,

4.2 Total Probability Theorem and Bayes’ theorem (Inverse Probability Theorem)

4.3 Discrete and continuous random variable with probability distribution and

probability density function.

4.4 Expectation of random variables with mean, variance and standard deviation,

moment generating function up to four moments.

4.5 Skewness and Kurtosis of distribution (data)

06 CO4

5

Probability Distribution

5.1 Binomial Distribution: Meaning, examples, properties with applications

5.2 Poisson Distribution: Meaning, examples, properties with applications

5.3 Normal Distribution: Meaning, examples, properties with applications

06 CO5

6

Sampling Theory

6.1 Sampling distribution,

6.2 Test of Hypothesis, Level of Significance, Critical region, One-tailed, and two-

tailed test, Degree of freedom.

6.3 Students’ t-distribution (Small sample). Test the significance of mean and

Difference between the means of two samples. Chi-Square Test: Test of goodness of fit

and independence of attributes, Contingency table.

07 CO6



140

Text Books: 1. C. B. Gupta and Vijay Gupta, “An Introduction to Statistical Methods”, Vikas Publication 23rd

Edition.

2. Dr. P. C. Tulsian and Bharat Jhunjhnuwala, “Business Statistics”, S. Chand, 2nd Edition.

Reference Books: 1. T. Veerarajan, “Probability, Statistics and Random Processes”, McGraw-Hill education.

2. Murray Spiegel, “Probability and Statistics”, Schaum’s Outline Series, McGraw-Hill education.

3. Jay Devore, “Probability and Statistics for Engineering and the Sciences”, Cengage Learning.

4. Ludwig Fahrmeir, “Regression Models”, Methods and Applications, Springer Verlag.

5. Peter Bikel and Doksum, “Mathematical Statistics Basic Ideas and Selected Topics Vol-I”, Prentice

Hall.

Evaluation Scheme:











141


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTILO2023 Project Management 03 -- -- 03 -- -- 03

Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration (in


IAs

Mid Sem

Exam

MTILO2023 Project

Management 20 20 20 20 60 02 -- -- 100


Course Description:

This course develops a foundation of concepts and solutions that supports the planning, scheduling, controlling, resource

allocation, and performance measurement, closing activities required for successful completion of a project. It explains

organizational structures in which projects are executed and the importance of qualitative and quantitative analysis tools.

Financial aspects required for project like procurement, bidding, budgeting and techniques related with those are introduced.

Course Objectives:

To familiarize the students with the use of a Project Management techniques and tools used in various industry sectors for achieving

success in projects

To understand and be able to apply processes and techniques throughout the life cycle of a project from initiation to closure



142


CO1: Understand what are projects and what is the importance of management and project manager.

CO2: Analyse and initiate projects based on numeric and non-numeric criteria. Design a project proposal and build project teams.

CO3: Analyze the effect of different organizational structures on the execution of projects. Perform Project estimation and budgeting.

Understand role of project management office.

CO4: Perform project planning activities including risk planning, scheduling, team building and resource allocation.

CO5: Perform project control activities like monitoring & control, auditing, reporting, tracking, risk mitigation & control.

CO6: Perform proper closure of different types of projects. Apply the techniques learned in the course in the execution of real-life

projects.

Module


1

Project Management Fundamentals Definition of a project, Necessity of project management,

Triple constraints, Project life cycles, Project phases, Qualities of project manager, Role of

project manager. Project management in various organization structures. 6 CO1

2

Initiation How to get a project started, Selecting project strategically, Project selection models

(Numeric /Scoring Models and Non-numeric models), Project portfolio process, Project sponsor

and creating charter; Project proposal. Effective project team, Stages of team development &

growth

6 CO2

3

Project Budgeting and Estimation Project Plan, Work Breakdown structure (WBS) and linear

responsibility chart, Interface Co-ordination, Project cost estimation and budgeting, Top down

and bottoms up budgeting. 6 CO3

4

Project Planning and Management Networking and Scheduling techniques. PERT, CPM,

GANTT chart. Crashing project time, Resource loading and leveling, Goldratt's critical chain,

Project Stakeholders and Communication plan. Risk Management in projects: Risk management

planning, Risk identification and risk register. Qualitative and quantitative risk assessment,

Project procurement management. Change Management

9 CO4



143

5

Project Monitoring and Control Planning monitoring and controlling cycle. Information needs

and reporting, engaging with all stakeholders of the projects.

Team management, communication and project meetings. Earned Value management

techniques for measuring value of work completed; Using milestones for measurement; change

requests and scope creep. Project audits.

6 CO5

6

Project Closure Customer acceptance; Reasons of project termination, Various types of project

Terminations, Process of project termination, completing a final report; doing a lessons learned

analysis;

acknowledging successes and failures; Project management templates and other resources. Case

studies of successful and failed projects

6 CO6

Text Books:

1. Jack Meredith & Samuel Mantel, “Project Management: A managerial approach”, 10th ed., Wiley

India.

2. “A Guide to the Project Management Body of Knowledge (PMBOK® Guide)”, 6th ed., Project

Management Institute PA, USA.

Reference Books:

1. Harold Kerzner, “Project Management: A Systems Approach to Planning, Scheduling, and

Controlling”, 12th ed., Wiley.

Evaluation Scheme:







144







145

Subject

Code Subject Name

Theory

Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTILO2024 Disaster Management and Mitigation

Measures 03 -- -- 03 -- -- 03

Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


2 IAs

Mid Sem

Exam

MTILO2024 Disaster Management and

Mitigation Measures 20 20 20 20 60 02 -- -- 100


Course Description:

This course aims for disaster managers eventually to work themselves out of their job. The ultimate success of disaster management would

be the elimination of the underlying causes of disasters which would contribute to disaster prevention. Obviously, total prevention will

not be feasible, but minimizing the people's vulnerability to disaster and responding to emergencies in positive ways will make an

enormous impact on the current deadly state of disaster events. This enhances awareness of Disaster Risk Management institutional

processes in India and builds skills to respond to disasters.

Course Objectives:

To understand the various types of disaster occurring around the world.

To identify extent and damaging capacity of a disaster.



146

To study and understand the means of losses and methods to overcome /minimize it.

To understand role of individual and various organization during and after disaster.

To know warning systems, their implementation and based on this to initiate training to a laymen.

To understand application of GIS in the field of disaster management.

To understand the emergency government response structures before, during and after disaster.

Course Outcomes: At the end of the course learner will able to,

CO1: Acquire fundamentals of disasters, long term effects global warming, perspective and concepts of human life.

CO2: Understand natural as well as man-made disaster and their extent and possible effects on the economy.

CO3: Planning of national importance structures based upon the previous history.

CO4: Understand government policies, acts and various organizational structure associated with an emergency.

CO5: Know the simple do’s and dont’s in such extreme events and act accordingly.

CO6: Know the preventive and mitigation disaster measures.

Module


1

Introduction: Definition of Disaster, hazard, global and Indian scenario,

general perspective, importance of study in human life, Direct and indirect

effects of disasters, long term effects of disasters. Introduction to global

warming and climate change.

04 CO1



147

2

Natural Disaster and Manmade disasters: Natural Disaster: Meaning and

nature of natural disaster, Flood, Flash flood, drought, cloud burst,

Earthquake, Landslides, Avalanches, Volcanic eruptions, Mudflow,

Cyclone, Storm, Storm Surge, climate change, global warming, sea level

rise, ozone depletion. Manmade Disasters: Chemical, Industrial, Nuclear

and Fire Hazards. Role of growing population and subsequent

industrialization, urbanization and changing lifestyle of human beings in

frequent occurrences of manmade disasters.

08 CO2

3

Disaster Management, Policy and Administration: Disaster

management: meaning, concept, importance, objective of disaster

management policy, disaster risks in India, Paradigm shift in disaster

management. Policy and administration: Importance and principles of

disaster management policies, command and co-ordination of in disaster

management, rescue operations-how to start with and how to proceed in due

course of time, study of flowchart showing the entire process.

06 CO3

4

Institutional Framework for Disaster Management in India: Importance

of public awareness, Preparation and execution of emergency management

programme. Scope and responsibilities of National Institute of Disaster

Management (NIDM) and National disaster management authority

(NDMA) in India. Methods and measures to avoid disasters, Management

of casualties, set up of emergency facilities, importance of effective

communication amongst different agencies in such situations. Use of

Internet and softwares for effective disaster management. Applications of

GIS, Remote sensing and GPS in this regard.

07 CO4



148

5

Financing Relief Measures: Ways to raise finance for relief expenditure,

Role of government agencies and NGO’s in this process, Legal aspects

related to finance raising as well as overall management of disasters.

Various NGO’s and the works they have carried out in the past on the

occurrence of various disasters, Ways to approach these teams. International

relief aid agencies and their role in extreme events.

07 CO5

6

Preventive and Mitigation Measures: Pre-disaster, during disaster and

post-disaster measures in some events in general, Structural mapping: Risk

mapping, assessment and analysis, sea walls and embankments, Bio shield,

shelters, early warning and communication. Non-Structural Mitigation:

Community based disaster preparedness, risk transfer and risk financing,

capacity development and training, awareness and education, contingency

plans. Do’s and dont’s in case of disasters and effective implementation of

relief aids.

07 CO6

References:

1. Harsh K.Gupta, “Disaster Management”, Universities Press Publications.

2. O.S. Dagur, “Disaster Management: An Appraisal of Institutional Mechanisms in India”, published

by Centre for land warfare studies, New Delhi, 2011.

3. Damon Copolla, “Introduction to International Disaster Management”, Butterworth Heinemann

Elsevier Publications.

4. Jack Pinkowski, “Disaster Management Handbook”, CRC Press Taylor and Francis group.

5. Rajdeep Dasgupta, “Disaster management & rehabilitation”, Mittal Publications, New Delhi.

6. R B Singh, “Natural Hazards and Disaster Management, Vulnerability and Mitigation”, Rawat

Publications.



149

Evaluation Scheme:











150


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTILO2025 Financial management 03 -- -- 03 -- -- 03

Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration (in


IAs

Mid Sem

Exam

MTILO2025 Financial

Management 20 20 20 20 60 02 -- -- 100


Course Description:

Overall Objective of this course is to develop awareness among you about the importance and need of learning techniques for managing

finances either on a project, in an organization or in a profit making unit. The course goes into details of financial planning, measurement,

analysis and eventually controlling the finances. Varies techniques and tools useful for managing the finances and budgeting will be

explored in this course.

Course Objectives:

To understand the operational nuances of aIndian financial system, instruments and market

To study concepts of value of money, returns and risks, corporate finance, working capital and its management

To study technique of making decisions related to finance function.



151


CO1: Understand Indian finance system and corporate finance.

CO2: Understand Present and future value of money.

CO3: Evaluate Risk and return on investment.

CO4: Under the importance of working capital and portfolios.

CO5: Possess the techniques of managing finance in an organization.

CO6: Take investment, finance as well as dividend decisions

Module


1

The Financial Systems: Functions of the Financial System, Financial Assets, Financial

Markets, Financial Market Returns, Financial Intermediaries, Regulatory Infrastructure,

Growth and Trends in the Indian Financial System. Overview of Financial Statements—

Balance Sheet, Profit and Loss Account, and Cash Flow Statement; Purpose of Financial Ratio

Analysis; Liquidity Ratios; Efficiency or Activity Ratios; Profitability Ratios; Capital

Structure Ratios; Stock Market Ratios; Limitations of Ratio Analysis.

06 CO1

2

Time value of Money: Time Lines and Notation, Future Value of a Single Amount,Present

Value of a Single Amount, Future Value of an Annuity, Present Value of an Annuity, Present

Value of a Perpetuity, Intra-Year Compounding and Discounting.

08 CO2

3

Risk and Return: Historical Returns and Risk, Expected Return and Risk of a Single Security

and a Two-security Portfolio,Risk and Return of a Single Security and a Two-security

Portfolio, Measurement of Market Risk , Determinants of Beta , Relationship Between Risk

and Return.

06 CO3

4

Techniques of Capital Budgeting: Capital Budgeting Process, Project Classification,

Investment Criteria, Net Present Value, Benefit-Cost Ratio, Internal Rate of Return, Modified

Internal Rate of Returns (MIRR), Payback Period, Accounting Rate of Return, Investment

04 CO4



152

Appraisal in Practice.

Concepts of Meaning Working Capital; Importance and Factors Affecting an Entity‘s Working

Capital Needs; Management of Inventories; Management of Receivables; and Management of

Cash and Marketable Securities.

5

The Cost of Capital: Cost of Debt and Preference, Cost of Equity, Determining the

Proportions, Weighted Average Cost of Capital, Weighted Marginal Cost of Capital,

Determining the Optimal Capital Budget, Divisional and Project Cost of Capital, Floatation

Cost and the Cost of Capital, Factors Affecting the Weighed Average Cost of Capital

09 CO5

6

Capital Structure and Firm Value: Assumptions and Definitions, Net Income Approach,

Net Operating Income Approach, Traditional Position, Modigliani and Miller Position,

Taxation and Capital Structure, Tradeoff Theory, Signaling Theory, Dividend Policy and Firm

Value, Miller and Modigliani Position

06 CO6

Text Books:

1. Financial Management Theory & Practice by Prasanna Chandra, Publisher: TMH, New Delhi 2004

2. Fundamentals of Financial Management, 13th Edition (2015) by Eugene F. Brigham and Joel F. Houston; Publisher: Cengage

Publications, New Delhi.

3. Fundamentals of Financial Management by Van Horne, Publisher: Prentice Hall of India.

Reference Books:

1. Financial Management, 11th Edition (2015) by I. M. Pandey; Publisher: S. Chand (G/L) & Company Limited, New Delhi

2. Indian Financial System, 9th Edition (2015) by M. Y. Khan; Publisher: McGraw Hill Education, New Delhi.

3. Advanced Accounting by Gupta R.L. and RadhaSwamy M., Publisher: Sultan Chand & Sons, New Delhi.



153

Evaluation Scheme:











154


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits

MTILO2026 IPR and Patenting 03 -- -- 03 -- -- 03

Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration (in


IAs

Mid Sem

Exam

MTILO2026 IPR and

Patenting 20 20 20 20 60 02 -- -- 100


Course Description:

This course helps to understand intellectual property rights protection system and to promote the knowledge of Intellectual Property

Laws of India as well as International treaty procedures. To get acquaintance with Patent search and patent filing procedure and

applications. IPR internalization process to help the researchers to set targeted objectives in their research project and also to design

and implement their research to clearly differentiate their work vis-a-vis the existing state of knowledge/ prior art.

Course Objectives:

To understand intellectual property rights protection system.

To promote the knowledge of Intellectual Property Laws of India as well as International treaty procedures.

To get acquaintance with Patent search and patent filing procedure and applications.

To get familiarize with different patent databases.



155


CO1: Understand Intellectual Property Rights and importance.

CO2: Demonstrate enforcement of intellectual property rights.

CO3: Work for development, promotion, protection, compliance, and enforcement of Intellectual Property and Patenting.

CO4: Inspect emerging issues in IPR.

CO5: Assist individuals and organizations in capacity building,

CO6: Understand national and international patent filing procedure.

Module

No.

Detailed Contents Hrs CO

1

1.1 Introduction to Intellectual Property Rights (IPR): Meaning of IPR, Different

category of IPR instruments - Patents, Trademarks, Copyrights, Industrial Designs,

Plant variety protection, Geographical indications, Transfer of technology etc.

1.2 Importance of IPR in Modern Global Economic Environment: Theories of IPR,

Philosophical aspects of IPR laws, Need for IPR, IPR as an instrument of development.

07 CO1

2

2.1 Enforcement of Intellectual Property Rights: Introduction, Magnitude of problem,

Factors that create and sustain counterfeiting/piracy, International agreements,

International organizations (e.g. WIPO, WTO) active in IPR enforcement.

2.2 Indian Scenario of IPR: Introduction, History of IPR in India, Overview of IP laws in

India, Indian IPR, Administrative Machinery, Major international treaties signed by

India, Procedure for submitting patent and Enforcement of IPR at national level etc.

07 CO2

3 Emerging Issues in IPR: Challenges for IP in digital economy, e-commerce, human

genome, biodiversity and traditional knowledge etc. 05 CO3

4 Basics of Patents: Definition of Patents, Conditions of patentability, Patentable and non- 07 CO4



156

patentable inventions, Types of patent applications (e.g. Patent of addition etc.), Process

Patent and Product Patent, Precautions while patenting, Patent specification Patent

claims, Disclosures and non-disclosures, Patent rights and infringement, Method of

getting a patent

5

Patent Rules: Indian patent act, European scenario, US scenario, Australia

scenario, Japan scenario, Chinese scenario, Multilateral treaties where India is a member

(TRIPS agreement, Paris convention etc.)

07 CO5

6

6.1 Procedure for Filing a Patent (National and International): Legislation and Salient

Features, Patent Search, Drafting and Filing Patent Applications, Processing of patent,

Patent Litigation, Patent Publication etc, Time frame and cost, Patent Licensing, Patent

Infringement

6.2 Patent databases: Important websites, Searching international databases

06 CO6

Text and Reference Books: -

1. Rajkumar S. Adukia, “A Handbook on Laws Relating to Intellectual Property Rights in India”, The Institute of Chartered Accountants

of India, 2007.

2. Keayla B K, “Patent system and related issues at a glance”, Published by National Working Group on Patent Laws.

3. T Sengupta, “Intellectual Property Law in India”, Kluwer Law International. 2011.

4. Tzen Wong and Graham Dutfield, “Intellectual Property and Human Development: Current Trends and Future Scenario”, Cambridge

University Press, 2010.

5. Cornish, William Rodolph & Llewelyn, David, “Intellectual Property: Patents, Copyrights, Trade Marks and Allied Right”, 7th

Edition, Sweet & Maxwell, 2010.

6. LousHarns, “The enforcement of Intellactual Property Rights: A Case Book”, 3rd Edition, WIPO, 2012.

7. Prabhuddha Ganguli, “Intellectual Property Rights”, 1st Edition, TMH, 2012.

8. R Radha Krishnan & S Balasubramanian, “Intellectual Property Rights”, 1st Edition, Excel Books, 2012.

9. M Ashok Kumar and Mohd Iqbal Ali, “Intellectual Property Rights”, 2nd Edition, Serial Publications.

10. Kompal Bansal and Praishit Bansal, “Fundamentals of IPR for Engineers”, 1st Edition, BS Publications, 2012.



157

11. “A Manual on Intellectual Property Rights”, Entrepreneurship Development and IPR Unit, BITS Pilani, 2007.

12. Mathew Y Maa, “Fundamentals of Patenting and Licensing for Scientists and Engineers”, World Scientific Publishing Company,

2009.

13. Indian Patent Acts and Rules (Online – Indian patent office)

Evaluation Scheme:











158

Master of Technology in Electronics & Telecommunication Engineering

Semester-III

Course Code Course Name Teaching Scheme

(Contact Hours) Credits Assigned

Theory Practical Tutorial Theory Practical Tutorial Total



Total -- 30 -- -- 15 -- 15

Evaluation Scheme

Semester-III

Course Code Course Name IA1 IA2 AVG of 2 IAs ESE Exam Hrs TW Pr/Or Total

MTETS301 Special Topic Seminar -- -- -- -- -- 50 50 100

MTETD302 M. Tech Thesis Dissertation I -- -- -- -- -- 50 50 100

Total -- -- -- -- -- 100 100 200



159


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits


Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration (in


IAs

Mid Sem

Exam

MTETS301 Special Topic

Seminar -- -- -- -- -- -- 50 50 100

Guidelines for Special Topic Seminar

1. Seminar should be based on thrust areas in Information Technology.

2. Students should do literature survey and identify the topic of seminar and finalize in consultation with Guide/Supervisor. Students

should refer multiple literature (at least 10 papers from Refereed Journals) and understand the topic and compile the report in standard

format and present in front of Panel of Examiners.

3. The seminar report should be compulsorily prepared in Latex.

4. The seminar report should be checked for plagiarism and the similarity index should not exceed 30%.

Seminar would be assessed based on following points

1. Quality of Literature survey and novelty in the topic

2. Relevance to the specialization

3. Understanding of the topic

4. Quality of written and oral presentation



160


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits


Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration (in


IAs

Mid Sem

Exam

MTETD302 M. Tech Thesis

Dissertation I -- -- -- -- -- -- 50 50 100

Guidelines for Dissertation I

1. Students should do literature survey and identify the problem for dissertation and finalize it in consultation with the Guide/Supervisor.

2. Students should review multiple literature and understand the problem. The problem should be relevant and should have research

potential.

3. Students should attempt solution to the problem by analytical/simulation/experimental methods. The solution is to be validated with

proper justification and compiled into a report in standard format.

4. All reports should be compulsorily prepared in Latex.

5. Reports should be checked for plagiarism and the similarity index should not exceed 30%.



161

Guidelines for Assessment of Dissertation I

1. Dissertation I would be assessed based on the following points:

a. Quality of literature survey and novelty in the problem

b. Clarity of problem definition and feasibility of problem solution

c. Relevance to the specialization

d. Clarity of objective and scope

2. Dissertation I would be assessed through a presentation by a panel of examiners appointed by the Head of the Department.

3. After successful completion of Dissertation I, students should immediately submit synopsis of their Dissertation I to the University

for Approval.



162

Master of Technology in Electronics & Telecommunication Engineering

Semester-IV

Course Code Course Name Teaching Scheme

(Contact Hours) Credits Assigned

Theory Practical Tutorial Theory Practical Tutorial Total


Total -- 30 -- -- 15 -- 15

Evaluation Scheme

Semester-IV

Course Code Course Name T1 T2 AVG ESE Exam Hrs TW Pr/Or Total

MTETD401 M. Tech Thesis Dissertation II -- -- -- -- -- 100 100 200

Total -- -- -- -- -- 100 100 200



163


Hrs

Practical

Hrs

Tutorial

Hrs

Theory

Credit

Practical/Oral

Credit

Tutorial

Credits

Total

Credits


Subject

Code Subject Name

Examination Scheme

Theory Marks

Term

Work

Pract.

/Oral Total


Exam

Exam Duration


IAs

Mid Sem

Exam

MTETD401 M. Tech Thesis

Dissertation II -- -- -- -- -- -- 100 100 200

Guidelines for Dissertation II

1. Students to come up with solution to the problem which is efficient and is justified by the results obtained.

2. Students should validate the solution and analyze the impact of this solution.

3. All reports should be compulsorily prepared in Latex.

4. Reports should be checked for plagiarism and the similarity index should not exceed 30%.

Guidelines for Assessment of Dissertation II

1. Dissertation II would be assessed based on the following points:

a. Quality of literature survey and novelty in the problem

b. Clarity of problem definition and feasibility of problem solution



164

c. Relevance to the specialization or current research / industrial trends

d. Clarity of objective and scope

e. Quality of work attempted

f. Validation of results

g. Quality of written report and oral presentation

2. Dissertation II would be assessed through a presentation by a Panel of Examiners. After successful completion of Dissertation II,

students should immediately submit their MTech Thesis to the University.

3. Students should publish at least two papers based on the work in reputed International /National Conference/Journal (desirably

should be ISI/Scopus/SCI indexed and only in referred Journal).

Master of Technology (M.Tech.) in Electronics and ...

Documents

Transcript of Master of Technology (M.Tech.) in Electronics and ...