1

Wireless and Mobile Communications

2

Link Budget

− It is the accounting of all of the gains and losses from the Transmitter, through the medium (free space, cable, waveguide, fiber, etc.) to the Receiver in a telecommunication system.

− Simple link budget equation Received Power = Transmitted Power + Gains −

Losses

− Accounts for the attenuation of the transmitted signal due to Propagation Antenna gains Feedline and miscellaneous losses.

3

Link Budget

− Randomly varying channel gains such as fading are taken into account by adding some margin (depending on the anticipated severity of its effects ).

− The amount of margin required can be reduced by the use of mitigating techniques such as antenna diversity or frequency hopping.

− Link budgets are required for different terrains

4

Link Budgets

5

Link Budgets

6

Maximum Allowable Path Loss

7

Maximum Allowable Path Loss

8

Link Budgets – Forward and Reverse

9

Link Budgets – Forward and Reverse

10

Link Budgets – Forward and Reverse

11

Reverse Link Budget Example

12

13

Reverse Link Budgets Example

1414

Link Budget

Free Space Loss Path

Frequency 0.9000 GHzERP 50.0000 WattsERP in dBm 46.9897 dBmTransmission Line Loss 0.0000 dBTx Antenna Gain 0.0000 dBiPath Length 0.1500 KmFree Space Path Loss 75.0484 dBRx Antenna Gain 0.0000 dBiRx Transmission Line Loss 0.0000 dBRx Signal Strength -28.0587 dBmRx Threshhold -85.0000 dBmFade Margin 56.9413 dB

RF Link Budget Calculator

15

Propagation Models

16

Types Of Propagation Models And Their Uses

17

−Practical Link Budget Design using Path Loss Models Log-distance Path Loss Model Log-normal Shadowing

−Outdoor Propagation Models Longley-RIce Model Okumura Model Hata Model

−Indoor Propagation Models

Propagation Models

18

Path Loss Models

−Models to estimate the received signal level as a function of distance

−Prediction of the Signal to Noise Ratio

−Path Loss Models

Log-distance Path loss model

Log-normal shadowing

19

Uses the idea that both theoretical and empirical evidence suggests that average received signal strength decreases logarithmically with distance , whether in outdoor or indoor radio channels

To measure received signal strength near to transmitter and approximate to different distances based on above “reference” observation

Log-distance Path loss model

20

Log-distance Path Loss Model

−A radio propagation model that predicts the path loss that a signal encounters inside

a building or densely populated areas over distance.

−The average large-scale path loss for an arbitrary T-R separation is expressed as a function of distance by using a path loss exponent “ n”.

21

• n = Path Loss Exponent • Indicates the rate at which the path loss increases with distance• The value of n depends on the specific propagation

environment.• In free space, n = 2• When obstructions are present, n > 2

Log-distance Path Loss Model

The Mean loss in dB follows the power law .Average power (in dB) decreases proportional to log of distanceThe Mean loss in dB follows the power law .Average power (in dB) decreases proportional to log of distance

22

• d0 = the close-in reference distance • In large coverage cellular systems 1 km reference

distances are commonly used • The reference path loss is calculated using the

“Free space path loss formula" or through field measurements at distance d0.

• d = T-R separation distance

• “bar” means the average of many “PL” values at a given value of d (T-R separation.)

Log-distance Path Loss Model

23

Log-distance Path Loss Model

24

− Limitations of “Log-distance path loss normal Model”

Gives only the average value of path loss.

Does not consider the fact that the surrounding environmental clutter may be vastly different at two different locations having the same T-R separation.

Thus measured signals are different than the average value predicted

Log-Normal Shadowing

25

Log-normal shadowing

− The long-term variation in the mean level is known as shadowing or log-normal fading. This fading caused by shadowing.

− Observes that the environment can be vastly different at two points with the same distance of separation.

− Shadowing occurs when objects block LOS between transmitter and receiver

26

Log-normal shadowing

− Measurements have shown that at any value of d, the path loss PL(d) at a particular location is random and distributed log-normally

− A simple statistical model can account for unpredictable “shadowing”

Add a Zero -mean Gaussian RV to Log-Distance PL The measured loss in dB varies about this mean according to a

zero-mean Gaussian RV, Xσ, with standard deviation σ

• Xσ : zero mean Gaussian random variable, a “bell curve”

27

− σ is the standard deviation that takes into account received signal strength variations due to shadowing

− n & σ are computed from measured data for different area types

Log-Normal Shadowing

28

Log-Normal Model

− This distribution is applicable where the propagation environment has high rising structures like tall buildings and trees.

− The signal does not adopt different propagation paths immediately after it is transmitted from the antenna.

− Rather, it undergoes through multiple reflections or scattering through tall structures prior to adopting multiple paths to the receiver.

− Therefore, the signal reaching the receiver will not be the result of single scattering effect but will be the result of multiple scattering.

29

− Multiple scattering introduces further fluctuation in the received signal.

− The long-term variation in the mean level is known as shadowing

or log-normal fading. This fading is caused by shadowing.

− Accounts for random variations in received power observed over distances comparable to the widths of buildings

− Extra transmit power (a fading margin) must be provided to compensate for these fades.

− Log normal distribution typical model for random attenuation

− Random due to random number and type of obstructions

Log-Normal Model

30

− The probability density function and cumulative distribution functions are given by

, r >0

− where are the standard deviation and mean

2102

log rP(r) exp

2

1

r

and

Log-Normal Model

31

Log-normal Distribution

MM

2

p(M)

The pdf of the received signal level− where M is the true received signal level m in decibels, i.e., 10log10

m, M is the area average signal level, i.e., the mean of M, − is the standard deviation in decibels

32

− To calculate large-scale median transmission loss relative to free space loss

− Available as a computer program to calculate large-scale median transmission loss relative to free space loss over irregular terrain for frequencies between 20 MHz and 10 GHz

− Geometric Optics Techniques (primarily the 2-ray ground reflection model) are used to predict signal strengths within the radio horizon.

− Diffraction losses over isolated obstacles are estimated using the Fresnel-Kirchoff knife-edge models

Longley Rice model

33

−Inputs of the program the transmission frequency Path length Polarization Antenna heights Surface refractivity Effective radius of earth Ground conductivity Ground dielectric constant Climate

Longley Rice model

34

−Two modes of operation −Point-to-point mode prediction

When a detailed terrain path profile is available

−Area mode prediction When a detailed terrain path profile not

available

Provides techniques to estimate the path-specific parameter

Longley Rice model

35

−Modifications and corrections Radio propagation in urban areas for mobile

• Introduction of an excess term as an allowance for the additional attenuation due to urban clutter near the receiving antenna.

• Urban factor (UF)

Longley Rice model

36

−Shortcoming Does not provide a way of determining

corrections due to environmental factors in the immediate vicinity of the mobile receiver

Multipath not considered.• Does not consider correction factors to account for

the effects of buildings and foliage

Longley Rice model

37

Okumura Model

−Used for signal prediction in urban areas

−Applicable for frequencies in the range 150 MHz to 1920 MHz (Extrapolated up to 3000 MHz)

−Applicable for distances of 1 km to 100 km.

−Totally based on measured data and does not provide any analytical explanation.

38

Okumura Model− Median Attenuation Curve

Okumura developed a set of curves giving the median attenuation (Amu ) relative to free space (Amu), in an urban area over a quasi-smooth terrain with a base station effective antenna height (hte) of 200 m and a mobile antenna height (hre) of 3m

These curves were developed from extensive measurements using vertical omni-directional antennas at both the base and mobile,

Plotted as a function of • frequency in the range 100 MHz to 1920 MHz and • distance from the base station in the range 1 km to 100 km.

39

Structure of the Okumura Model

40

Okumura Model

41

−Advantages Simplest best in terms of accuracy in path loss

prediction for mature cellular and land mobile radio systems in cluttered environments.

It is very practical and has become a standard for system planning in modern land mobile radio systems in Japan

Okumura Model

42

−Disadvantages Model is slow in response to rapid changes in

terrain, Model is fairly good in urban and suburban

areas, but not as good in rural areas.

Okumura Model

43

Hata Model

44

Hata Model− Empirical formulation of the graphical path loss data

provided by Okumura, and is valid from 150 MHz to 1500 MHz.

− Hata presented the urban area propagation loss as a standard

formula and supplied correction equations for application to

other situations

45

Hata Model

46

Hata Model – Morphology

4747

Indoor Propagation Models− Indoor radio channel differs from traditional mobile

radio channel because of :

distances variability of the environment

− Propagation within buildings is strongly influenced by

layout of the building construction materials building type

48

Indoor Propagation Models

−Indoor radio propagation is dominated by the same mechanisms as outdoor: Reflection diffraction and scattering.

49

Indoor Propagation Models− Indoor propagation models

Log-distance path loss model Ericsson multiple breakdown model