Lecture 1 Introduction

I-Hsiang WangNational Taiwan University

ihwang@ntu.edu.tw

2018.09.13

Principle of Communications, Fall 2018

Outline• The basic architecture of communication systems

• Source-channel separation

• Overview of this course

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A Communication System

• The simplest point-to-point abstraction

• By nature/applications: source, channel, destination

• Engineers’ design: the encoder + the decoder

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Encoder Channel DecoderSource Destination

Noise

Source and Channel

• The (information) source‣ generates the message to be delivered‣ message: text, audio, image, video, etc.. → abstracted into signals‣ continuous-time and continuous-valued signals → waveforms!

• Channel‣ abstraction of the physical medium: light, sound, wire, fiber, EM

radiation, etc.‣ distorts the transmitted signal → noisy channel (stochastic models)

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Encoder Channel DecoderSource Destination

Noise

Encoder and Decoder

• The Encoder‣ converts the message into physical signals ready for transmission‣ functions include sampling, quantization, compression,

modulation, error-correction coding, etc.

• The Decoder‣ reconstructs the message from the received signals‣ depending on the goal of the destination, can also carry out other

tasks such as computing a function of the messages.

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Encoder Channel DecoderSource Destination

Noise

A Digital Communication System

• A digital communication system uses digital sequence (bits) as an interface between source coding and channel coding

• Why separation?‣ Digital hardware is cheap, reliable, and scalable. ‣ Source coding and channel coding can be independently designed. ‣ Separation attains optimal transmission efficiency (Shannon).‣ Bits as the universal currency of the digital world → a channel can be extended to a network

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SourceEncoderSource

NoisyChannel

ChannelEncoder

Destination SourceDecoder

ChannelDecoder

Binary Interface

Bits

Bits

message waveform

signal waveform

Source Coding

• Sampling: ‣ (continuous-time) waveform → (discrete-time) sequence‣ (Review: Sampling Theorem, Nyquist Rate)

• Quantization: ‣ continuous-valued seq. → discrete-valued seq.

• Compression: ‣ discrete-valued seq. → bit seq., remove redundancy

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input (message) waveform

Sampler Quantizer Discrete Encoder

Discrete Decoder

Table LookupFilter

output (message) waveform

analog sequence

discrete sequence

Binary Interface

Source Coding

s(t)

s(t){s[m]}

{s[m]}

{dm}

{dm}

{bi}

{bi}

Channel Coding

• Error correcting code (ECC) encoder: bit seq. → Longer bit seq.‣ protect information bits by adding redundancy into the information bit seq.

• Symbol Mapper: bit seq. → discrete-valued seq.‣ map the coded bits to constellation points, a step in digital modulation

• Pulse Shaper: sequence → baseband waveform‣ bridge the digital world and the analog world, a key step in digital modulation

• Up Converter: baseband waveform → passband waveform‣ move the signal to the “right” frequency band

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ECC Encoder

Symbol Mapper

Pulse Shaper

Filter + Sampler

Symbol Demapper

ECC Decoder

codedbits

discrete sequence

Binary Interface

Channel Coding

Information bits

Up Converter

Down Converter

baseband waveform Noisy

Channel

passband waveform

{bi}

{bi}

{ci}

{ci}

{um}

{um}

xb(t)

yb(t)

x(t)

y(t)

This Course: All about Channel Coding• Build a bridge between the cyber and the physical world‣ Digital modulation and demodulation without noise

• Overcoming noise in narrow-band channels‣ Optimal detection under noise‣ Reliable communication with error correction codes

• Overcoming inter-symbol interference in wide-band ch.‣ Equalization techniques‣ Orthogonal frequency division multiplex (OFDM)

• Overcoming fading in wireless channels‣ Diversity techniques

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