Lecture 01 Introduction to Communication Systems I-Hsiang Wang - - PowerPoint PPT Presentation

Principle of Communications, Fall 2017

Lecture 01 Introduction to Communication Systems

I-Hsiang Wang

ihwang@ntu.edu.tw National Taiwan University 2017/9/13

Outline

• The basic architecture of communication systems
• Source-channel separation
• Overview of the course

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A communication system

• The simplest point-to-point abstraction
• Given by nature/applications: source, channel, destination
• Engineers’ design: encoder, decoder

3

Encoder Channel Decoder Source Destination Noise

Source and channel

• Source
• generates the message to be delivered
• message: text, audio, image, video, etc.. → can be abstracted into signals
• in general, signals can be continuous-time and continuous-valued → waveforms!
• Channel
• abstraction of the physical medium: light, sound, wire, optical fiber, EM radiation, etc.
• distorts the transmitted signal in some way → noisy channel, using stochastic models

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Encoder Channel Decoder Source Destination Noise

Encoder and decoder

• Encoder
• converts the message into physical signals that is ready for transmission
• functions include sampling, quantization, compression, error-correction coding,

modulation, etc.

• 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 Decoder Source Destination Noise

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.
• Source-channel separation attains optimal transmission efficiency (Shannon).
• Bits as universal currency of the digital world → a channel can be extended to a network

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Source Encoder Source Noisy Channel Channel Encoder Destination Source Decoder Channel Decoder Binary Interface Bits Bits

message waveform signal waveform

Source coding: main building blocks

• Sampling: (continuous-time) waveform → (discrete-time) sequence
• (Review: Sampling Theorem, Nyquist Rate)
• Quantization: continuous-valued sequence → discrete-valued sequence
• Compression: discrete-valued sequence → bit sequence, remove redundancy

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input (message) waveform Sampler Quantizer Discrete Encoder Discrete Decoder Table Lookup Filter

• utput

(message) waveform

analog sequence discrete sequence

Binary Interface

Source Coding

ˆ s(t) s(t)

{s[m]} {ˆ s[m]} {dm} { ˆ dm}

{bi} {ˆ bi}

Channel coding: main building blocks

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ECC Encoder Symbol Mapper Pulse Shaper Sampler + Filter Symbol Demapper ECC Decoder

coded bits discrete sequence

Binary Interface

Channel Coding

Information bits Up Converter Down Converter

baseband waveform

Noisy Channel

passband waveform

{bi} {ˆ bi}

{ci} {ˆ ci} {um} {ˆ um} xb(t) yb(t)

x(t) y(t)

Overview of the course: all on channel coding

• Building a bridge between the cyber world 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 channels
• Equalization techniques
• Orthogonal frequency division multiplex (OFDM)
• Overcoming fading in wireless channels
• Diversity techniques

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