Digital Communication

Mr. Sajid Gul Khawaja

Overview

� Course Information

� Course Schedule

� Prerequisites

� Books

� Scoring\Grading

� Expectations

� Digital Systems

� Introduction to digital communication systems

Course Info

� Prerequisites

� Probability and random variables

� Digital Signal Processing

� Course materials

� Course text books:

� “Communication Systems Engineering”, by John G. Proakis and Masoud Salehi, Prentice Hall, 2002, 2nd edition, ISBN: 0-13-095007-6

� “Principles of Digital Communications”, Gallager

� “Digital Communications: Fundamentals and Applications” by Bernard Sklar,Prentice Hall, 2001, ISBN: 0-13-084788-7

� “Communication Systems” by Simon Haykin 4th Edition

� Additional recommended books:

� “Digital Communications”, by Ian A. Glover and Peter M. Grant, Pearson, Prentice Hall, 2004, 2nd edition, ISBN: 0-13-089399-4

Course Schedule

� 14-16 lectures

� 2-4 Quizzes

� 2-4 home assignments

� Written assignments may not be graded

� 2 Sessional Exams

� Practical Work

� Final Exam

Score/Grading

� Tentative marks division

� 2 Sessional Exams 25~30%

� Reading Assignments 5~10%

� Quizzes 5%

� Practical 20~25%

� Lab

� Project

� Final Examination 40~45%

Expectations/Objectives

� Mine� Deliver the concepts of digital communications

� Understand the following about the different blocks of digital communication� What

� Why

� When

� How

� Eventually forming a prototype system

� Yours’� Getting through this course (majority)

� Getting an A

� Learn something new

Course Outline

� Introduction to DC� Some Probability Theory

� Probability space, random variables, density functions, independence

� Expectation, conditional expectation, Baye’s rule

� Stochastic processes, autocorrelation function, stationary, spectral density

� Source Coding� Measuring information, entropy, the source coding

theorem

� Huffman coding, Run-length coding, Lempel-Ziv etc.

� Analog-to-digital conversion� Sampling (ideal, natural, sample-and-hold)

� Quantization, PCM

� Communication channels� Band-limited channels

� The AWGN channel, fading channels

� Receiver design� General binary and M-ary signaling

� Maximum-likelihood receivers

� Performance in an AWGN channel� The Chernoff and union/Chernoff bounds

� Simulation techniques

� Signal spaces

� Modulation: PAM, QAM, PSK, DPSK, coherent FSK, incoherent FSK

� Channel coding

� Block codes, hard and soft-decision decoding, performance

� Convolutional codes, the Viterbi algorithm, performance bounds

� Trellis-coded modulation (TCM)

� Signaling through bandlimited channels

� ISI, Nyquist pulses, sequence estimation, partial response signaling

� Equalization

� Signaling through fading channels

� Rayleigh fading, optimum receiver, performance

� Interleaving

� Synchronization or Link Estimation

� Symbol synchronization

� Frame synchronization

� Carrier synchronization

What is Digital

Communication?

Digital Communications

� Digital Communication:

� Enormous and normally rapidly growing industry

� Objective:

� Study those aspects of communication systems

unique to those systems. Little focus on hardware

or software

� Hardware and software are similar to other

systems.

Basis of Digital Communication

� Information theory, developed in 1948 by

Claude Shannon

� Reading Assignment

� A Mathematical Theory of Communication By C.

E. SHANNON

� Complex relationship between modeling, theory, exercises, and engineering/design.

� Use very simple models to understand ideas. This generates powerful general theorems plus insights into more complex models and thus reality.

� Exercises aimed at understanding the principles getting the right answer is not the point since the model is oversimplified.

� Engineering deals with approximations and judgment calls based on multiple simple models (insights).

� Since the exercises apply only to simple

models, they don’t apply directly to real

systems.

� You have to understand the exercise at a gut

level to see how to use the idea.

� This is why you should discuss the exercises

with other students –getting the correct

answer by pattern matching and manipulation

is not the point.

� Everyday communication systems (the

telephone system, the Internet) have

incredible complexity.

� Must be designed and understood based on

simple architectural principles.

� Standardized interfaces and layering are key.

Why Digital Communication?

Device Challenges

� Analog and RF Components

� A/D Converters

� Size, Power, Cost

� Multiple Antennas

� Multiradio Coexistance

Cellular

AppsProcessor

BT

MediaProcessor

GPS

WLAN

Wimax

DVB-H

FM/XM

A/D

A/D

DSPA/D

A/D

These challenges may

someday be completely

solved by a

software-defined radio

Design Challenges

� Hardware Design� Precise components� Small, lightweight, low power� Cheap� High frequency operation

� System Design� Converting and transferring information� High data rates � Robust to noise and interference� Supports many users

� Network Design� Connectivity and high speed� Energy and delay constraints

Advantages of Digital Systems

� Error correction/detection

� Better encryption algorithms: Can not be

done in analog communication

� More reliable data processing

� Easily reproducible designs

� Reduced cost

� Easier data multiplexing

� Facilitate data compression

Disadvantages:

� Heavy signal processing

� Synchronization is crucial

� Larger transmission bandwidth

� Non-graceful degradation

23

Goals in Communication System Design

To maximize transmission rate, R

To maximize system utilization, U

To minimize bit error rate, Pe

To minimize required systems bandwidth, W

To minimize system complexity, Cx

To minimize required power, Eb/No

R U

Pe w cx Eb/No

Where is Digital Communication

Embedded in a Digital System?

Data Network Protocols and the OSI Model

Examples of Digital System

from everyday life

Communication Systems

� Provide for electronic exchange of multimedia data

� Voice, data, video, music, email, web pages, etc.

� Communication Systems Today

� Radio and TV broadcasting

� Public Switched Telephone Network (voice,fax,modem)

� Cellular Phones

� Computer networks (LANs, WANs, and the Internet)

� Satellite systems (pagers, voice/data, movie broadcasts)

� Bluetooth

An Overview of the Digital

System

Main Points

� Communication systems send information electronically over communication channels

� Many different types of systems which convey many different types of information

� Design challenges include hardware, system, and network issues

� Communication systems recreate transmitted information at receiver with high fidelity

� Focus of this class is design and performance of analog and digital communication systems

Information Source and Sinks

� Information Source and Input Transducer:

� The source of information can be analog or digital, � Analog: audio or video signal,

� Digital: like teletype signal.

� In digital communication the signal produced by this source is converted into digital signal consists of 1′s and 0′s.

� Output Transducer:

� The signal in desired format analog or digital at the output

Channel

� Channel:

� The communication channel is the physical

medium that is used for transmitting signals from

transmitter to receiver

� Wireless channels: Wireless Systems

� Wired Channels: Telephony

� Channel discrimination on the basis of their

property and characteristics, like AWGN channel

etc.

Source Encoder and Decoder

� Source Encoder� In digital communication we convert the signal from source into

digital signal. The point to remember is we should like to use asfew binary digits as possible to represent the signal. In such away this efficient representation of the source output results inlittle or no redundancy. This sequence of binary digits iscalled information sequence.

� Source Encoding or Data Compression: the process ofefficiently converting the output of wither analog or digital sourceinto a sequence of binary digits is known as source encoding.

� Source Decoder� At the end, if an analog signal is desired then source decoder

tries to decode the sequence from the knowledge of the encodingalgorithm. And which results in the approximate replica of theinput at the transmitter end

Channel Encoder and Decoder

� Channel Encoder:� The information sequence is passed through the channel encoder. The

purpose of the channel encoder is to introduce, in controlled manner,some redundancy in the binary information sequence that can be usedat the receiver to overcome the effects of noise and interferenceencountered in the transmission on the signal through the channel.

� e.g. take k bits of the information sequence and map that k bits to uniquen bit sequence called code word. The amount of redundancy introducedis measured by the ratio n/k and the reciprocal of this ratio (k/n) is knownas rate of code or code rate.

� Channel Decoder:� Channel decoder attempts to reconstruct the original information

sequence from the knowledge of the code used by the channel encoder and the redundancy contained in the received data

Digital Modulator and Demodulator

� Digital Modulator:� The binary sequence is passed to digital modulator

which in turns convert the sequence into electricsignals so that we can transmit them on channel. Thedigital modulator maps the binary sequences intosignal wave forms , for example if we represent 1 bysin x and 0 by cos x then we will transmit sin x for 1and cos x for 0.

� Digital Demodulator:� The digital demodulator processes the channel

corrupted transmitted waveform and reduces thewaveform to the sequence of numbers that representsestimates of the transmitted data symbols.

The Main Points

� The point worth noting are :� The source coding algorithm plays an important role

in higher code rate

� The channel encoder introduce redundancy in data

� The modulation scheme plays important role in deciding the data rate and immunity of signal towards the errors introduced by the channel

� Channel can introduce many types of errors due to thermal noise etc.

� The demodulator and decoder should provide high Bit Error Rate (BER).

Block Diagram of a Digital

System

Step Wise

Layering of Source Coding

� Source coding includes

� Sampling

� Quantization

� Symbols to bits

� Compression

� Decoding includes

� Decompression

� Bits to symbols

� Symbols to sequence of numbers

� Sequence to waveform (Reconstruction)

Layering of Source Coding

Layering of Channel Coding

� Channel Coding is divided into

� Discrete encoder\Decoder

� Used to correct channel Errors

� Modulation\Demodulation

� Used to map bits to waveform for transmission

Layering of Channel Coding