1. Digital Communication
Mr. Sajid Gul Khawaja

2. Overview Course Information Course Schedule Scoring\Grading
Prerequisites
Books
Scoring\Grading
Expectations
Digital Systems
Introduction to digital communication systems

3. Course Info Prerequisites Course materials
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:
“Principles of Digital Communications”, Gallager
“Digital Communications: Fundamentals and Applications” by Bernard Sklar,Prentice Hall, 2001, ISBN:
“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:

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

5. Score/Grading Tentative marks division 2 Sessional Exams 25~30%
Reading Assignments 5~10%
Quizzes %
Practical ~25%
Lab
Project
Final Examination ~45%

6. 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

7. Course Outline Introduction to DC Source Coding
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

8. 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

9. Signaling through bandlimited channels
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

10. Signaling through fading channels
Rayleigh fading, optimum receiver, performance
Interleaving
Synchronization or Link Estimation
Symbol synchronization
Frame synchronization
Carrier synchronization

11. What is Digital Communication?

12. Digital Communications
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.

13. Basis of Digital Communication
Information theory, developed in 1948 by Claude Shannon
Reading Assignment
A Mathematical Theory of Communication By C. E. SHANNON

14. 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).

15. 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.

16. 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.

17. Why Digital Communication?

18. Device Challenges Analog and RF Components A/D Converters
Size, Power, Cost
Multiple Antennas
Multiradio Coexistance
Cellular
Apps
Processor BT
Media
GPS
WLAN
Wimax
DVB-H
FM/XM
A/D
DSP
These challenges may
someday be completely
solved by a
software-defined radio

19. Design Challenges Hardware Design System Design Network 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

20. 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

22. 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

24. Where is Digital Communication Embedded in a Digital System?

25. Data Network Protocols and the OSI Model

26. Examples of Digital System from everyday life

27. Communication Systems
Provide for electronic exchange of multimedia data
Voice, data, video, music, , 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

28. An Overview of the Digital System

29. 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

30. 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

31. 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.

32. Source Encoder and Decoder
In digital communication we convert the signal from source into digital signal. The point to remember is we should like to use as few binary digits as possible to represent the signal. In such a way this efficient representation of the source output results in little or no redundancy. This sequence of binary digits is called information sequence.
Source Encoding or Data Compression: the process of efficiently converting the output of wither analog or digital source into 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 encoding algorithm. And which results in the approximate replica of the input at the transmitter end

33. Channel Encoder and Decoder
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 used at the receiver to overcome the effects of noise and interference encountered in the transmission on the signal through the channel.
e.g. take k bits of the information sequence and map that k bits to unique n bit sequence called code word. The amount of redundancy introduced is measured by the ratio n/k and the reciprocal of this ratio (k/n) is known as 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

34. Digital Modulator and Demodulator
The binary sequence is passed to digital modulator which in turns convert the sequence into electric signals so that we can transmit them on channel. The digital modulator maps the binary sequences into signal wave forms , for example if we represent 1 by sin x and 0 by cos x then we will transmit sin x for 1 and cos x for 0.
Digital Demodulator:
The digital demodulator processes the channel corrupted transmitted waveform and reduces the waveform to the sequence of numbers that represents estimates of the transmitted data symbols.

35. 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).

36. Block Diagram of a Digital System

38. Step Wise

39. 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)

40. Layering of Source Coding

41. 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

42. Layering of Channel Coding