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 material • Course text book: • “Communication Systems Engineering”, by John G. Proakis and MasoudSalehi, 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 • Communication Systems. 3rd Edition, Simon Haykins
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 • 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 • Bandlimited channels • The AWGN channel, fading channels
Some Probability Theory • Probability space, random variables, density functions, independence • Expectation, conditional expectation, Baye’s rule • Stochastic processes, autocorrelation function, stationarity, spectral density • 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 responsesignaling • Equalization
Signaling through fading channels • Rayleigh fading, optimum receiver, performance • Interleaving • Synchronization or Link Estimation • Symbol synchronization • Frame synchronization • Carrier synchronization
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.
Device Challenges • Analog and RF Components • A/D Converters • Size, Power, Cost • Multiple Antennas • Multiradio Coexistance BT FM/XM A/D A/D A/D GPS Cellular DVB-H Apps Processor WLAN These challenges may someday be completely solved by a software-defined radio A/D Media Processor Wimax DSP
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
Pe w cx Eb/No R U 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
Communication Systems • Provide for electronic exchange of multimedia data • Voice, data, video, music, email, web pages, etc. • Communication Systems Today • Radio and TV broadcasting (covered later in the course) • Public Switched Telephone Network (voice,fax,modem) • Cellular Phones • Computer networks (LANs, WANs, and the Internet) • Satellite systems (pagers, voice/data, movie broadcasts) • Bluetooth
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 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
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 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
Digital Modulator and Demodulator • Digital Modulator: • 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.
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).
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 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