Digital Communication Proakis 5th Edition

[Tambra Podrasky]

ProfessorProakis's professional experience and interests include adaptive filtering, adaptive communication systems and adaptive equalization techniques, communication through fading multipath channels, radar detection, signal parameter estimation, optimization techniques, and statistical analysis. Proakis has had an impact on a generation of engineering students, as the author of the widely used textbook "Digital Communications" (McGraw-Hill, 1983). An introductory-level text for graduate students, its fourth edition (published in 2000) has been updated to cover new topics including serial and parallel concatenated codes, punctured convolutional codes, turbo TCM and turbo equalization, and spatial multiplexing. Proakis has taught undergraduate and graduate courses in communications, circuit analysis, control systems, probability, stochastic processes, discrete systems, and digital signal processing.

John Proakis joined the UCSD faculty in 1998, while retaining the title of Professor Emeritus at Northeastern University. He received his Ph.D. in Engineering from Harvard in 1967, and subsequently worked at GTE Laboratories and the MIT Lincoln Laboratory. From 1969-98, Proakis taught at Northeastern, taking on a succession of administrative roles that culminated in his Chairmanship fo the Department of Electrical and Computer Engineering from 1984-1997. Apart from a landmark textbook on digital communications (see above), Proakis co-authored "Digital Signal Processing" (Macmillan, 2nd Edition 1992); "Advanced Digital Signal Processing" (Macmillan, 1992); "Digital Processing of Speech Signals" (Macmillan, 1993); and "Communication Systems Engineering" (Prentice-Hall, 1994).

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Digital Communications is a classic book in the area that is designed to be used as a senior or graduate level text. The text is flexible and can easily be used in a one semester course or there is enough depth to cover two semesters. Its comprehensive nature makes it a great book for students to keep for reference in their professional careers.This all-inclusive guide delivers an outstanding introduction to the analysis and design of digital communication systems. Includes expert coverage of new topics: Turbocodes, Turboequalization, Antenna Arrays, Digital Cellular Systems, and Iterative Detection. Convenient, sequential organization begins with a look at the history and classification of channel models and builds from there.

Introduction to digital communication systems and spread spectrum communications. Topics include analog message digitization, signal space representation of digital signals, binary and M-ary signaling methods, detection of binary and M-ary signals, comparison of digital communication systems in terms of signal energy and signal bandwidth requirements. The principal types of spread spectrum systems are analyzed and compared. Application of spread spectrum to multiple access systems and to secure communication systems is discussed.

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The largest portion of the course is devoted to studying how to translate information into a digital signal to be transmitted, and how to retrieve the information from the received signal. We study in-depth various digital modulation schemes through a concept of signal space. We build analytical and simulation models for digital modulation systems in presence of noise, and define the performances of digital communication systems through a probability of reliable transmission of information. We also build optimal receiver models for digital base-band and band-pass modulation schemes, and introduce iterative decoding on graphs, iterative decoding on intersymbol interference channels and constrained coding.

Prerequisites: EEE 185.

Review of Fourier analysis and theory of probability, random processes, optimum filtering, performance of analog and digital communication systems in the presence of noise, system optimization.

This is the first graduate course covering the principles of digital transmission of information. ECE 535 introduces a notion of information. We rigorously define the amount of information, introduce information measures and explain how to extract a pure information from a source and how to protect information during transmission. The largest portion of the course is devoted to studying how to translate information into a digital signal to be transmitted, and how to retrieve the information back from the received signal. We study in depth various digital modulation schemes through a concept of signal space. We build analytical and simulation models for digital modulation systems in presence of noise, and define the performances of digital communication systems through a probability of reliable transmission of information. We also build optimal receiver models for digital base-band and band-pass modulation schemes.

The subject of digital communications involves the transmission ofinformation in digital form from a source that generates theinformation to one or more destinations. This course extends theknowledge gained from ECS332 (Principles of Communications) and ECS315(Probability and Random Processes). Basic principles that underlie theanalysis and design of digital communication systems are covered. Thissemester, the main focus includes performance analysis (symbol errorprobability), optimal receivers, and limits (information theoretic quantities).These topics are challenging but the presented material are carefullyselected to keep the difficulty level appropriate for undergraduatestudents.

Knowledge regarding digital communication theory. Knowledge regarding wired and wireless communication systems. Knowledge regarding the most utilized communication solutions for the Internet of Things.

Conoscenza e capacit di comprensione - Knowledge and understaning": Exploiting the knowhow achieved in the course, students will be able to apply the communication theory to the design of communication systems.

Conoscenze e capacit di comprensione applicate - Applying Knowledge and understaning": Exploiting the knowhow achieved in the course, students will be able to identify the major system requirements characterizing the application scenario of interest and, thus, identify and design the most appropriate technical solutions.

At the end of the course, students will be able to identify the best solutions (modulation scheme, multiplexing scheme, transmission media, communication standard) for the design and budgeting of communication systems.

Should teaching be carried out in mixed mode or remotely, it may be necessary to introduce changes with respect to previous statements, in line with the programme planned and outlined in the syllabus.

A good book that covers theory and practice is Digital Communications, A Discrete-Time Approach, by Michael Rice. (Pearson, 2009). Among other topics, it includes details of carrier recovery and clock recovery for QAM. Note the presentation is at a block diagram level, not device level. Also, it does not cover OFDM in significant detail. You will want to get the Errata, since there are quite a few mistakes in it.

I am working in wireless creating remote radio head designs on FPGAs. I was given the task of creating the processing designs from scratch in Xilinx FPGAs and found the tricks and techniques section from Richard Lyons' Understanding Digital Signal Processing book to be spot on for the implementations needed. I already knew how to code FPGA designs but this helped me create an efficient design for which all of the pieces of the puzzle slotted together. I now recommend it to new employees.

Another good book on all aspects of digital communications is Digital Communications with Emphasis on Data Modems: Theory, Analysis, Design, Simulation, Testing, and Applications by Richard Middlestead (2017).

Upon successful completion of this course, students will be able to:

(1) List the sampling theorem, pulse amplitude modulation, pulse code modulation, and quantization,

(2) Explain baseband transmission of digital signals and matched filter detection in baseband digital communication systems,

(3) Utilize the probability of error concept to investigate baseband transmission systems performance,

(4) Analyze the geometric representation of multidimensional signal waveforms, optimal receiver structures, decision regions, and union bound on error probability for bandpass transmission systems,

(5) Evaluate the information theory principles including entropy, source-coding theorem, and lossless data compression,

(6) Collaborate with peers in conducting experiments on digital communications.

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