Digital Communications Systems II
Catalog Data: 

Graduate Course Information


ECE 537A - Digital Communications Systems II

Credits: 3.00

Course Website:

UA Catalog Description:

Course Assessment:

Homework:  assigned but not graded

Project:  1-2 projects

Exams:  2 Midterm Exams, 1 Final Exam

Grading Policy:

Typically: 30% Midterms,

                  20% Final Exam,

                    0% Homework,

                    0% Laboratory,

                    50% Project. 

Course Summary:

This is an advanced graduate course covering the principles of digital transmission of information. We rigorously define the amount of information and introduce information measures. 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, introduce iterative decoding on graphs, iterative decoding on intersymbol interference channels, constrained coding.

Graduate Standing

J. G. Proakis, Digital Communications, 5th Edition, McGraw-Hill, 2012.

Course Topics: 

1.     Representation of band-pass signals and systems

2.     Signal space representation of band-pass signals and noise

3.     Memoryless digital modulation methods (ASK, PSK, FSK, QPSK, spectra of digitally modulated signals)

4.     Optimum receivers for additive white Gaussian noise (AWGN) channel, maximum a posteriori (MAP) and maximum likelihood (ML) detection, matched filter demodulation

5.     Sequence detectors

6.     Receiver performance

7.     Error control coding fundamentals (finite fields, generator and parity check matrices)

8.     Fundamentals of block and convolutional codes, Hamming codes, syndrome decoding,

9.     Basics of low-density parity check (LDPC) codes and iterative decoding.

10.  Partial response channels (controlled ISI. partial response equalization, data detection for controlled ISI channels, optimum maximum-likelihood receiver)

11.  Constrained (modulation) coding (symbolic dynamics basics, modulation codes for spectrum shaping, shnnon noiseless capacity, sofic shifts of finite type, sliding window decoders, state-splitting algorithm)

12.  Iterative receivers for ISI channels (iterative decoding principles, combined equalization and coding, BCJR algorithm)

Class/Laboratory Schedule: 

Lecture:  150 minutes/week

Prepared by: 
Bane Vasic`
Prepared Date: 
April 2013

University of Arizona College of Engineering