School of Engineering and Technology, (SET)
 
AT77.13 : Digital Communications  3(3-0)
 
Course objectives:

To provide students with thorough understanding of the fundamentals in digital communications and information theory.
 
Learning Outcomes:

Source coding, signal analysis, communications through additive white Gaussian noise (AWGN) channels, optimal detection, signal constellations, block and convolutional codes, information theory, Shannons channel capacity.
 
Pre-requisite(s):

Consent of instructor.
 
Course Outline:

I Reviews of probability, random processes, Fourier analysis, and linear algebra.

II Elements of point-to-point digital communication systems.

III Source coding.

1. Data compression for discrete memoryless source (DMS)
2. Entropy as a fundamental limit for data compression
3. Huffman and Lempel-Ziv (LZ) algorithms
4. Asymptotic equipartition property (AEP)
5. Scalar and vector quantization for continuous memoryless source (CMS)

IV Communication signal representations.

1. L 2 signal spaces and their orthonormal bases
2. Sampling and aliasing theorems
3. Modeling noise as random processes

V Communications through baseband additive white Gaussian noise (AWGN) channels

1. Pulse amplitude modulation (PAM)
2. Signal detection and hypothesis testing
3. Optimal receivers for AGWN channels
4. Nyquist criterion for no intersymbol interference (ISI)

VI Communications through passband AGWN channels

1. Quadrature amplitude modulation (QAM)
2. Signal constellations and their performances

VII Introduction to error control coding

1. Binary linear block codes
2. Binary linear convolutional codes
3. Nonbinary codes

VIII Fundamental limits on communications

1. Mutual information and Shannon 's channel capacity
2. Data processing and Fano's inequalities
3. Discrete memoryless channels (DMCs) and their capacities
4. Differential entropy
5. Capacities of AWGN channels

 
 
 
Learning Resources:

Textbook:

Lecture notes and handouts.
 
Reference Books:

T.M. Cover and J.A. Thomas Elements of Information Theory, Wiley, 1991.
R.G. Gallager Information Theory and Reliable Communication, Wiley, 1968.
MIT Open Courseware, 6.450 Digital Communications, web.mit.edu/6.450/www
J.G. Proakis Digital Communications, McGraw-Hill, 2000.
H.L. Van Trees Detection, Estimation, and Modulation Theory: Part I, Wiley, 2001.
J.M. Wozencraft and I.M. Jacobs Principles of Communication Engineering, Wiley, 1965.

 
Journals and Magazines:

IEEE Communication Magazine
IEEE Network Magazine
IEEE Journal on Selected Areas in Communications
IEEE Transaction on Communications
International Journal of Communication Systems
IEE Proceedings, Communications
IEE Electronics Letters
IEEE Transactions on Information Theory
IEEE Transactions on Broadcasting
IEEE Transactions on Vehicular Technology (VT)
Proceedings IEEE

 
 
Teaching and Learning Methods:

N/A
 
Evaluation Scheme:

The final grade will be computed from the following components:
assignments (25%),
mid-semester exam (35%), and
final exam (40%).
Closed-book examination is used in both mid-semester and final exams.
 
Instructor(s):
SECTION NAME
A Dr. Attaphongse Taparugssanagorn