Statistical Communication Theory

ECE 630

Spring 2008
Instructor
Prof. B.-P. Paris
S & T II Room 227
Tel.: 703-993-1559
e-mail:pparis@gmu.edu
WWW: http://www.spec.gmu.edu/~pparis
Time and Place
Tuesday 7:20pm – 10:00pm, S & T II, Room 260
Office Hours
Tuesday 5:30pm – 6:30pm and Thursday 10:30 – 11:30am.
Required Textbook
J.M. Wozencraft and I.M. Jacobs, Priciples of Communication Engineering, New York: Wiley & Sons, 1965. (reissued by Waveland Press, Prospect Heights, IL, 1990.)
Recommended Further Reading
  1. H.L. van Trees, Detection, Estimation, and Modulation Theory, vol. I, New York: Wiley & Sons, 1968.
  2. J.G. Proakis, Digital Communications, 5th ed., New York: McGraw-Hill, 2007.
Homework
will be assigned every week except when an exam is scheduled the following week. A set of solutions will be made available. You are encouraged to work on the assignments in small groups.
Two Exams
will be given: one midterm exam and a comprehensive final exam. All exams are conducted under the rules and regulations of the Honor Code (see University Catalog ).
On-line Class Material
Class material will be distributed electronically via the World-Wide Web. Use a browser to find the ECE 630 homepage at URL http://www.spec.gmu.edu/~pparis/classes/ece630.html.
Final Grades
are determined as a weighted average of homeworks and exams in the following way:
Homework 20%

Midterm 40%

Final 40%

Tentative Course Schedule

Week 1:
Review of Probability Theory and Stochastic Processes.
Week 2:
Review of Probability Theory and Stochstic Processes, continued.
Week 3:
Review of relevant Linear Vector Space Methods.
Week 4:
Optimum receivers in additive white Gaussian noise.
Week 5:
Optimum receivers in additive white Gaussian noise, continued.
Week 6:
Efficient Signaling for Message Sequences.
Week 7:
Efficient Signaling for Message Sequences, continued.
Week 8:
Midterm Exam.

During the second half of the course we will consider important channel models that are more complicated than the AWGN channel. In detail, the schedule is as follows:

Week 9:
The coloured Gaussian noise channel.
Week 10:
Dispersive channels.
Week 11:
Nonlinear channels: random amplitude and random phase.
Week 12:
Nonlinear channels: fading channels.
Week 13-14:
Selected Topics
May 13:
7:30-10:15, Final Exam