This is supplemental course information, designed to give you a
fuller picture of the course and an expanded look at the topics
covered. This is an unofficial document. The USC Course Catalog is the
binding description of all university courses. Information such as
books, materials covered, and the order of topics is subject to change.
Please consult instructor for this semseter to get more upto date
course information.
J. M. Wozencraft and I. M. Jacobs, Principles of Communication System
Engineering, Waveland Press (ISBN 0-88133-554-1). This is a classic textbook
that was originally published in 1965 by Wiley.
Harry L. Van Trees, Detection, Estimation, and Modulation Theory, Wiley-Interscience
(ISBN 0471095176). This is a paperback edition of the first volume of
a highly regarded set of volumes.
John Proakis, Digital Communications, 4th ed., McGraw-Hill (ISBN 0072321113).
Excellent modern text.
To give the student a basic understanding of how digital information is
communicated over simple channels, to provide analytical tools for advanced
study in the field of communication system design, and to understand the
limitations of current theories of digital communication.
This course is a first course in statistical communication theory. Emphasizing
the mathematical design of optimal receivers and modulation for communication
over additive Gaussian noise channels, and the evaluation of receiver
performance in these situations. Basic Relationships between information
rate, bandwidth, signal space dimensionality, signal-to-noise ratio, and
channel capacity are carefully developed and exploited as part of the
design process.
1. Baysean decision theory: problem structures, minimizing risk, decision
regions, optimal decision procedures, problems with limited information.
2. The probability-of-error risk function, application of decision theory
to vector models of communication signals, and the performance of optimal
decision rules for communication in additive Gaussian noise.
3. The reduction of waveform observations to vector observations; sampling,
the Karhuenen-Loeve expansion, sufficient statistics. Optimal reception
of a digital waveform observed in a finite time interval, correlation
detection, matched filtering.
(Midterm primarily covers topics 1-3, with some elements of topic 4.)
4. Signal design concepts for the baseband additive-white-Gaussian-noise
(AWGN) channel. Orthogonal and simplex signal sets; designs known to minimize
error probability for the AWGN channel. Constant envelope designs using
Hadamard matrices.
5. Communication systems organization for the transmission and reception
of a symbol stream. Baseband and carrier communications, spectral analysis
of transmissions, definitions of bandwidth, the mathematical basis for
the relation between transmission bandwidth and the rate of growth of
signal space dimensionality.
6. Random coding, the union bound, sphere packing, Shannon’s capacity
theorem for the AWGN channel, and a converse to this theorem.
7. Communication over wideband radio-frequency (RF) channels, mathematical
modeling of receiver front ends, the equivalent baseband representation
of RF signals, synchronization requirements. The effects of uncertain
phase on optimal receiver and modulation design for the AWGN channel.
8. Advanced topics as time permits.
(Final covers the whole course, but with an emphasis on later topics.)
Prepared by: Robert Scholtz - 11/2003
