CATALOG DESCRIPTION: Digital modulation, complex baseband signaling, multicarrier modulation, sequence estimation, the Viterbi algorithm, probability of error analysis, equalization.

REQUIRED TEXTS:  E. A. Lee, D. G. Messerschmitt, and J. Barry, Digital Communication, Kluwer Academic Publishers, 3rd Ed., 2004.

REFERENCE TEXT: J. G. Proakis, Digital Communications, 5th Ed., McGraw-Hill, 2006.

COURSE DIRECTOR: Prof. Michael Honig

COURSE GOALS: To provide first-year graduate students with an understanding of design and performance analysis techniques for digital communication systems with power and bandwidth constraints.

PREREQUISITES BY COURSES: 422, 378, 359

PREREQUISITES BY TOPIC:
   ITEM 1: Probability and random processes
   ITEM 2: Frequency-domain (spectral) analysis
   ITEM 3: Familiarity with z-transforms.

DETAILED COURSE TOPICS:
   1. Review of digital modulation
   2. Baseband signaling and pulse shaping
   3. Passband Pulse- and Quadrature-Amplitude Modulation
   4. Multi-carrier modulation
   5. Maximum-likelihood detection 6. Whitened matched filter
   7. Viterbi algorithm
   8. Probability of error
   9. Linear equalization
  10. Decision-feedback equalization

COMPUTER PROJECTS: Optional.

LABORATORY PROJECTS: None.

GRADES: A weighted combination of problem sets, midterm, and final.

COURSE OBJECTIVES: When a student completes this course, s/he should be able to:
   1. Construct time- and frequency-domain models for digital communications systems with linear channels and additive noise. 
   2. Design the optimal receiver when the noise is Gaussian. 
   3. Design linear and decision-feedback equalizers. 
   4. Evaluate and compare the performance of the preceding techniques.