Digital Communication
525.740
Course Description
The course presents the basic theory of modulation and detection systems for
digital communications. The basic tools of the discrete Fourier transform, the
Z-transform, and complex signal representations are first briefly presented. The
optimum receiver and the resulting probability of error are then discussed for
memoryless modulation schemes with the additive white Gaussian noise channel.
The bandwidth requirement for digital modulation schemes is considered, as well
as noncoherent detection and intersymbol interference. Additional topics may
include equalization, synchronization, the Viterbi algorithm, and hard vs. soft
decision decoding.
Syllabus
- Review of Probability and Stochastic Processes
- Bandpass Signals and Systems; Signal Space Representations
- Power Spectra of Digitally Modulated Signals
- Optimum Receiver for Signals Corrupted by AWGN
- Block and Bit Error Rate of Various Digital Modulation Schemes
- Noncoherent Detection; Regenerative Repeaters and Link Budget Analysis
- Mid-term Exam
- Channel Capacity and Coding
- Linear Block Codes
- Convolutional Codes and the Viterbi Algorithm
- Hard-Decision vs. Soft-Decision Decoding
- Signal Design for Band-Limited Channels
- Communication through Band-Limited Linear Filter Channels
- Final Exam
Prerequisites
525.414
Probability and Stochastic Processes for Engineers, 525.416
Communication Systems Engineering, and the basics of linear vector space
theory.
Instructor
Nader Moayeri is the Manager of the Wireless Communications Technologies
Group at the National Institute of Standards and Technology in Gaithersburg, MD. His areas
of research are wireless communications, data compression, and image/video processing. He
received a Ph.D. in electrical engineering-systems from the University of Michigan, Ann
Arbor, MI, in 1986.
Textbook
Digital
Communications by John G. Proakis
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Engineering Courses | Electrical
Engineering | Part-Time
Engineering
Fall 1998