Digital Signal Processing (DSP) Applications of Communication Systems Course

Program Overview

This online, self-paced course provides an in-depth exploration of DSP techniques for communication applications. Students gain a comprehensive understanding of topics such as sampling, quantization, linear systems, and z-transforms. The course also covers practical aspects like ADCs, DACs, and DSP chips, as well as advanced techniques like adaptive filtering, DFT, and FFT. Students will develop proficiency in using Matlab for analysis and problem-solving.

Program Outline

Outline:

• The course discusses DSP techniques for communication applications such as cellular telephones, satellites, and audio/data/CD/video systems.
• Topics covered include under/over/I&Q channel sampling, Nyquist criteria, aliasing, quantization noise, SNR, SFDN, dynamic range, linear systems, and z-transforms.
• Students gain an understanding of practical aspects such as ADCs, DACs, DSP chips, FPGAs, and ASICs, as well as multirate processing, decimation, interpolation, DFT, IDFT, FFT, and IFFTs.
• The course explores theoretical and practical aspects of adaptive, FIR, and IIR filtering.
• Students gain an understanding of DSP techniques for modulators, demodulators, equalization, and other communication components, as well as DDS and NCOs, BER, correlation, and eye patterns, etc.
• Instruction discusses polyphase filtering and techniques for channelization.
• The instructor demonstrates the use of Matlab and other software tools for analysis, simulation, and problem solving.

Teaching:

• The course is taught by David Taggart.
• The course is offered online in a self-paced format.
• The course fee includes access to optional Matlab software for analysis, simulation, and problem solving.