This course addresses how to implement engineering functions in a cost-effective way by using computational means instead of analog hardware. Instruction emphasizes communication systems, where traditional applications, such as modulation/demodulation, channelization, channel equalization, synchronization, and frequency synthesis, are now being implemented with new digital signal processing techniques to achieve high performance. The course analyzes these techniques, including multirate filters, I-Q sampling, sigma-delta modulators, and conversion between I-Q and real signals. The course focuses on real-world systems using modern DSP methods and illustrates all concepts with MATLAB demonstrations that are distributed to participants.
This course emphasizes the DSP technology used for implementing modern communication systems.
The text, Multirate Signal Processing for Communication Systems, fredric j. harris (Prentice Hall, 2004), and lecture notes are distributed on the first day of the course. The notes are for participants only and are not for sale.
Coordinator and Lecturer
fredric j. harris, PhD, Cubic Signal Processing Chair Professor of Electrical and Computer Engineering, San Diego State University, California. Professor harris is a recognized expert in the field of Digital Signal Processing (DSP), especially as applied to Modem Design, radio surveillance, satellite communications, radar, sonar, acoustic monitoring equipment, and laboratory instrumentation. He is the author of the text, Multirate Signal Processing for Communication Systems. Since 1970, he has been a consultant to such organizations as the U.S. Navy Ocean Systems Center, Lockheed, ESL, Cubic, Hughes, BAE, Scientific Atlanta, Rockwell, Northrop Grumman, Boeing, and Inritsu. He also has presented courses on Modem Design, Multirate Signal Processing, DSP Based Synchronization, DSP for Communication Systems, OFDM, and Spectrum Analysis, Dr. harris has conducted seminars in DSP for Motorola, Qualcomm, Northrop Grumman, BAE, Lockheed, Raytheon, NRL, and SPAWAR.
Digital Signal Processing Tools and Technology
Sampled data processing; sampled data convolution; Z-transform; classical versus intuitive description; discrete Fourier transform (DFT); engineers’ version of the sampling theorem; rules of thumb, sampling rates versus bandwidth; applications: I-Q sampling, DFT demodulation, narrowband sampling, Hilbert transforms.
Prototype filter design; window techniques–first pass, back-of-envelope filter designs; guidelines for estimating computational workload; band-centered designs and their computational advantages; multirate filters, interpolators, and decimators; applications: FM demodulator, I-Q to real-signal processor, surveillance receivers.
Anti-aliasing filters; analog-to-digital and digital-to-analog conversion; quantization effects; amplitude dither; time-base jitter; applications: oversampling converters, digital frequency synthesis.
Adaptive Algorithms for Communication Systems
Self-learning algorithms and examples; optimal estimation, prediction, equalization, cancellation; algorithm structures: least mean square (LMS) and recursive least square (RLS); lattice forms; median filters–nonlinear noise suppression; adaptive threshold for optimal detection; applications: equalizers, channel modeling, line cancellers, AGC loops.
For more information contact the Short Course Program Office:
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