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What you can learn.

Understand DSP synchronization through sample designs and implementations

About This Course

Learn the essential concepts of full DSP synchronization for timing recovery, phase recovery, and carrier recovery. Understand the processes through sample designs and implementations. Real-time MATLAB simulations illustrate essential concepts for a number of common modulation schemes, such as QPSK and QAM, as well as CPM, Offset QPSK, VSB, OFDM, and CDMA.

It is highly recommended that participants have attended the two related UCLA Extension short courses in this area, Communication Systems Using Digital Signal Processing and Advanced Digital Communications: The Search for Efficient Signaling Methods, or have a working familiarity with Z-transforms, FIR filters, Sampling Theorem, and spectrum analysis techniques.

Lecture notes are distributed on the first day of the course. These notes are for participants only and are not otherwise available for sale or unauthorized distribution.

fredric j. harris, PhD, Cubic Signal Processing Chair Professor of Electrical and Computer Engineering, San Diego State University, California. Dr. harris is a recognized expert in the field of Digital Signal Processing (DSP), especially as applied to underwater acoustics, radio surveillance, satellite communications, radar, real-time acoustics, vibration 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 fast algorithms, adaptive algorithms, error-correcting codes, and control theory. Dr. harris has conducted seminars in DSP for Motorola, Northrop Grumman, BAE, Lockheed, Hewlett Packard, General Electric, Rockwell, Spectral Dynamics, and the U.S. Navy Research Laboratory.

Receiver Structures

Parameters to be estimated
Eye diagrams, constellations, and other observables
Visualization aides

Maximum Likelihood Estimation (MLE) of Phase

Phase-locked loops and digital equivalents
Matched filters
Decision and non-decision directed
Squaring loops

Maximum Likelihood Estimation of Timing

MLE Model and approximations
Phase detectors
Early-late gate
Decision and non-decision directed

Maximum Likelihood Frequency Estimation

Frequency matched filter
Band edge filtering

Polyphase Filters for Timing Recovery and Band Edge Filtering

Pilots and Preambles

Fast acquisition training signals
Signal mining options

Practical Consideration

Acquisition and tracking aides
Phase detectors
Frequency detectors
Direct digital synthesizers
CORDIC algorithms
SNR-Estimators

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