Optimal stochastic signal design and detector randomization in the Neyman-Pearson framework
Date
2012-03
Authors
Advisor
Instructor
Source Title
37th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2012
Print ISSN
15206149
Electronic ISSN
Publisher
IEEE
Volume
Issue
Pages
3025 - 3028
Language
English
Type
Conference Paper
Journal Title
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Volume Title
Abstract
Power constrained on-off keying communications systems are investigated in the presence of stochastic signaling and detector randomization. The joint optimal design of decision rules, stochastic signals, and detector randomization factors is performed. It is shown that the solution to the most generic optimization problem that employs both stochastic signaling and detector randomization can be obtained as the randomization among no more than three Neyman-Pearson (NP) decision rules corresponding to three deterministic signal vectors. Numerical examples are also presented. © 2012 IEEE.
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Keywords
Detection, Detector randomization, Neyman-Pearson, Stochastic signaling, Communications systems, Decision rules, Deterministic signals, Generic optimization, Numerical example, Optimal design, Stochastic signals, Detectors, Error detection, Optimization, Signal processing, Stochastic systems, Random processes