Optimal stochastic signal design and detector randomization in the Neyman-Pearson framework
Author
Dülek, Berkan
Gezici, Sinan
Date
2012-03Source Title
37th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2012
Print ISSN
15206149
Publisher
IEEE
Pages
3025 - 3028
Language
English
Type
Conference PaperItem Usage Stats
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Show full item recordAbstract
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.
Keywords
DetectionDetector 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
Permalink
http://hdl.handle.net/11693/28154Published Version (Please cite this version)
http://dx.doi.org/10.1109/ICASSP.2012.6288552Collections
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