Uniformly most powerful distributed detection and its application in cooperative spectrum sensing

In this paper, a special class of distributed composite binary hypothesis testing problem with monotonic likelihood ratio is investigated. The sensor observations are assumed to be conditionally independent given a fixed but unknown parameter θ where θ ∈ Θ 1 under the H 1 hypothesis and θ = θ 0 unde...

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Bibliographic Details
Main Authors: Hao Chen, Rogers, U.
Format: Conference Proceeding
Language:English
Subjects:
Cognitive radio
Cooperative Sensing
Distributed Detection
Gaussian noise
Optimization
Random variables
Sensors
Testing
Uniformly Most Powerful Test
Wireless sensor networks
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Summary:In this paper, a special class of distributed composite binary hypothesis testing problem with monotonic likelihood ratio is investigated. The sensor observations are assumed to be conditionally independent given a fixed but unknown parameter θ where θ ∈ Θ 1 under the H 1 hypothesis and θ = θ 0 under the H 0 hypothesis. The optimal form of sensor decision rule is established under both the Neyman-Pearson and Bayesian criteria. As an illustrative example, the design of an optimal cognitive radio rule for cooperative spectrum sensing is established.
ISSN:1058-6393
2576-2303
DOI:10.1109/ACSSC.2011.6190304