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 ∈ Θ1 under the H1 hypothesis and θ = θ0 under the H0 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.
Chen, Hao and Rogers, Uri. (2011). "Uniformly Most Powerful Distributed Detection and its Application in Cooperative Spectrum Sensing". 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 1674-1676. http://dx.doi.org/10.1109/ACSSC.2011.6190304