TY - GEN
T1 - Uniformly most powerful distributed detection and its application in cooperative spectrum sensing
AU - Chen, Hao
AU - Rogers, Uri
PY - 2011
Y1 - 2011
N2 - 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 ε 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.
AB - 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 ε 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.
KW - Cooperative Sensing
KW - Distributed Detection
KW - Uniformly Most Powerful Test
UR - http://www.scopus.com/inward/record.url?scp=84861323575&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2011.6190304
DO - 10.1109/ACSSC.2011.6190304
M3 - Conference contribution
AN - SCOPUS:84861323575
SN - 9781467303231
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 1674
EP - 1676
BT - Conference Record of the 45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011
T2 - 45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011
Y2 - 6 November 2011 through 9 November 2011
ER -