Elements of information theory
Elements of information theory
An introduction to signal detection and estimation (2nd ed.)
An introduction to signal detection and estimation (2nd ed.)
Batch and on-line parameter estimation of Gaussian mixtures based on the joint entropy
Proceedings of the 1998 conference on Advances in neural information processing systems II
Distributed Detection and Data Fusion
Distributed Detection and Data Fusion
Information Theory: Coding Theorems for Discrete Memoryless Systems
Information Theory: Coding Theorems for Discrete Memoryless Systems
Convex Optimization
Decentralized detection in sensor networks
IEEE Transactions on Signal Processing
Asymptotic results for decentralized detection in power constrained wireless sensor networks
IEEE Journal on Selected Areas in Communications
Optimal sensor selection in binary heterogeneous sensor networks
IEEE Transactions on Signal Processing
Power control strategy for distributed multiple-hypothesis detection
IEEE Transactions on Signal Processing
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In distributed detection systems with wireless sensor networks, communication between sensors and a fusion center is not perfect due to interference and limited communication powerof the sensors to combat noise. The problem of optimizing detection performance with imperfect communication between the sensors and the fusion center over wireless channels brings a new challenge to distributed detection. In this paper, a distributed detection system infrastructure is provided, and a multiaccess channel model is included to account for imperfect communication between the sensors and the fusion center. The J-divergence between the distributions of the detection statistic under different hypotheses is used as a performance criterion instead of the probability of error in order to provide a tractable analysis. Optimizing the performance (in terms of the J-divergence) under a total communication power constraint on the sensors is studied, and the optimal power allocation is provided.