Parallel distributed detection for wireless sensor networks: performance analysis and design

Parallel distributed detection for wireless sensor networks is studied in this paper. The network consists of a set of local sensors and a fusion center. Each local sensor makes a binary (single-bit) or M-ary (multi-bit) decision and passes it to the fusion center where a final decision is made. The links between the local sensors and the fusion center are subject to fading and additive noise resulting in corruption of the transmitted decisions. We analyze the performance of the decision fusion based on likelihood ratio tests and derive false alarm and detection probabilities. Based on the theoretical probability expressions, we design optimal decision rules for the local sensors and the fusion center. Finally, we illustrate the performance of the parallel fusion by numerical examples