J‐divergence‐based Power Allocation in Wireless Sensor Networks with Distributed Detection under Correlated Noises

Abstract

SummaryIn this paper, the power allocation problem in a wireless sensor network (WSN) with binary distributed detection is considered. It is assumed that the sensors independently transmit their local decisions to a fusion center (FC) through a slow fading orthogonal multiple access channel (OMAC), where, in every channel, the interferences from other devices are considered as correlated noises. In this channel, the associated power allocation optimization problem with equal power constraint is established between statistical distributions under different hypotheses by using the Jeffrey divergence (J‐divergence) as a performance criterion. It is shown that this criterion for the power allocation problem is more efficient compared to other criteria such as mean square error (MSE). Moreover, several numerical simulations and examples are presented to illustrate the effectiveness of the proposed approach.