Optimal Power Allocation for Distributed Detection over MIMO Channels in Wireless Sensor Networks
Xin Zhang, H. Vincent Poor, Mung Chiang

TL;DR
This paper develops an optimal power allocation scheme for distributed detection in wireless sensor networks over MIMO channels, balancing communication quality and local decision accuracy to improve detection performance efficiently.
Contribution
It introduces a novel power allocation method based on J-divergence for sensors with imperfect communication, including a weighted water-filling solution for orthogonal channels.
Findings
Proposed power allocation reduces power consumption by up to 75% compared to equal allocation.
The scheme effectively balances channel quality and local decision quality.
Simulation results demonstrate significant performance improvements with the new method.
Abstract
In distributed detection systems with wireless sensor networks, the communication between sensors and a fusion center is not perfect due to interference and limited transmitter power at the sensors to combat noise at the fusion center's receiver. The problem of optimizing detection performance with such imperfect communication brings a new challenge to distributed detection. In this paper, sensors are assumed to have independent but nonidentically distributed observations, and a multi-input/multi-output (MIMO) 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 in order to provide a tractable analysis. Optimizing the performance (in terms of the J-divergence) with individual and total transmitter power…
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