Distributed Detection Fusion in Clustered Sensor Networks over Multiple Access Fading Channels
Sami Aldalahmeh, Domenico Ciuonzo

TL;DR
This paper develops and analyzes distributed detection fusion methods for clustered wireless sensor networks over fading channels, proposing optimal and suboptimal rules that improve detection performance and reduce power consumption.
Contribution
It introduces new fusion rules based on moment matching for non-ideal MACs, and analyzes their performance in different propagation environments.
Findings
Increasing clusters improves detection performance.
MOR-Gaussian algorithms excel in free-space conditions.
Log-normal algorithms perform better in ground-reflection and low SNR scenarios.
Abstract
In this paper, we tackle decision fusion for distributed detection in a randomly-deployed clustered wireless sensor networks (WSNs) operating over a non-ideal multiple access channels (MACs), i.e. considering Rayleigh fading, pathloss and additive noise. To mitigate fading, we propose the distributed equal gain transmit combining (dEGTC) and distributed maximum ratio transit combining (dMRTC). The first and second order statistics of the received signals were analytically computed via stochastic geometry tools. Then the distribution of the received signal over the MAC are approximated by Gaussian and log-normal distributions via moment matching. This enabled the derivation of moment matching optimal fusion rules (MOR)for both distributions. Moreover, suboptimal simpler fusion rules were also proposed, in which all the CHs data are equally weighed, which is termed moment matching equal…
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