Improved Decision Fusion Model for Wireless Sensor Networks over Rayleigh Fading Channels
Files
Date
2017
Authors
Jamoos, Ali
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI Technologies
Abstract
This paper deals with decision fusion in wireless sensor networks (WSNs) over Rayleigh
fading channels. The likelihood ratio test (LRT) is considered as the optimal fusion rule when
applied at the fusion center (FC). However, applying the LRT at the FC requires both the channel
state information (CSI) and the local sensors’ performance indices. Acquiring such information is
considered as an overhead in energy and bandwidth constrained systems such as WSNs. To avoid
these drawbacks, we propose a modification to the traditional three-layer system model of a WSN
where the LRT is applied as a local decision making method at the sensors level. Applying the
LRT at the sensors level does not require the CSI or the local sensors’ performance indices. It only
requires the signal-to-noise ratio (SNR). Moreover, a new fusion rule based on selection combining
(SC) is suggested. This fusion method has the lowest complexity when compared to other diversity
combining based fusion rules such as the equal gain combiner (EGC) and the maximum ratio
combiner (MRC). Simulation results show that the performance of the proposed model outperforms
the traditional model. In addition, applying the EGC at the FC in the proposed model provides
comparable performance to the traditional model that applies the LRT at the FC.
Description
Keywords
wireless sensor networks , decisions fusion , fading channels , likelihood ratio test , EGC , MRC , SC