Information fusion by utilizing multiple distributed sensors

is studied in this work. Extending the classical parallel fusion structure

by incorporating the fading channel layer that is omnipresent in wireless

sensor networks, we derive the likelihood ratio based fusion rule given fixed

local decision devices. This optimum fusion rule, however, requires perfect

knowledge of the local decision performance indices as well as the fading

channel. To address this issue, two alternative fusion schemes, namely, the

maximum ratio combining statistic and a two-stage approach using the

Chair–Varshney fusion rule, are proposed that alleviate these requirements

and are shown to be the low and high signal-to-noise ratio (SNR) equivalents

of the likelihood-based fusion rule