Fusion of decisions transmitted over fading channels in wireless sensor networks

Information fusion by utilizing multiple distributed sensors is studied. We derive the optimal likelihood based fusion statistic for a parallel decision fusion problem with fading channel assumption. This optimum fusion rule, however, requires perfect knowledge of the local decision performance indices as well as the fading channel. Several alternatives are presented that alleviate these requirements. At low SNR, the likelihood based fusion rule reduces to a form analogous to a maximum ratio combining statistic; while at high SNR, it leads to a two-stage approach using the well known Chair-Varshney fusion rule. A third alternative, in the form of an equal gain combiner, is also proposed; it requires the least amount of information regarding the sensor/channel. Simulation shows that the two-stage approach, which considers the communication and decision fusion as two independent stages, suffers performance loss compared with the other two alternatives for a practical SNR range.