Decision Fusion Rules over Rician Fading Channel for Wireless Sensor Networks

This work considers the problem of decision fusion in wireless sensor networks with Rician fading channels between sensors and the fusion center. Optimal likelihood ratio (LR) based decision fusion rule requires instantaneous channel state information. However, wireless sensor networks are resource limited systems, channel estimation may cost considerable battery power and bandwidth. Therefore, the optimal LR-based rules can hardly be utilized in practice. For Rician fading channel, this work derives a LR-based decision fusion method which requires only channel statistics in stead of instantaneous channel state information. Through simulation, it is shown that the performance of the channel statistics based decision fusion rule can approach that of the optimal LR-based method under the condition of large Rician K factor and high SNR.