Distributed detection using MRC with censored sensors and Rayleigh faded communications

In this paper, we consider the problem of fusing decisions in a distributed detection system when the local binary decisions made at the sensors, relative to observations of a common binary phenomenon, are transmitted over wireless links subject to Rayleigh flat fading and additive noise. A training-based channel estimator is used at the fusion center (FC) to estimate the complex Gaussian fading coefficients characterizing the channels between the sensors and the FC. We use channel state information (CSI) on the fading coefficients for censoring the sensors. Locally optimal decision threshold is considered for binary quantization at the sensors. The detection error probability, using a maximal ratio combining (MRC) fusion rule, is selected as a qualitative measure of system performance and is evaluated by means of simulations. We also use majority logic fusion at the FC to compare detection error probability with MRC after censoring sensors. We study the effects, on the system performance, of the channel estimation error, the channel signal-to-noise ratio (SNR), the sensor SNR, and the number of selected sensors.