Distributed Detection in Massive MIMO Wireless Sensor Networks under Perfect and Imperfect CSI

This paper considers the problem of distributed detection for massive multiple-input multiple-output (MIMO) wireless sensor networks (WSNs). Neyman-Pearson criterion based fusion rules are developed at the fusion center (FC) that also incorporate the local probabilities of detection and false alarm of the constituent sensor nodes. Closed-form expressions are obtained for the probabilities of detection and false alarm at the FC for various signaling schemes employed by the sensors. The fusion rules and analysis are extended to the scenario with imperfect channel state information (CSI). Furthermore, signaling matrices are determined for the massive MIMO WSN to enhance detection performance. The asymptotic detection performance of the WSN is analyzed for the large antenna regime, which yields pertinent power scaling laws with respect to the number of antennas at the FC. Simulation results demonstrate the improved performance of the proposed schemes and also validate the theoretical findings.