We study channel-aware binary-decision fusion over a shared Rayleigh flat-fading channel with multiple antennas at the Decision Fusion Center (DFC). We present the optimal rule and derive sub-optimal fusion rules, as alternatives with improved numerical stability, reduced complexity and lower system knowledge required. The set of rules is derived following both "Decode-and-Fuse" and "Decode-then-Fuse" approaches. Simulation results for performances are presented both under Neyman-Pearson and Bayesian frameworks. The effect of multiple antennas at the DFC for the presented rules is analyzed, showing corresponding benefits and limitations. Also, the effect on performances as a function of the number of sensors is studied under a total power constraint.
Channel-Aware Decision Fusion in Distributed MIMO Wireless Sensor Networks: Decode-and-Fuse vs. Decode-then-Fuse
ROMANO, Gianmarco;SALVO ROSSI, Pierluigi
2012
Abstract
We study channel-aware binary-decision fusion over a shared Rayleigh flat-fading channel with multiple antennas at the Decision Fusion Center (DFC). We present the optimal rule and derive sub-optimal fusion rules, as alternatives with improved numerical stability, reduced complexity and lower system knowledge required. The set of rules is derived following both "Decode-and-Fuse" and "Decode-then-Fuse" approaches. Simulation results for performances are presented both under Neyman-Pearson and Bayesian frameworks. The effect of multiple antennas at the DFC for the presented rules is analyzed, showing corresponding benefits and limitations. Also, the effect on performances as a function of the number of sensors is studied under a total power constraint.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
