Channel-Aware Distributed Best-Linear-Unbiased Estimation With Reduced Communication Overheads
Energy consumption in wireless sensor networks is dominated by intra-network communication dedicated to coordination and information exchange between sensor nodes and the fusion center. The design of distributed estimation algorithms with reduced communication overheads is thus rather crucial. For amplify-and-forward sensor networks over flat fading channels, this paper proposes a new distributed Best-Linear-Unbiased-Estimation (BLUE) scheme by exploiting the statistical characterizations of the sensing noise variance and channel gains. The performance measure is the reciprocal of the mean square error averaged over the considered statistical distributions. The authors derive a closed-form lower bound for the adopted design metric.