Optimal Energy-Aware Distributed Estimation in Wireless Sensor Networks

The motes in a wireless sensor network observe the environment, make estimates based on their observations, and then send these estimates to a Cluster-Head (CH). A novel scheme based on dithered quantization and channel compensation is used to ensure that each mote's local estimate received by the CH is unbiased. Then the CH fuses these unbiased local estimates into a global one using a Best Linear Unbiased Estimator (BLUE). We determine the number of bits each node should transmit to reach a prescribed error variance at the CH subject to per-node limits on the energy that can be used and the per-node cost of forwarding a bit to the CH.

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