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.