Optimal Energy Allocation for Estimation in Wireless Sensor Networks

A sensor network´s motes observe the environment, make estimates based on their observations, and send/relay these estimates to a Cluster-Head (CH). There are two sources of error in these multi-hop networks: observations are corrupted by noise and transmissions suffer communication errors. 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. The CH fuses these unbiased local estimates into a global one using a Best Linear Unbiased Estimator (BLUE). We determine both the minimum energy required for the network to produce a BLUE estimate with a prescribed error variance and show how this energy should be allocated across the rings of a multi-hop network and the motes in each ring.