Channel optimized binary quantizers for distributed sensor networks

Distributed binary quantizer design for sensor nets tasked with a hypothesis testing problem is considered in this paper. Allowing for non-ideal transmission channels, we show that under the conditional independence assumption, the optimum binary quantizer, in the sense of minimizing the error probability, should operate on the likelihood ratio (LR) of the local sensor observations. Necessary conditions for optimality are derived to facilitate finding of optimal LRT thresholds through an iterative algorithm. A design example with binary symmetric channels between local sensors and the fusion center is given to illustrate how the results can be applied in sensor signaling design.