Bandwidth-constrained MAP estimation for wireless sensor networks

We deal with distributed parameter estimation algorithms for use in wireless sensor networks (WSNs) with a fusion center when only quantized observations are available due to power/bandwidth constraints. The main goal of the paper is to design efficient estimators when the parameter can be modelled as random with a priori information. In particular, we develop maximum a posteriori (MAP) estimators for distributed parameter estimation and formulate the problem under different scenarios. We show that the pertinent objective function is concave and hence, the corresponding MAP estimator can be obtained efficiently through simple numerical maximization algorithms.