Abstract

This paper considers a wireless sensor network for locating a static target or tracking a dynamic target, which is characterized a priori by a Gaussian mixture distribution. An amplify-and-forward relay node acts as a wireless bridge in relaying the sensor's independent observations of the target to a fusion center (FC). Joint power allocation is considered for the sensors and relay to optimize a Bayesian filter, which is deployed at the FC for a global estimate of the target. The mean squared error of the Bayesian filter is already computationally intractable for fixed sensor and relay transmitter power, so power allocation to minimize its mean squared error is a very challenging problem. In this paper, the problem is addressed by an iterative procedure of very low computational complexity. Simulations are provided to support the efficiency of our proposed power allocation.

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