Joint Power and Quantization Optimization for Target Tracking in Wireless Sensor Networks

Abstract

Consider a scenario where a subset of sensors has been selected for target tracking in an energy-constrained wireless sensor network. They communicate their quantized state measurements over noisy Rayleigh fading channels to a fusion center, where centralized estimation of target state is performed. In this context, we consider the problem of determining optimum quantization bits and transmission power per bit for all sensors such that both resource utilization and overall estimation error at the fusion center are minimized. Unlike prior efforts, we incorporate the operating state (characterized by the amount of residual battery power) of the sensors in the optimization framework. Analytical solutions for optimum power and number of quantization bits are derived and validated with numerical examples through simulations. We study the effect of channel quality, local measurement noise, and operating states of the sensors on their optimum choice for quantization bits and transmit power per bit.