Energy-efficient quantization and transmission in distributed estimation

In this paper, we investigate the problem of energy-efficient distributed estimation in wireless sensor networks. In an inhomogeneous sensing and transmission environment, the minimization of total energy is jointly determined by the optimal quantization and transmission scheduling. In order to minimize the total energy under the mean squared error (MSE) and total transmission time constraints, we design a joint algorithm which iteratively computes the optimal quantization lengths and transmission times. We proved that the algorithm is convergent. Simulations show that the iteration converges quickly, and significant energy saving can be achieved when compared with the uniform quantization and transmission scheme.