SPC05-4: Successively Structured Gaussian CEO Problem

Abstract

We consider a distributed sensor network, modeled by the Chief Executive Officer (CEO) problem, in which sensors encode their observations without collaborating with each other and send through rate constrained noiseless channels to a fusion center (FC). We use the successive Wyner-Ziv coding strategy in this problem where sensors have differing quality of observations. We determine the optimal rate allocation scheme to obtain the minimum distortion under a sum-rate constraint. We show that the optimal sum-rate distortion performance for the Gaussian CEO problem is achievable using the successive coding strategy which is inherently a less complex way of obtaining a prescribed distortion. We also determine the achievable rate region and the optimal rate allocation region for the Gaussian CEO problem. We show that if the number of sensors tends to infinity while the sum-rate is finite, the performance of the successive coding strategy with equal rate sensors converges to the rate-distortion function. The same is true when the sum-rate tends to infinity with a finite number of sensors. Finally, we obtain the communication throughput of a K-relay network based on our results for the CEO problem.