Rate Allocation for Decentralized Detection in Wireless Sensor Networks

TL;DR

This paper investigates optimal rate allocation strategies in decentralized detection for wireless sensor networks, especially when the number of active sensors is limited, extending previous work to more realistic constraints.

Contribution

It extends existing results on rate allocation to scenarios with a maximum number of active sensors, providing conditions for uniform allocation optimality.

Findings

Uniform rate allocation is optimal under certain conditions.

Numerical verification confirms these conditions for Gaussian models.

The work applies to sensor design with rate constraints.

Abstract

We consider the problem of decentralized detection where peripheral nodes make noisy observations of a phenomenon and send quantized information about the phenomenon towards a fusion center over a sum-rate constrained multiple access channel. The fusion center then makes a decision about the state of the phenomenon based on the aggregate received data. Using the Chernoff information as a performance metric, Chamberland and Veeravalli previously studied the structure of optimal rate allocation strategies for this scenario under the assumption of an unlimited number of sensors. Our key contribution is to extend these result to the case where there is a constraint on the maximum number of active sensors. In particular, we find sufficient conditions under which the uniform rate allocation is an optimal strategy, and then numerically verify that these conditions are satisfied for some relevant sensor design rules under a Gaussian observation model.