Improved Active Sensing Performance in Wireless Sensor Networks via Channel State Information - Extended Version

TL;DR

This paper proposes a method to enhance active sensing in wireless sensor networks by leveraging channel state information, improving tracking accuracy and energy efficiency through a joint sensor and communication channel approach.

Contribution

It introduces a joint tracking framework that incorporates communication channel data, modeling it as a partially observable Markov decision process to optimize sensor selection.

Findings

Using channel information improves tracking precision.

The approach reduces energy consumption.

Sub-optimal strategies outperform traditional methods.

Abstract

Active sensing refers to the process of choosing or tuning a set of sensors in order to track an underlying system in an efficient and accurate way. In a wireless environment, among the several kinds of features extracted by traditional sensors, the information carried by the communication channel about the state of the system can be used to further boost the tracking performance and save energy. A joint tracking problem which considers sensor measurements and communication channel together for tracking purposes is set up and solved. The system is modeled as a partially observable Markov decision problem and the properties of the cost-to-go function are used to reduce the problem complexity. In particular, upper and lower bounds to the optimal sensor selection choice are derived and used to introduce sub-optimal sensing strategies. Numerical results show the advantages of using the channel as an additional way for improving the tracking precision and reduce the energy costs.