On base station localization for state estimation over lossy networks

TL;DR

This paper investigates the optimal placement of a base station for state estimation in sensor networks with lossy communication, showing that placing it at a sensor location is optimal in certain cases.

Contribution

It provides a theoretical analysis demonstrating optimal base station placement at sensor locations under specific packet loss models, supported by empirical evidence.

Findings

Optimal base station placement at sensor locations in two-sensor scenarios

Empirical evidence suggests the result extends to more general cases

Analysis improves understanding of network design for reliable state estimation

Abstract

We consider a state estimation problem where observations are made by multiple sensors. These observations are communicated over a lossy wireless network to a central base station that computes estimates via a Kalman filter. The goal is to determine the optimal location of the base station under a certain class of packet loss probability models. It is shown in the two sensor case that the base station is optimally located at one of the sensor locations. Empirical evidence suggests that the result holds in some generality.