Power Optimization for Network Localization

TL;DR

This paper develops a unified optimization framework for power allocation in wireless network localization, improving accuracy, network lifetime, and robustness through SOCP-based algorithms.

Contribution

It introduces a novel unifying approach for power allocation in both active and passive localization networks, with robust and efficient algorithms.

Findings

Algorithms are efficient and robust in simulations.

Power allocation significantly improves localization accuracy.

Framework applies to both active and passive networks.

Abstract

Reliable and accurate localization of mobile objects is essential for many applications in wireless networks. In range-based localization, the position of the object can be inferred using the distance measurements from wireless signals exchanged with active objects or reflected by passive ones. Power allocation for ranging signals is important since it affects not only network lifetime and throughput but also localization accuracy. In this paper, we establish a unifying optimization framework for power allocation in both active and passive localization networks. In particular, we first determine the functional properties of the localization accuracy metric, which enable us to transform the power allocation problems into second-order cone programs (SOCPs). We then propose the robust counterparts of the problems in the presence of parameter uncertainty and develop asymptotically optimal and efficient near-optimal SOCP-based algorithms. Our simulation results validate the efficiency and robustness of the proposed algorithms.