Robust power allocation for energy-efficient location aware networks

TL;DR

This paper develops a robust optimization framework for power allocation in wireless location-aware networks, improving localization accuracy and network performance under uncertain network parameters.

Contribution

It introduces a novel robust power allocation method formulated as conic programs, enabling distributed implementation and outperforming uniform and non-robust schemes.

Findings

Robust schemes outperform non-robust ones under parameter uncertainty.

Proposed methods significantly improve localization accuracy.

Distributed power allocation schemes are computationally efficient.

Abstract

In wireless location-aware networks, mobile nodes (agents) typically obtain their positions through ranging with respect to nodes with known positions (anchors). Transmit power allocation not only affects network lifetime, throughput, and interference, but also determines localization accuracy. In this paper, we present an optimization framework for robust power allocation in network localization to tackle imperfect knowledge of network parameters. In particular, we formulate power allocation problems to minimize the squared position error bound (SPEB) and the maximum directional position error bound (mDPEB), respectively, for a given power budget. We show that such formulations can be efficiently solved via conic programming. Moreover, we design an efficient power allocation scheme that allows distributed computations among agents. The simulation results show that the proposed schemes significantly outperform uniform power allocation, and the robust schemes outperform their non-robust counterparts when the network parameters are subject to uncertainty.