Location-Quality-aware Policy Optimisation for Relay Selection in Mobile Networks

TL;DR

This paper presents a Markov model to optimize relay selection policies in mobile networks by accounting for localization errors, update rates, and mobility, enhancing network performance analysis.

Contribution

It introduces a novel Markov model that jointly considers localization errors, update delays, and mobility for designing optimal relay policies in wireless networks.

Findings

Localization errors significantly impact relay performance.

Optimal update rates depend on mobility and error levels.

Model-based analysis guides deployment parameter choices.

Abstract

Relaying can improve the coverage and performance of wireless access networks. In presence of a localisation system at the mobile nodes, the use of such location estimates for relay node selection can be advantageous as such information can be collected by access points in linear effort with respect to number of mobile nodes (while the number of links grows quadratically). However, the localisation error and the chosen update rate of location information in conjunction with the mobility model affect the performance of such location-based relay schemes; these parameters also need to be taken into account in the design of optimal policies. This paper develops a Markov model that can capture the joint impact of localisation errors and inaccuracies of location information due to forwarding delays and mobility; the Markov model is used to develop algorithms to determine optimal location-based relay policies that take the aforementioned factors into account. The model is subsequently used to analyse the impact of deployment parameter choices on the performance of location-based relaying in WLAN scenarios with free-space propagation conditions and in an measurement-based indoor office scenario.