Radio Co-location Aware Channel Assignments for Interference Mitigation in Wireless Mesh Networks

TL;DR

This paper introduces intelligent, graph-theoretic channel assignment algorithms specifically designed to mitigate radio co-location interference in wireless mesh networks, thereby significantly improving network capacity.

Contribution

It presents novel, interference-aware channel assignment algorithms that focus on alleviating radio co-location interference, a less-addressed aspect in WMN research, with theoretical foundations and simulation validation.

Findings

Algorithms significantly reduce radio co-location interference.

Network capacity is notably improved compared to existing schemes.

Simulation results validate theoretical effectiveness.

Abstract

Designing high performance channel assignment schemes to harness the potential of multi-radio multi-channel deployments in wireless mesh networks (WMNs) is an active research domain. A pragmatic channel assignment approach strives to maximize network capacity by restraining the endemic interference and mitigating its adverse impact on network performance. Interference prevalent in WMNs is multi-faceted, radio co-location interference (RCI) being a crucial aspect that is seldom addressed in research endeavors. In this effort, we propose a set of intelligent channel assignment algorithms, which focus primarily on alleviating the RCI. These graph theoretic schemes are structurally inspired by the spatio-statistical characteristics of interference. We present the theoretical design foundations for each of the proposed algorithms, and demonstrate their potential to significantly enhance network capacity in comparison to some well-known existing schemes. We also demonstrate the adverse impact of radio co- location interference on the network, and the efficacy of the proposed schemes in successfully mitigating it. The experimental results to validate the proposed theoretical notions were obtained by running an exhaustive set of ns-3 simulations in IEEE 802.11g/n environments.