Reliable Prediction of Channel Assignment Performance in Wireless Mesh Networks

TL;DR

This paper introduces a reliable method for predicting channel assignment performance in wireless mesh networks, aiding in interference mitigation and optimal CA scheme selection through simulation-based validation.

Contribution

It presents a novel interference estimation and CA performance prediction approach validated with ns-3 simulations, addressing the lack of predictive tools in WMN channel assignment.

Findings

Accurate CA performance predictions align with simulation data

The approach effectively estimates interference levels in WMNs

Supports better CA scheme selection for interference mitigation

Abstract

The advancements in wireless mesh networks (WMN), and the surge in multi-radio multi-channel (MRMC) WMN deployments have spawned a multitude of network performance issues. These issues are intricately linked to the adverse impact of endemic interference. Thus, interference mitigation is a primary design objective in WMNs. Interference alleviation is often effected through efficient channel allocation (CA) schemes which fully utilize the potential of MRMC environment and also restrain the detrimental impact of interference. However, numerous CA schemes have been proposed in research literature and there is a lack of CA performance prediction techniques which could assist in choosing a suitable CA for a given WMN. In this work, we propose a reliable interference estimation and CA performance prediction approach. We demonstrate its efficacy by substantiating the CA performance predictions for a given WMN with experimental data obtained through rigorous simulations on an ns-3 802.11g environment.