Interference-Aware Channel Assignment for Maximizing Throughput in WMN

TL;DR

This paper proposes an interference-aware clustered channel assignment scheme for wireless mesh networks that reduces interference and enhances throughput, outperforming existing methods like BFSCA and Distributed Greedy CA in simulations.

Contribution

It introduces a novel interference-aware clustering approach prioritizing interference minimization over channel diversity to improve WMN performance.

Findings

Scheme reduces interference more effectively.

Network throughput is significantly increased.

Outperforms BFSCA and Distributed Greedy CA in simulations.

Abstract

Wireless Mesh network (WMN) is dynamically self-organizing and self-configured, with the nodes in the network automatically establishing an ad-hoc network and maintaining the mesh connectivity. The ability to use multiple-radios and multiple channels can be cashed to increase aggregate throughput of wireless mesh network. Thus the efficient use of available interfaces and channels without interference becomes the key factor. In this paper we propose, interference aware clustered based channel assignment schemes which minimizes the interference and increases throughput. In our proposed scheme we have given priority to minimize interference from nearby mesh nodes in interference range than maximizing channel diversity. We simulated our proposed work using NS-3 and results show that our scheme improves network performance than BFSCA and Distributed Greedy CA.