Fine-Grained Radio Resource Management to Control Interference in Dense Wi-Fi Networks

Seyedebrahimi, Mir and Bouhafs, Faycal and Raschella, Alessandro and Mackay, Michael and Shi, Q. (2017) Fine-Grained Radio Resource Management to Control Interference in Dense Wi-Fi Networks. In: IEEE Wireless Communications and Networking Conference - Proceedings. IEEE. ISBN 978-1-5090-4183-1/17

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Abstract

In spite of the enormous popularity of Wi-Fienabled devices, the utilisation of Wi-Fi radio resources (e.g. RF spectrum and transmission power levels) at Access Points (APs) is degraded in current decentralised Radio Resource Management (RRM) schemes. Most state of the art centralised control solutions apply configurations in which the network-wide impacts of the
involved parameters and their mutual relationships are ignored. In this paper, we propose an algorithm for jointly adjusting the transmission power levels and optimising the RF channel assignment of APs by taking into account the flows’ required qualities while minimising their interference impact throughout the network. The proposed solution is tailored for an operatoragnostic and Software Defined Wireless Networking (SDWN)- based centralised RRM in dense Wi-Fi networks. Our extensive simulation results validate the performance improvements of the proposed algorithm compared to the main state of the art alternative by showing more than 25% higher spectrum efficiency, satisfying the users’ demands and further mitigating the networkwide interference through flow-based and quality-oriented power
level adjustment.

Item Type: Book Section
Uncontrolled Keywords: Wireless LAN; Radio Resource Management; RF Channel Assignment; Transmission Power Control; SDWN
Subjects: G400 Computer Science
Divisions: Faculty of Computing, Engineering and the Built Environment
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology > Cloud Computing
UoA Collections > UoA11: Computer Science and Informatics
Depositing User: $ Ian McDonald
Date Deposited: 30 Jun 2017 14:41
Last Modified: 03 Jul 2017 08:30
URI: http://www.open-access.bcu.ac.uk/id/eprint/4769

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