Title

Interference Aware Spectrum Allocation In Ieee 802.22 Wireless Mesh Networks

Abstract

Since static spectrum allocation has proved to be ineffective in maximizing spectrum utilization over time and space, dynamic spectrum access is clearly the best alternative for efficient usage of radio spectrum. In order to take advantage of the flexibilities presented by dynamic spectrum access, the newly proposed IEEE 802.22 standard based on cognitive radio is seen as one of the solutions that can harness the unused or under-utilized spectrum. Also, the recent success of wireless mesh networks is creating the possibility of availing wide-area wireless back-haul networks without the infrastructure cost that will have increased network resource utilization and greater performance characteristics at low cost. In this research, we study the current IEEE 802.22 system architecture and investigate the limitations in creating wireless back-haul mesh networks due to its lack of knowledge about the spectrum bands to be used. In this regard, we propose a coordinated distributed scheme for IEEE 802.22 enabled devices to establish a mesh network with reduced interference. The coordination is initiated by the base station and is followed by the iterative joining of the IEEE 802.22 consumer premise equipments to the mesh network in a distributed manner. We take a graph coloring approach and propose an algorithm called Maximum Utility Graph Coloring (MUGC) that allocates spectrum to the mesh network, enabling higher spectrum utilization and reduced collisions. We explore two objective functions: maximize utility and proportional fair utility to allocate spectrum efficiently. Through extensive simulation experiments, we demonstrate how the proposed algorithm helps reduce collisions and most importantly, increase spectrum utilization among IEEE 802.22 devices.

Publication Date

12-1-2008

Publication Title

Proceedings of the 8th IASTED International Conference on Wireless and Optical Communications, WOC 2008

Number of Pages

42-47

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

62749104423 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/62749104423

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