Collaborative spectrum sensing optimisation algorithms for cognitive radio networks

Arshad, K., Imran, M. A. and Moessner, K. (2010) Collaborative spectrum sensing optimisation algorithms for cognitive radio networks. International Journal of Digital Multimedia Broadcasting, 2010, 424036. (doi:10.1155/2010/424036)

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Abstract

The main challenge for a cognitive radio is to detect the existence of primary users reliably in order to minimise the interference to licensed communications. Hence, spectrum sensing is a most important requirement of a cognitive radio. However, due to the channel uncertainties, local observations are not reliable and collaboration among users is required. Selection of fusion rule at a common receiver has a direct impact on the overall spectrum sensing performance. In this paper, optimisation of collaborative spectrum sensing in terms of optimum decision fusion is studied for hard and soft decision combining. It is concluded that for optimum fusion, the fusion centre must incorporate signal-to-noise ratio values of cognitive users and the channel conditions. A genetic algorithm-based weighted optimisation strategy is presented for the case of soft decision combining. Numerical results show that the proposed optimised collaborative spectrum sensing schemes give better spectrum sensing performance.

Item Type:Articles
Additional Information:This work was performed in the project E3 which has received research funding from the EU FP7 framework.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Imran, Professor Muhammad
Authors: Arshad, K., Imran, M. A., and Moessner, K.
College/School:College of Science and Engineering > School of Engineering
Journal Name:International Journal of Digital Multimedia Broadcasting
Publisher:Hindawi Publishing Corporation
ISSN:1687-7578
ISSN (Online):1687-7586
Copyright Holders:Copyright © 2010 Kamran Arshad et al.
First Published:First published in International Journal of Digital Multimedia Broadcasting 2010: 424036
Publisher Policy:Reproduced under a Creative Commons License

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