Bio‐inspired collaborative spectrum sensing and allocation for cognitive radios. Issue 16 (1st November 2015)

• Record Type: Journal Article
• Authors: Azmat, Freeha; Chen, Yunfei; Stocks, Nigel
• Is Part Of: IET communications. Volume 9:Issue 16(2015)
• Page Start: 1949
• Page End: 1959
• Publication Date: 2015-11-01
• Subjects: cognitive radio -- power amplifiers -- nonlinear distortion -- sensor fusion -- particle swarm optimisation -- radio spectrum management -- probability; bioinspired collaborative spectrum sensing -- cognitive radio network -- particle swarm optimisation -- optimal weighting vectors -- data fusion centre -- nonlinear distortion -- power amplifiers -- spectrum allocation -- probability of detection; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2014.0769
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : Bio‐inspired techniques, including firefly algorithm, fish school search, and particle swarm optimisation, are utilised in this study to evaluate the optimal weighting vectors used in the data fusion centre. This evaluation is performed for more realistic signals that suffer from non‐linear distortions, caused by the power amplifiers. The obtained optimal weighting vectors are then used for collaborative spectrum sensing and spectrum allocation in cognitive radio networks. Numerical results show that bio‐inspired techniques outperform the conventional algorithms used for spectrum sensing and allocation by deriving optimal weights that ensure the highest value of probability of detection and guarantee the maximum proportional fair reward for users.