Open AccessBio‐inspired collaborative spectrum sensing and allocation for cognitive radios
Author(s) -
Azmat Freeha,
Chen Yunfei,
Stocks Nigel
Publication year - 2015
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2014.0769
Subject(s) - cognitive radio , computer science , particle swarm optimization , weighting , firefly protocol , mathematical optimization , firefly algorithm , spectrum (functional analysis) , subcarrier , algorithm , wireless , telecommunications , mathematics , orthogonal frequency division multiplexing , zoology , physics , quantum mechanics , biology , radiology , channel (broadcasting) , medicine
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.