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Resource Allocation Algorithm for Multi‐cell Cognitive Radio Networks with Imperfect Spectrum Sensing and Proportional Fairness
Author(s) -
Zhu Jianyao,
Liu Jianyi,
Zhou Zhaorong,
Li Li
Publication year - 2016
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.16.0115.0535
Subject(s) - cognitive radio , subcarrier , computer science , resource allocation , interference (communication) , constraint (computer aided design) , mathematical optimization , cognitive network , algorithm , power (physics) , base station , computer network , telecommunications , orthogonal frequency division multiplexing , engineering , mathematics , wireless , physics , quantum mechanics , mechanical engineering , channel (broadcasting)
This paper addresses the resource allocation (RA) problem in multi‐cell cognitive radio networks. Besides the interference power threshold to limit the interference on primary users PUs caused by cognitive users CUs, a proportional fairness constraint is used to guarantee fairness among multiple cognitive cells and the impact of imperfect spectrum sensing is taken into account. Additional constraints in typical real communication scenarios are also considered—such as a transmission power constraint of the cognitive base stations, unique subcarrier allocation to at most one CU, and others. The resulting RA problem belongs to the class of NP‐hard problems. A computationally efficient optimal algorithm cannot therefore be found. Consequently, we propose a suboptimal RA algorithm composed of two modules: a subcarrier allocation module implemented by the immune algorithm, and a power control module using an improved sub‐gradient method. To further enhance algorithm performance, these two modules are executed successively, and the sequence is repeated twice. We conduct extensive simulation experiments, which demonstrate that our proposed algorithm outperforms existing algorithms.

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