Spectrum allocation in cognitive radio networks using chaotic biogeography-based optimisation

被引：8

作者：

Tegou, Thomas I. ^{[1
]}

Tsiflikiotis, Antonios ^{[1
]}

Vergados, Dimitrios D. ^{[2
]}

Siakavara, Katherine ^{[1
]}

Nikolaidis, Spiros ^{[1
]}

Goudos, Sotirios K. ^{[1
]}

Sarigiannidis, Panagiotis ^{[3
,4
]}

Obaidat, Mohammad ^{[5
]}

机构：

[1] Aristotle Univ Thessaloniki, Dept Phys, Thessaloniki 54124, Greece

[2] Univ Piraeus, Dept Informat, 80 Karaoli & Dimitriou St, GR-18534 Piraeus, Greece

[3] Univ Western Macedonia Karamanli & Ligeris, Dept Informat & Telecommun Engn, Karamanli 50100, Kozani, Greece

[4] Univ Western Macedonia Karamanli & Ligeris, Dept Informat & Telecommun Engn, Ligeris 50100, Kozani, Greece

[5] Univ Jordan, King Abdullah II Sch IT, Amman, Jordan

来源：

IET NETWORKS | 2018年 / 7卷 / 05期

关键词：

channel allocation; radio networks; cognitive radio; optimisation; cognitive radio networks; chaotic biogeography-based optimisation; spectrum utilisation; available channels; secondary users; spectrum allocation problem; dynamic spectrum assignment; NP-hard problem;

D O I：

10.1049/iet-net.2017.0264

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Cognitive radio networks are a promising technology for the improvement of the spectrum utilisation. The basic idea is to maximise the utilisation of the available spectrum by dynamically assigning available channels to secondary users. This problem known as the spectrum allocation problem is non-deterministic polynomial-time hard (NP-hard). Chaotic biogeography-based optimisation (CBBO) is a recently proposed evolutionary algorithm that can be applied to the above-mentioned problem. The authors compare CBBO with other popular algorithms in different spectrum allocation problem cases. The results show that CBBO performs in general better or similar to the other algorithms.

引用

页码：328 / 335

页数：8

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