Research Article
Spectrum Allocation in Cognitive Radio Networks by Hybrid Analytic Hierarchy Process and Graph Coloring Theory
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@INPROCEEDINGS{10.1007/978-3-319-73447-7_2, author={Jianfei Shi and Feng Li and Xin Liu and Mu Zhou and Jiangxin Zhang and Lele Cheng}, title={Spectrum Allocation in Cognitive Radio Networks by Hybrid Analytic Hierarchy Process and Graph Coloring Theory}, proceedings={Machine Learning and Intelligent Communications. Second International Conference, MLICOM 2017, Weihai, China, August 5-6, 2017, Proceedings, Part II}, proceedings_a={MLICOM}, year={2018}, month={2}, keywords={Cognitive radio Graph coloring Spectrum allocation Analytic hierarchy process}, doi={10.1007/978-3-319-73447-7_2} }
- Jianfei Shi
Feng Li
Xin Liu
Mu Zhou
Jiangxin Zhang
Lele Cheng
Year: 2018
Spectrum Allocation in Cognitive Radio Networks by Hybrid Analytic Hierarchy Process and Graph Coloring Theory
MLICOM
Springer
DOI: 10.1007/978-3-319-73447-7_2
Abstract
In this paper, a graph coloring-based spectrum allocation algorithm in cognitive radio networks combined with analytic hierarchy process is proposed. By analyzing several key factors that affect the quality of the leased spectrum, the algorithm combines the graph algorithm and analytic hierarchy process to assign the optimal spectrum to cognitive users orderly. Simulation results show that the proposed algorithm can effectively improve the network efficiency compared with original algorithms and arose inconspicuous loss to the whole network’s fairness. The proposal not only improves the efficiency of spectrum allocation, but also balances the requirements of the overall fairness of cognitive radio networks.
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