Abstract
As a famous representative of the NP-Hard problem, the optimization of cognitive radio spectrum allocation has attracted the attention of many scholars. In this paper, a quantum lion swarm optimization (QLSO) algorithm is proposed to solve the problem of spectrum allocation. Firstly, we introduce the basic lion swarm optimization algorithm and cognitive radio network model. Secondly, we introduce quantum coding and order some operators in the QLSO algorithm. Finally, we select several common swarm intelligence algorithms as a comparison and conduct simulation experiments. The experiments on randomly generated spectrum allocation models with different topologies show that the QLSO algorithm has higher solution quality and convergence performance than the other algorithms, such as discrete particle swarm optimization (DPSO) algorithm, genetic algorithm (GA), and binary lion swarm optimization (BLSO) algorithm.
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Acknowledgment
This study is supported by the Shandong Province Science Foundation of China (Grant No. ZR2020MF153) and Key Innovation Project of Shandong Province (Grant No. 2019JZZY010111).
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Jiang, K., Jiang, M. (2022). Research on Spectrum Allocation Algorithm Based on Quantum Lion Swarm Optimization. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2022. Lecture Notes in Computer Science, vol 13344. Springer, Cham. https://doi.org/10.1007/978-3-031-09677-8_6
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DOI: https://doi.org/10.1007/978-3-031-09677-8_6
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