异构物联网中基于粒子群算法的频谱分配方法
Spectrum Allocation Method Based on Particle Swarm Optimization in Heterogeneous Internet of Things
DOI: 10.12677/CSA.2021.118222, PDF,  被引量    国家科技经费支持
作者: 蒋 鹏, 刘 卫, 富 爽*:黑龙江八一农垦大学信息与电气工程学院,黑龙江 大庆;顾环宇:中国卫通集团股份有限公司,北京
关键词: 认知无线电物联网异构网络频谱分配粒子群算法Cognitive Radio Internet of Things Heterogeneous Network Spectrum Allocation Particle Swarm Optimization
摘要: 针对异构物联网中不同网络相互重叠、相互干扰和信道重叠等情况下的复杂频谱分配问题,提出了异构物联网中基于粒子群算法的频谱分配方法。考虑信道空闲状态、网络干扰状态和信道重叠状态,将总网络效益的最大化的频谱分配问题建模为非线性约束0-1整数规划问题,使用粒子群算法求解该问题。仿真结果显示,本文方法能够获得最优的频谱分配策略,相比随机的频谱分配方法,能够有效提高系统的总网络效益及平均频谱需求满足率。
Abstract: Aiming at the complex spectrum allocation problem when different networks overlap, interfere with each other and channel overlap in heterogeneous Internet of things, a spectrum allocation method based on particle swarm optimization algorithm in heterogeneous Internet of things is proposed. Considering the channel idle state, network interference state and channel overlap state, the spectrum allocation problem to maximize the total network utilities is modeled as a nonlinear constrained 0-1 integer programming problem, which is solved by particle swarm optimization algorithm. Simulation results show that the proposed method can obtain the optimal spectrum allocation strategy. Compared with the random spectrum allocation method, it can effectively improve the total network efficiency and average spectrum demand satisfaction rate of the system.
文章引用:蒋鹏, 刘卫, 富爽, 顾环宇. 异构物联网中基于粒子群算法的频谱分配方法[J]. 计算机科学与应用, 2021, 11(8): 2167-2178. https://doi.org/10.12677/CSA.2021.118222

参考文献

[1] Monemian, M., Mahdavi, M. and Omidi, M.J. (2019) Improving the Lifetime of Multichannel Cognitive Radio Sensor Networks via New Spectrum Sensing Method. Transactions on Emerging Telecommunications Technologies, 30, Arti-cle No. e3551. [Google Scholar] [CrossRef
[2] 胡海波. 无线异构网络发展综述[J]. 现代电信科技, 2009, 39(12): 19-22. 30.
[3] Tarek, D., Benslimane, A., Darwish, M. and Kotb, A.M. (2020) Survey on Spectrum Shar-ing/Allocation for Cognitive Radio Networks Internet of Things. Egyptian Informatics Journal, 21, 231-239. [Google Scholar] [CrossRef
[4] Khalifa, A.H., Shehata, M.K., Gasser, S.M. and El-Mahallawy, M.S. (2020) Enhanced Cooperative Behavior and Fair Spectrum Allocation for Intelligent IoT Devices in Cognitive Radio Networks. Physical Communication, 43, Article ID: 101190. [Google Scholar] [CrossRef
[5] 刘鑫一, 姜建. 基于拍卖理论的认知物联网频谱分配策略[J]. 中国科技论文, 2016, 11(19): 2187-2192, 2204.
[6] Ejaz, W. and Ibnkahla, M. (2018) Multiband Spectrum Sensing and Resource Allocation for IoT in Cognitive 5G Networks. IEEE Internet of Things Journal, 5, 150-163. [Google Scholar] [CrossRef
[7] Ding, X., Tian, X., Liu, X. and Chen, Y. (2020) PP-SPEC: Se-curing Spectrum Allocation for Internet of Things. IEEE Internet of Things Journal, 7, 10826-10836. [Google Scholar] [CrossRef
[8] Yang, N., Zhang, H., Long, K., Jiang, C. and Yang, Y. (2018) Spectrum Management Scheme in Fog IoT Networks. IEEE Communications Magazine, 56, 101-107. [Google Scholar] [CrossRef
[9] Li, F., Lam, K., Meng, L., Luo, H. and Wang, L. (2019) Trading-Based Dynamic Spectrum Access and Allocation in Cognitive Internet of Things. IEEE Access, 7, 125952-125959. [Google Scholar] [CrossRef
[10] Han, R., Gao, Y., Wu, C. and Lu, D. (2018) An Effective Multi-Objective Optimization Algorithm for Spectrum Allocations in the Cognitive-Radio-Based Internet of Things. IEEE Access, 6, 12858-12867. [Google Scholar] [CrossRef
[11] 葛雨明, 孙毅, 蒋海, 李军, 李忠诚. 基于认知无线电技术的动态频谱分配方案研究[J]. 计算机学报, 2012, 35(3): 446-453.
[12] Toka, L. and Vidács, A. (2009) General Distributed Economic Framework for Dynamic Spectrum Allocation. Computer Communications, 32, 1955-1964. [Google Scholar] [CrossRef
[13] 杜祜康, 赵英凯. 整数规划问题智能求解算法综述[J]. 计算机应用研究, 2010, 27(2): 408-412.
[14] Zhao, Z., Peng, Z., Zheng, S. and Shang, J. (2009) Cognitive Radio Spec-trum Allocation Using Evolutionary Algorithms. IEEE Transactions on Wireless Communications, 8, 4421-4425. [Google Scholar] [CrossRef