认知工业物联网中基于麻雀搜索算法的频谱分配策略
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作者单位:

1.贵州大学大数据与信息工程学院,贵阳 550025;2.贵州大学机械工程学院,贵阳 550025

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国家自然科学基金(62062021,61872034);贵州省科学技术基金(黔科合基础[2020]1Y254)。


Spectrum Allocation Strategy Based on Sparrow Algorithm in Cognitive Industrial Internet of Things
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Affiliation:

1.College of Big Data and Information Engineering, Guizhou University, Guiyang 550025,China;2.College of Mechanical Engineering, Guizhou University, Guiyang 550025,China

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    摘要:

    针对工业物联网因海量数据交换导致的频谱短缺问题,本文将认知无线电技术运用到工业物联网中,提出一种认知工业物联网(Cognitive industrial internet of things, CIIOT)中基于改进麻雀算法和功率控制的频谱分配策略。该策略以最大化公平性和能量效率为前提,首先使用一种基于改进地图指南针算子和步长因子的二进制麻雀搜索算法(Improved binary sparrow search algorithm, IBSSA)对CIIOT用户进行频谱分配;然后使用基于接收信噪比(SINR)的闭环功率控制算法对通信过程中的用户进行动态功率调整,达到发射功率最佳,最后将系统能量效率和公平性作为评价指标,与二进制麻雀算法(Binary sparrow algorithm, BSSA)和二进制蝙蝠算法(Binary bat algorithm, BBA)进行比较。仿真结果表明,相比BSSA和BBA算法,IBSSA算法可以获得更高的系统能量效率和用户公平性,说明本文提出的优化策略明显提高了认知工业物联网的公平性和能量效率。

    Abstract:

    In order to solve the problems of spectrum shortage caused by massive data exchange in industrial internet of things, cognitive radio technology is applied to the industrial internet of things in this paper. This paper proposes a spectrum allocation strategy based on improved sparrow algorithm and power control in cognitive industrial internet of things(CIIOT). This strategy is based on the premise of maximizing fairness and energy efficiency. First, this paper uses improved binary sparrow search algorithm(IBSSA) based on improved map compass operator and step-size factor, which is used to allocate spectrum for CIIOT users. Then, in the communication process to optimize the transmitting power, this paper uses the closed-loop power control algorithm based on receiving SINR to adjust the dynamic power of the users. Finally, the energy efficiency and fairness of the system are taken as evaluation indexes, and the binary sparrow algorithm (BSSA) and binary bat algorithm (BBA) are compared. Simulation results demonstrate that IBSSA can achieve higher system energy efficiency and user fairness than BSSA and BBA, showing that the proposed optimization strategy significantly improves the fairness and energy efficiency of the CIIOT.

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尹德鑫,张达敏,张琳娜,蔡朋宸,秦维娜.认知工业物联网中基于麻雀搜索算法的频谱分配策略[J].数据采集与处理,2022,37(2):371-382

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  • 收稿日期:2021-04-24
  • 最后修改日期:2021-07-07
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  • 在线发布日期: 2022-03-25