北京邮电大学学报

  • EI核心期刊

北京邮电大学学报

• •    

具有自适应用户选择的CR-IoT网络的性能分析

代阿飞,李恩玉,王荣钰,张悦,张瑞轩   

  1. 青岛理工大学
  • 收稿日期:2024-05-22 修回日期:2024-07-01 发布日期:2024-11-22
  • 通讯作者: 李恩玉
  • 基金资助:
    山东省自然科学基金;大学生创新创业训练计划项目

Performance analysis of CR-IoT network with adaptive user selection

  • Received:2024-05-22 Revised:2024-07-01 Published:2024-11-22
  • Contact: En-Yu LI

摘要: 为了提高无线通信系统的能效和可靠性,在下垫式频谱共享机制的基础上,针对能量受限的认知物联网用户协助远端用户实现其信息和自身数据上传的系统,研究了认知物联网用户的选择策略以及用户传输距离优化问题。在该模型中,能量受限的认知物联网协作用户采用功率分割协议进行能量收集,并考虑实际能量收集过程满足非线性的特性,提出了一种发射功率受限条件下的主动机会认知用户的选择策略,分析了该模型采用所提用户选择策略的中断性能,应用高斯-切比雪夫近似积分公式得到了中断概率的闭式结果,并进一步给出了高信噪比下中断概率的近似逼近结果。为了使得系统中断概率最小以及协作认知用户的传输距离最大,给出了功率分割因子和信号功率分配因子的联合优化分配方案。最后通过蒙特卡洛仿真验证了理论推导的准确性和所提策略的性能优势。

关键词: 非线性能量收集, 用户选择策略, 物联网, 认知无线电

Abstract: In order to improve the energy efficiency and reliability of wireless communication system, based on the underlying spectrum sharing mechanism, the selection strategy of the cognitive radio-internet of things (CR-IoT) users and the user transmission distance optimization problem are studied for the system where the energy-constrained CR-IoT users assist remote users to upload the information and their data. In this model, the CR-IoT cooperative users adopt the power splitting protocol for energy harvesting (EH). Considering the nonlinear characteristics of the actual energy harvesting process, a selection strategy of active opportunistic cognitive users under limited transmission power is proposed. The outage probability (OP) of the proposed user selection strategy is analyzed. The closed-form result of OP is obtained by using the Gauss-Chebyshev approximate integral formula, and the approximate result of OP under high signal-to-noise ratio (SNR) is further derived. To minimize the OP and maximize the transmission distance of cooperative cognitive users, a joint optimal allocation scheme of power splitting factor and signal power allocation factor is proposed. Finally, the accuracy of the theoretical derivation and the performance advantages of the proposed strategy are verified by Monte Carlo simulation.

Key words: nonlinear energy harvesting, user selection strategy, internet of things, cognitive radio

中图分类号: