北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2021, Vol. 44 ›› Issue (5): 74-80.doi: 10.13190/j.jbupt.2020-275

• 论文 • 上一篇    下一篇

非线性电池模型下能量收集通信系统功率控制

陈海林, 雷维嘉   

  1. 1. 重庆邮电大学 通信与信息工程学院, 重庆 400065;
    2. 重庆邮电大学 移动通信技术重庆市市级重点实验室, 重庆 400065
  • 收稿日期:2020-12-30 出版日期:2021-10-28 发布日期:2021-09-06
  • 通讯作者: 雷维嘉(1969-),男,教授,硕士生导师,E-mail:leiwj@cqupt.edu.cn. E-mail:leiwj@cqupt.edu.cn
  • 作者简介:陈海林(1992-),女,硕士生.
  • 基金资助:
    国家自然科学基金项目(61971080)

Power Control Algorithm under Nonlinear Battery Model in Communication Systems with Energy Harvesting

CHEN Hai-lin, LEI Wei-jia   

  1. 1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;
    2. Chongqing Key Lab of Mobile Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Received:2020-12-30 Online:2021-10-28 Published:2021-09-06

摘要: 针对发送端配备能量收集设备的无线通信系统,基于Lyapunov优化框架,提出了一种以最大化长期平均传输速率为目标的在线功率控制策略.功率决策算法中考虑了可充电电池充放电过程中的能量损失,采用非线性数学模型来描述充放电效率.将电池电量的约束条件转为能量虚队列的稳定性要求,将需要最大化的传输速率的相反数作为惩罚项,在仅拥有当前信道状态和电池状态的条件下,通过使漂移加惩罚最小化,在满足约束条件的同时最大化平均传输速率.仿真结果显示,所提算法的性能略低于离线注水算法,优于贪婪算法和半功率算法,也优于同样采用Lyapunov方法、但没有考虑充放电效率的现有其他算法.

关键词: 能量收集, Lyapunov优化框架, 在线功率控制, 充放电效率

Abstract: Based on Lyapunov optimization framework,an online power control scheme is proposed to maximize the long-term average transmission rate for wireless communication systems with energy harvesting devices at the transmitter. The power control algorithm takes into account the energy loss in the charging and discharging processes of the rechargeable battery,and uses a nonlinear mathematical model to describe the charging and discharging efficiency. The constraint condition of battery power is transformed into the stable requirement for the energy virtual queue,and the negative value of the transmission rate that needs to be maximized is taken as the penalty term. Based on the current channel state and battery energy state,the average transmission rate is maximized by minimizing the drift-plus-penalty under the constraint of the harvested energy. Simulation results show that the performance of the proposed algorithm is slightly lower than that of the off-line water-filling algorithm,but is much better than those of the greedy algorithm and the half-power algorithm. In addition, the proposed algorithm also outperforms the existing algorithm that adopts Lyapunov method without considering the chargeing and discharging efficiency.

Key words: energy harvesting, Lyapunov optimization framework, online power control, charging/discharging efficiency

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