西安电子科技大学学报 ›› 2022, Vol. 49 ›› Issue (3): 83-92.doi: 10.19665/j.issn1001-2400.2022.03.010

• 信息与通信工程 • 上一篇    下一篇

能量收集多天线发送机的功率控制和天线选择

宁晓晗1,2(),雷维嘉1,2()   

  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重点实验室,重庆 400065
  • 收稿日期:2021-05-12 修回日期:2021-12-15 出版日期:2022-06-20 发布日期:2022-07-04
  • 通讯作者: 雷维嘉
  • 作者简介:宁晓晗(1998—),女,重庆邮电大学硕士研究生,E-mail: cheninth@163.com
  • 基金资助:
    国家自然科学基金(61971080);重庆市教委科学技术研究重点项目(KJZD-M201900602)

Power control and antenna selection for themulti-antenna transmitter with energy harvesting

NING Xiaohan1,2(),LEI Weijia1,2()   

  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:2021-05-12 Revised:2021-12-15 Online:2022-06-20 Published:2022-07-04
  • Contact: Weijia LEI

摘要:

针对能量收集多输入单输出无线通信系统传输过程中的速率最大化问题,提出一种基于李雅普诺夫优化框架的在线功率控制和天线选择策略。系统中源节点为能量收集设备供电的多天线节点,且天线激活后的射频电路功耗不可忽略。激活天线数越多,发送天线阵列增益越大,但电路功耗也越大,需要在二者间进行平衡。源节点应根据可用能量和信道状态来选择合适的发送天线和传输功率。由于能量到达和信道衰落是随机过程,该速率最大化问题是一个随机优化问题。由可充电电池的电量构造能量虚队列,而速率的负值作为惩罚项,再利用李雅普诺夫优化框架将功率控制与天线选择的优化问题转换为瞬时队列漂移加惩罚函数最小化问题。每时隙遍历电池电量支持的激活天线数,并优化发送功率,选取使漂移加惩罚最小的天线数和发送功率作为最优解。仿真结果表明,相比3种对比算法,算法能够获得明显更高的传输速率。所提算法仅依据当前的信道状态和电池电量状态做出决策,且计算复杂度低,是一种实用的算法。

关键词: 通信技术, 能量收集, 功率控制, 天线选择, 李雅普诺夫框架

Abstract:

Aiming at the rate maximization in the MISO system with energy harvesting,we propose an online joint power control and antenna selection strategy based on the Lyapunov optimization framework.The source node is a multi-antenna node powered by an energy harvesting device.The power consumption of the radio frequency (RF) circuit for each antenna is not negligible.The more antennas are activated,the larger the gain of the antenna array,but the larger the power consumption of the RF circuit,so it is necessary to balance between the gain and the power consumption.The source node should choose the appropriate transmit antenna and transmit power according to the available energy and the channel state.Since the energy arrival and the channel fading are stochastic processes,the rate maximization problem is a stochastic optimization problem.The energy virtual queue is constructed from the power level of the rechargeable battery,the negative value of the rate is modeled as the penalty term,and then the optimization problem of power control and antenna selection is transformed into the minimization of the instantaneous queue drift-plus-penalty function by using the Lyapunov optimization framework.During each time slot,the corresponding transmit power is optimized for each active antenna number that the power stored in the battery can support,and then the number of active antennas and the transmission power with the minimum drift-plus-penalty are selected as the optimal solution.Simulation results show that compared with the three comparison algorithms,the proposed algorithm can achieve a significantly higher transmission rate.The proposed algorithm only makes decisions based on the current channel state and battery power state,and has a very low computational complexity.

Key words: communication technology, energy harvesting, power control, antenna selection, Lyapunov framework

中图分类号: 

  • TN925