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能量收集通信系统中功率和调制方式的在线联合优化策略
引用本文:雷维嘉,孙嘉琳,谢显中,雷宏江.能量收集通信系统中功率和调制方式的在线联合优化策略[J].电子与信息学报,2022,44(3):1024-1033.
作者姓名:雷维嘉  孙嘉琳  谢显中  雷宏江
作者单位:1.重庆邮电大学通信与信息工程学院 重庆 4000652.移动通信技术重庆市重点实验室 重庆 4000653.重庆邮电大学光电工程学院 重庆 400065
基金项目:重庆市教委科学技术研究重点项目;国家自然科学基金
摘    要:针对源节点配备能量收集装置的点对点能量收集无线通信系统,该文以最大化长期平均传输速率为目标,提出一种基于Lyapunov优化框架的在线功率控制和自适应调制联合优化策略.由于能量到达和信道状态的随机性,优化问题是一个随机优化问题.利用Lyapunov优化框架将电池操作和可用能量约束下的长期时间优化问题转化为每时隙以虚队列...

关 键 词:能量收集  功率控制  自适应调制  Lyapunov优化
收稿时间:2021-02-18

Online Joint Optimization of Power and Modulation in Energy Harvesting Communication Systems
LEI Weijia,SUN Jialin,XIE Xianzhong,LEI Hongjiang.Online Joint Optimization of Power and Modulation in Energy Harvesting Communication Systems[J].Journal of Electronics & Information Technology,2022,44(3):1024-1033.
Authors:LEI Weijia  SUN Jialin  XIE Xianzhong  LEI Hongjiang
Institution:1.School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China2.Chongqing Key Laboratory of Mobile Communications Technology, Chongqing 400065, China3.School of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Abstract:For a point-to-point energy harvesting wireless communication system equipped with energy harvesting devices at the source node, to maximize the long-term average transmission rate, an online power control and adaptive modulation joint optimization strategy based on Lyapunov optimization framework is proposed. Due to the randomness of the energy arrival and the channel state, the optimization problem is a stochastic optimization problem. By using Lyapunov optimization framework, the long-term optimization problem under the constraints of battery operation and available energy is transformed into a joint optimization problem of the transmission power, the modulation mode and the frame length to minimize the virtual queue drift-plus-penalty" per time slot. The proposed algorithm only dependes on the current channel state and the battery state. The simulation results show that the proposed algorithm can effectively utilize the harvested energy and adapt to the channel changes. The long-term average actual achievable information transmission rate is significantly better than the greedy and the half-power algorithm. Compared with the offline water filling algorithm and other comparison algorithms, both which aim at maximizing the channel capacity, the proposed algorithm also can achieve a higher actual transmission rate.
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