北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2017, Vol. 40 ›› Issue (6): 103-108.doi: 10.13190/j.jbupt.2017-074

• 研究报告 • 上一篇    下一篇

混合供电发射机的能量调度和自适应功率算法

刘迪迪1,2, 马丽纳1, Frank Jiang1   

  1. 1. 广西师范大学 电子工程学院, 桂林 541004;
    2. 西安电子科技大学 通信工程学院, 西安 710071
  • 发布日期:2017-12-28
  • 作者简介:刘迪迪(1980-),女,副教授;Frank Jiang (1974-),男,教授,博士,E-mail:fjiang@gxnu.edu.cn.
  • 基金资助:
    国家自然科学基金项目(61361011);广西教育厅项目(2017KY0074);广西师范大学重点科研项目(2016ZD008)

Energy Scheduling and Adaptive Transmission Power Algorithm for a Transmitter with Hybrid Energy Sources

LIU Di-di1,2, MA Li-na1, Frank Jiang1   

  1. 1. College of Electronic Engineering, Guangxi Normal University, Guilin 541004, China;
    2. School of Telecommunications Engineering, Xidian University, Xi'an 710071, China
  • Published:2017-12-28

摘要: 针对混合供电的点到点无线通信链路,讨论了能量收集过程、数据到达过程以及衰落信道统计分布均未知情况下发射机的能量调度和自适应发送功率问题,目的是在保证通信系统一定性能的要求下最小化传统电网的能耗,即有效利用可再生能源的能量.基于Lyapunov优化提出一种低复杂度动态算法,理论证明了该算法可使优化目标无限趋于最优,同时保证最大数据时延不超过用户要求.仿真结果表明,提出的算法在性能和数据时延上都优于其他2种贪婪算法.

关键词: 能量收集, 能量调度, 自适应功率, 混合电源, Lyapunov优化

Abstract: The problems of energy scheduling and adaptive transmission power were explored for a point to point wireless communication link, where, the transmitter is driven by hybrid energy sources. The problems are further constrained by the unknown information including 1) the energy harvesting process, 2) time-varying channel condition as well as 3) the statistics of dynamic/opportunistic data arrivals. To minimize the time average energy consumption from power grid over subject to a certain communication performance, i.e., utilizing efficiently the harvested energy, a new dynamic algorithm with low complexity was proposed based on Lyapunov optimization. Analysis shows that the proposed algorithm performs arbitrarily close to the optimal objective value, meanwhile ensures that the maximum time delay of the data queue would tolerate the data packets aggregated from the users' requirements. Simulations demonstrates that the proposed algorithm not only outperforms but also has smaller time delay than the other two greedy algorithms.

Key words: energy harvesting, energy scheduling, adaptive transmission power, hybrid energy sources, Lyapunov optimization

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