北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2013, Vol. 36 ›› Issue (6): 93-97.doi: 10.13190/j.jbupt.2013.06.020

• 研究报告 • 上一篇    下一篇

多基站协作通信系统容量最大化的功率分配方案

肖海林, 王鹏, 欧阳缮, 李民政   

  1. 桂林电子科技大学 信息与通信学院, 桂林 541004
  • 收稿日期:2013-03-12 出版日期:2013-12-31 发布日期:2013-10-08
  • 作者简介:肖海林(1976—),男,博士,教授,E-mail:xhl_xiaohailin@163.com.
  • 基金资助:

    国家自然科学基金项目(61261018,61362007);广西自然科学基金重点项目(2011GXNSFD018028);广西无线宽带通信与信号处理重点实验室2012 年度主任基金项目(12111)

Power Allocation Scheme Based on System Capacity Maximization for Multi-Base Station Cooperative Communication

XIAO Hai-lin, WANG Peng, OUYANG Shan, LI Min-zheng   

  1. School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China
  • Received:2013-03-12 Online:2013-12-31 Published:2013-10-08

摘要:

将多基站协作通信的功率分配问题转换为最大化系统容量问题,通过设置路径损耗门限为各用户判决与其通信的协作基站,并以最大化系统容量为目标,分别给出基于遗传算法和基于粒子群优化算法的多基站协作通信功率分配方案. 数值分析表明,当用户数量为100时,相对于多基站协作通信等功率分配方案,所提出的2种功率分配方案分别提高系统容量5.25 bit·s-1·Hz-1和7.38 bit·s-1·Hz-1. 另外,基于粒子群优化算法的功率分配方案在算法性能上优于基于遗传算法的功率分配方案.

关键词: 协作通信, 遗传算法, 功率分配, 粒子群优化算法

Abstract:

Power allocation was formulated as the system capacity maximization problem and a strategy to solve the problem in its equivalent form was proposed. Based on genetic algorithm and particle swarm optimization, the path loss threshold to select the cooperative base stations for each user and maximize system capacity was set by the proposed power allocation strategy. Numerical results show that when the number of mobile users is 100, the proposed power allocation strategies based on genetic algorithm and particle swarm optimization will increase system capacity about 5.25 bit·s-1·Hz-1 and 7.38 bit·s-1·Hz-1 in the same conditions of adopting equal power allocation of multi-base cooperative communication system, respectively. Moreover, the algorithm performance of power allocation strategy based on particle swarm optimization is better than the power allocation strategy based on genetic algorithm.

Key words: cooperative communication, genetic algorithm, power allocation, particle swarm optimization

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