Computer Engineering and Applications ›› 2017, Vol. 53 ›› Issue (3): 144-148.DOI: 10.3778/j.issn.1002-8331.1607-0004

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Fair power control based on game theory in cognitive radio networks

WANG Lili1, CHEN Guobin1, ZHANG Guangquan2, 3   

  1. 1.Big Data Research Institute, Rongzhi College, Chongqing Technology and Business University, Chongqing 401320, China
    2.School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215006, China
    3.State Key Laboratory of Computer Science, Chinese Academy of Sciences, Beijing 100080, China
  • Online:2017-02-01 Published:2017-05-11

认知无线电网络中基于公平性的功率控制方案

王莉莉1,陈国彬1,张广泉2,3   

  1. 1.重庆工商大学 融智学院 大数据研究所,重庆 401320
    2.苏州大学 计算机科学与技术学院,江苏 苏州 215006
    3.中国科学院 计算机科学国家重点实验室,北京 100080

Abstract:  For the far-near fairness issue existing in the non-cooperative power control game algorithm, an efficient and unbiased power control algorithm via pricing is given in the uplink of a cognitive radio network where secondary users share the bandwidth with primary users. In this game model, the pricing punishment parameter setting depends on the quality of received signal to guarantee the quality of service requirement of the secondary users. The improved utility function balances the fairness and system throughput of secondary users. The existence of Nash equilibrium point for the proposed game is proven by supermodular game theory and then the iterative process for Nash equilibrium point of the transmit power is given finally. Simulation results show that the proposed game not only enhances the system throughput, reduces transmit power of secondary users, and improves the global utility, but also takes the throughput fairness for far-near secondary users into account.

Key words:  cognitive radio networks, game theory, power control, Nash equilibrium, fairness

摘要: 针对现有非合作功率控制博弈算法中存在用户“远近性公平”问题,在主次用户共享频谱的认知无线电上行链路中,给出一种基于代价函数的高效和公平的功率控制博弈算法。在该博弈模型中,代价函数的设定依据次用户接收端信号质量需满足次用户的服务质量要求。改进后的效用函数能够同时兼顾认知无线电系统的总吞吐量和次用户获取资源的公平性,并利用超模理论证明了该模型存在纳什均衡,然后得到求解发射功率纳什均衡解的迭代过程。仿真结果表明,相比已有的研究,该算法不仅能提高认知系统的吞吐量,还能降低发射功率,改善系统效用,而且兼顾了远近用户吞吐量的公平性。

关键词: 认知无线电网络, 博弈论, 功率控制, 纳什均衡, 公平性