基于认知无线电的新型非合作功率控制博弈算法

doi:10.3969/j.issn.1000-436x.2012.z2.012

通信学报 ›› 2012, Vol. 33 ›› Issue (Z2): 97-103.doi: 10.3969/j.issn.1000-436x.2012.z2.012

基于认知无线电的新型非合作功率控制博弈算法

赵军辉,杨涛,张雪雪

北京交通大学电子信息工程学院，北京 100044

出版日期:2012-11-25 发布日期:2017-08-03
基金资助:
国家自然科学基金资助项目;北京交通大学轨道交通控制与安全国家重点实验室自主研究课题基金资助项目;中央高校基本科研业务费专项基金资助项目

Novel non-cooperative power control game algorithm for cognitive radio

Jun-hui ZHAO,Tao YANG,Xue-xue ZHANG

School of Electronic and Information Engineering,Beijing Jiaotong University,Beijing 100044,China

Online:2012-11-25 Published:2017-08-03
Supported by:
The National Natural Science Foundation of China;The State Key Laboratory of Rail Traffic Control and Safety of Beijing Jiaotong University;The Fundamental Research Funds for the Central Universities of Ministry of Education of China

摘要/Abstract

摘要：

从认知无线电技术特性出发，在干扰温度门限的限制条件下，提出了基于新的代价函数功率控制博弈论算法，以有效地提高认知用户的信干噪比。根据信道状况、吞吐量最大化和功率限制的需求，将功率控制问题转化为一个干扰受限的多约束非线性规划问题。结合博弈论和最优化理论，证明了其纳什均衡的存在性和唯一性，给出了该模型的分布式求解算法。仿真实验表明，该算法可以有效提高认知用户的QoS和系统性能，充分利用无线资源。

关键词: 认知无线电, 功率控制, 价格函数, 纳什均衡

Abstract:

A novel non-cooperative power control algorithm based on new pricing function and the characteristics of cognitive radio technology was proposed with the interference temperature constrain,in order to improve signal to interference plus noise ratio of CR.The problem of power control was changed into the problem of multi-restraints non-linear optimization with interference limits based on channel conditions,maximal network and power limits.The existence and unique of nash equilibrium(NE)in utility function by the principle of game theory and optimization were proved and a distributed algorithm for this game was proposed.Simulation results show that the proposed algorithm can improve users QoS(quality of serves),system performance effectively and improve radio resource efficiency.

Key words: cognitive radio, power control, pricing function, Nash equilibrium

赵军辉,杨涛,张雪雪. 基于认知无线电的新型非合作功率控制博弈算法[J]. 通信学报, 2012, 33(Z2): 97-103.

Jun-hui ZHAO,Tao YANG,Xue-xue ZHANG. Novel non-cooperative power control game algorithm for cognitive radio[J]. Journal on Communications, 2012, 33(Z2): 97-103.

图/表 3

参考文献 13

[1]	MITOLA J . Cognitive radio for flexible mobile multimedia communications[A]. 1999 IEEE International Workshop on Mobile Multimedia Communications[C]. San Diego,CA,USA, 1999. 3-10.
[2]	MITOLA J , MAGUIRE G Q . Cognitive radio:making software radios more personal[J]. IEEE Personal Communications, 1999,6(4): 13-18.
[3]	LOTKER Z , PARTER M , PELEG D ,et al. Distributed power control in the SINR model[A]. INFOCOM,Proceedings of IEEE[C]. Shanghai,China, 2011. 2525-2533.
[4]	LI J D , YANG C G , LI W Y ,et al. Pricing based power control game for cognitive radio networks[A]. International Conference on Telecommunications[C]. Marrakech,Morocco, 2009. 270-275.
[5]	林玉清, 王霞 ,等. 认知无线电系统中基于归一化效用函数的功率控制方法[J]. 南京邮电大学学报（自然科学）, 2011,31(1): 39-44. LIN Y Q , WANG X ,et al. Power control based on unitary utility function in cognitive radio system[J]. Journal of Nanjing University of Postsand Telecommunications(Natural Science), 2011,31(1): 39-44.
[6]	LI F , TAN X Z , WANG L . A new game algorithm for power control in cognitive radio networks[J]. IEEE Transactions on Vehicular Technology, 2011,60(9): 4384-4391.
[7]	SARAYDAR C U , MANDAYAM N B , GOODMAN D J . Efficient power control via pricing in wireless data networks[J]. IEEE Transactions on Communications, 2002,50(2): 291-303.
[8]	WANG W , PENG T , WANG W B . Modeling of uplink power control for cognitive radio networks:cooperative and noncooperative[J]. Mathematical and Computer Modelling, 2011,53(11): 2136-2148.
[9]	NADKAR T , THUMAR V , TEJ G P S ,et al. Distributed power allocation for secondary users in a cognitive radio scenario[J]. IEEE Transactions on Wireless Communications, 2012,11(4): 1576-1586.
[10]	张天魁, 曾志民, 张颖莹 ,等. 基于博弈论的OFDMA系统多小区功率协调分配算法[J]. 通信学报, 2008,29(1): 22-29. ZHANG T K , ZENG Z M , ZHANG Y Y ,et al. Multicell adaptive power allocation scheme based on game theory in OFDMA systems[J]. Journal on Communications, 2008,29(1): 22-29.
[11]	弗登博格, 梯若尔 . 博弈论[M]. 北京: 中国人民大学出版社, 2010. DREW F , JEAN T . Game Theory[M]. Beijing: China Renmin University PressPress, 2010.
[12]	WU J M , CHEN C Y . An adjustable fuzzy power control architecture for a multi-rate WCDMA system[A]. Proceedings of the 27th Chinese Control Conference[C]. Kunming,China, 2008. 633-636.
[13]	程世伦, 杨震, 张晖 . 新的认知无线电功率控制博弈算法[J]. 通信学报, 2007,28(3): 100-107. CHENG S L , YANG Z , ZHANG H . Novel power control game algorithm for cognitive radios[J]. Journal on Communications, 2007,28(3): 100-107.

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基于认知无线电的新型非合作功率控制博弈算法

Novel non-cooperative power control game algorithm for cognitive radio

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