认知网络中基于博弈论的联合功率控制与速率分配算法

doi:10.11772/j.issn.1001-9081.2017.06.1521

计算机应用 ›› 2017, Vol. 37 ›› Issue (6): 1521-1526.DOI: 10.11772/j.issn.1001-9081.2017.06.1521

• 网络与通信 • 下一篇

认知网络中基于博弈论的联合功率控制与速率分配算法

朱江, 巴少为, 杜清敏

重庆邮电大学重庆市移动通信重点实验室, 重庆 400065

收稿日期:2016-11-03 修回日期:2016-12-16 出版日期:2017-06-10 发布日期:2017-06-14
通讯作者: 巴少为
作者简介:朱江(1977-),男,湖北荆州人,副教授,博士,主要研究方向:通信理论与技术、信息安全技术;巴少为(1991-),女,湖北天门人,硕士研究生,主要研究方向:认知无线电技术;杜清敏(1990-),女,河北石家庄人,硕士研究生,主要研究方向为:认知无线电技术。
基金资助:
国家自然科学基金资助项目（61102062）；重庆市科委自然科学基金资助项目（cstc2015jcyjA40050）；教育部科学技术研究重点项目（212145）；重庆市教委科学技术研究项目（KJ120530）。

Game-theoretic algorithm for joint power control and rate allocation in cognitive networks

ZHU Jiang, BA Shaowei, DU Qingmin

Chongqing Key Laboratory of Mobile Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Received:2016-11-03 Revised:2016-12-16 Online:2017-06-10 Published:2017-06-14
Supported by:
This work is partially supported by the National Natural Science Foundation of China (61102062), the Natural Science Foundation of Chongqing Science and Technology Commission (cstc2015jcyjA40050), the Key Science and Technology Research Project of the Education Ministry (212145), the Science and Technology Research Project of Chongqing Municipal Education Commission (KJ120530).

摘要/Abstract

摘要： 针对认知无线网络上行链路中的资源分配问题，提出了一种适应于多小区认知无线网络的基于功率控制与速率分配的博弈算法。为了更加合理地控制用户的功率和速率，减小各次用户间的干扰，首先，在效用函数中分别给功率和速率设置了不同的代价因子，使其能够更加合理地控制用户，避免用户过度增加发射功率。其次，从理论上证明了该算法纳什均衡的存在性、唯一性以及算法的收敛性。最后，为了解决发射功率和传输速率的最优化问题，给出了联合功率控制和速率分配的迭代更新算法流程图。理论分析及仿真结果表明，与同类博弈算法相比，在保证通信质量的前提下，所提算法可以使得用户以较小的发射功率获得较大的传输速率和较高的信干噪比（SINR），并且减小了用户间的干扰，提高了次用户系统容量。

关键词: 认知无线电, 博弈论, 多小区, 功率控制, 速率控制

Abstract: Aiming at the resource allocation problem for the uplink in cognitive radio networks, a game-theoretic algorithm for joint power control and rate allocation adapted to multi-cell cognitive radio networks was proposed. To control user's power and rate more reasonably and reduce interference among Secondary Users (SUs), firstly, the different cost factors for power and rate were set respectively, so as to control user more reasonably and avoid user excessively increasing transmission power. Then, the existence and uniqueness of the Nash Equilibrium (NE) for the proposed algorithm were proved, the convergence demonstration of the proposed algorithm was given. Finally, for solving the optimization problem of the transmission power and transmission rate, the iterative updating flowchart of the proposed algorithm for the joint power control and rate allocation was presented. The theoretical analysis and simulation results show that, compared with the similar game algorithms, on the premise of guaranteeing the quality of communication, the proposed algorithm can make user acquire higher transmission rate and higher Signal to Interference plus Noise Ratio (SINR) at lower transmission power, reduce the interference among users, and improve the system capacity of SUs.

Key words: Cognitive Radio (CR), game theory, multi-cell, power control, rate control

中图分类号:

TN929.5

朱江, 巴少为, 杜清敏. 认知网络中基于博弈论的联合功率控制与速率分配算法[J]. 计算机应用, 2017, 37(6): 1521-1526.

ZHU Jiang, BA Shaowei, DU Qingmin. Game-theoretic algorithm for joint power control and rate allocation in cognitive networks[J]. Journal of Computer Applications, 2017, 37(6): 1521-1526.

参考文献

[1] GOODMAN D, MANDAYAM N. Power control for wireless data[J]. IEEE Personal Communications, 2000, 7(2):48-54.
[2] KOSKIE S, GAJIC Z. A Nash game algorithm for SIR-based power control in 3G wireless CDMA networks[J]. IEEE/ACM Transactions on Networking, 2005, 13(5):1017-1026.
[3] 罗荣华,杨震.认知无线电系统中一种新的自适应功率控制算法[J].信号处理,2010,26(8):1257-1262.(LUO R H, YANG Z. A novel adaptive power control algorithm in cognitive radio system[J]. Signal Processing, 2010, 26(8):1257-1262.)
[4] KANF X, ZHANG R, MOTANI M. Price-based resource allocation for spectrum-sharing femtocell networks:a Stackelberg game approach[J]. IEEE Journal on Selected Areas in Communications, 2012, 30(3):538-549.
[5] XIE X Z, YANG H L, VASILAKOS A V, et al. Fair power control using game theory with pricing scheme in cognitive radio networks[J]. Journal of Communications and Networks, 2014, 16(2):183-192.
[6] YANG H L, XIE X Z, VASILAKOS A V. Stackelberg game based power control with outage probability constraints for cognitive radio networks[J/OL]. International Journal of Distributed Sensor Networks, 2015:Article ID 604915.[2016-10-09]. http://or.nsfc.gov.cn/bitstream/00001903-5/327951/1/1000013968317.pdf.
[7] TREUST M L, LASAULCE S. A repeated game formulation of energy-efficient decentralized power control[J]. IEEE Transactions on Wireless Communications, 2010, 9(9):2860-2869.
[8] 马良,朱琦.基于干扰管理的功率速率联合控制博弈方法[J].信号处理,2012,28(1):26-32.(MA L, ZHU Q. A game-theoretic joint rate and power control based on interference management[J]. Signal Processing, 2012, 28(1):26-32)
[9] 贺刚,柏鹏,彭卫东,等.数据链中基于动态博弈的联合功率与速率控制[J].西南交通大学学报,2013,48(3):473-480.(HE G, BAI P, PENG W D, et al. Joint rate and power control based on dynamic game theory in data link system[J]. Journal of Southwest Jiaotong University, 2013, 48(3):473-480)
[10] BAGAYOKO A, FIJALKOW I, TORTELIER P. Power control of spectrum-sharing in fading environment with partial channel state information[J]. IEEE Transactions on Signal Processing, 2011, 59(5):2244-2256.
[11] JAVAN M R, SHARAFAT A R. Efficient and distributed SINR-based joint resource allocation and base station assignment in wireless CDMA networks[J]. IEEE Transactions on Communications, 2011, 59(12):3388-3399.
[12] SHASHIKA MANOSHA K B, RAJATHEVA N. Joint power and rate control for spectrum underlay in cognitive radio networks with a novel pricing scheme[C]//Proceedings of the 2010 IEEE 72nd Vehicular Technology Conference Fall. Piscataway, NJ:IEEE, 2010:1-5.
[13] 余翔,张小银.非合作博弈下功率与速率联合控制算法研究[J].重庆邮电大学学报(自然科学版),2016,28(3):349-353.(YU X, ZHANG X Y. Non-cooperative game of joint power and rate control algorithm[J]. Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition), 2016, 28(3):349-353.)
[14] FUDENBERG D, TIROEL J. Game Theory[M]. Cambridge, MA:MIT Press, 1991:841-846.
[15] YATES R D. A framework for uplink power control in cellular radio systems[J]. IEEE Journal on Selected Areas in Communications, 2006, 13(7):1341-1347.
[16] 郭艳艳,昌厚峰,贾鹤萍.基于公共DF中继的认知无线电中继选择和功率分配[J].测试技术学报,2015,29(2):105-110.(GUO Y Y, CHANG H F, JIA H P. Optimal relay selection and power allocation of cognitive networks based on public DF relay[J]. Journal of Test and Measurement Technology, 2015, 29(2):105-110.)
[17] 李鹏,朱宇.一种异构网络中的斯坦克尔伯格功率控制方法[J].太赫兹科学与电子信息学报,2013,11(3):368-376.(LI P, ZHU Y. A Stackelberg approach on power control in heterogeneous networks[J]. Journal of Terahertz Science and Electronic Information Technology, 2013,11(3):368-376).

认知网络中基于博弈论的联合功率控制与速率分配算法

Game-theoretic algorithm for joint power control and rate allocation in cognitive networks

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