无线网络中基于图型演化博弈的动态频谱接入机制

doi:10.11959/j.issn.1000-436x.2015209

Abstract

Abstract:

In order to realize efficient data transmission for users in radio networks,a dynamic spectrum access mechanism based on graphical evolutionary game was proposed for the bounded rationality characteristic of users,while graphical game can better reflect the actual game relationship among users.Meanwhile,a dynamic spectrum access algorithm and corresponding dynamic equation were designed for the mechanism to reduce the complexity of the game,and could converge to Nash equilibrium with faster speed and obtain higher system throughput and utility.Theoretical analysis showed that the dynamic equation was globally asymptotically stable,which illustrated that when user deviated because of bounded rationality and it was still able to guarantee faster converge and fewer performance deviation.Simulation comparison verifies the superiority above.

Key words: dynamic spectrum access mechanism, graphical evolutionary game, dynamic equation, Nash equilibrium

Fang-wei LI,Ying-hui YUAN,Jiang ZHU. Dynamic spectrum access mechanism based on graphical evolutionary game in radio networks[J]. Journal on Communications, 2015, 36(7): 1-9.

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References 19

[1]	FENG D Q , JIANG C Z , LIM G , et al. A survey of energy-efficient wireless communications[J]. IEEE Communications Surveys ＆ Tutorials, 2013,15(1): 167-178.
[2]	HAN Z , NIYATO D , SAAD W , et al. Game Theory in Wireless and Communication Networks[M]. Cambridge University Press, 2012:55-251.
[3]	谢识予 . 有限理性条件下的进化博弈理论[J]. 上海财经大学学报, 2001,3(5): 3-9. XIE S Y . Evolutionary game theory under the condition of bounded ration[J]. Journal of Shanghai University of Finance and Economics, 2001,3(5): 3-9.
[4]	YANG L , KIM H , ZHANG J S , et al. Pricing-based decentralized spectrum access control in cognitive radio networks[J]. IEEE/ACM Transactions on Networking (TON), 2013,21(2): 522-535.
[5]	黄丽亚, 刘臣, 王锁萍 . 改进的认知无线电频谱共享博弈模型[J]. 通信学报, 2010,31(2): 136-140. HUANG L Y , LIU C , WANG S P . Improved spectrum sharing model in cognitive radios based on game theory[J]. Journal on Communications. 2010,31(2): 136-140.
[6]	XU Y H , WANG J L , WU Q H , et al. Opportunistic spectrum access in cognitive radio networks:global optimization using local interaction games[J]. IEEE Journal of Selected Topics in Signal Processing, 2012,6(2): 180-194.
[7]	FANG H , XU L , HUANG C . Dynamic opportunistic spectrum access of multi-channel multi-radio based on game theory in wireless cognitive network[A]. 2013 IEEE Ninth International Conference on Mobile Ad-hoc and Sensor Networks (MSN)[C]. Dalian,China, 2013. 127-132.
[8]	WEIBULL J W . Evolutionary game theory[M]. MIT Press, 1997.
[9]	SANDHOLM W H . Evolutionary game theory[A]. Computational Complexity:Theory,Techniques,and Applications[C]. 2012. 1000-1029.
[10]	JIANG C X , CHEN Y , GAO Y , et al. Joint spectrum sensing and access evolutionary game in cognitive radio networks[J]. IEEE Transactions on Wireless Communication, 2013,12(5): 1-14.
[11]	ZHAO S S , ZHU Q , ZHU H B . Evolutionary game theoretical approach to dynamic spectrum sharing[J]. Journal of Computational Information Systems, 2012,8(10): 4225-4232.
[12]	XU Y H , WU Q H , WANG J L , et al. Opportunistic spectrum access using partially overlapping channels:graphical game and uncoupled learning[J]. IEEE Transactions on Communications, 2013,61(9): 1-13.
[13]	LI H S , HAN Z . Competitive spectrum access in cognitive radio networks:graphical game and learning[A]. 2010 IEEE Wireless Communications and Networking Conference (WCNC)[C]. Sydney,NSW, 2010. 1-6.
[14]	XU Y H , WU Q H , WANG J L , et al. Social welfare maximization for SRSNs using bio-inspired community cooperation mechanism[J]. Chinese Science Bulletin, 2012,57(1): 125-131.
[15]	SHENKER S . Fundamental design issues for the future Internet[J]. IEEE Journal on Selected Areas in Communications, 1995,13(7): 1176-1188.
[16]	SANDHOLM W H . Potential games with continuous player sets[J]. Journal of Economic Theory, 2001,97(1): 81-108.
[17]	NARENDRA K S , ANNASWAMY A M . Stable Adaptive Systems[M]. Courier Dover Publications, 2012.
[18]	BARTH D , BOUMEZ O , BOUSSATO O , et al. A dynamic approach for load balancing[A]. Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools[C]. Pisa,Italy, 2009. 60.
[19]	WU D P , NEGI R . Effective capacity channel model for frequency-selective fading channels[J]. Wireless Networks, 2006,13(3): 299-310.

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算法	加减运算	乘除运算	比较运算
所提机制	8M	ND_i	M?1
ODEGEG	13M	NMD_i	M
ODENGEG	20M	N ²M	M

Dynamic spectrum access mechanism based on graphical evolutionary game in radio networks

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