认知无线电中联合功率控制的动态频谱分配算法研究
|
摘要
随着无线通信业务需求的持续增长,有限的频谱资源与日益增长的频谱需求之间的矛盾已经成为制约无线通信发展的瓶颈。认知无线电作为一种频谱共享技术,通过对周围无线环境的感知、学习和分析,对搜索到的可用频谱机会式动态接入,从而实现对有限频谱资源的高效利用,缓解频谱紧缺的现状。而合适的动态频谱分配算法决定了无线频谱的使用效率,对认知无线电网络的性能起着关键性作用。
本文针对认知无线电网络中的动态频谱分配算法展开研究。由于在动态频谱分配过程中,存在多个认知用户同时占用同一频段的情况,不可避免会引入相互干扰,采用功率控制机制可以避免此问题。合理的功率控制不仅可以在扩大认知用户通信范围和减小通信干扰之间取得平衡,而且可以减少终端能耗。本文拟在动态频谱分配中联合功率控制机制来减小同频用户间干扰,从而提高频谱利用率。
主要研究内容包括:
1)首先简要介绍了认知无线电的背景和相关知识,然后详细阐述了动态频谱分配和功率控制技术,重点分析了功率控制在动态频谱分配过程中的重要作用,最后分析了常用的分配模型,着重研究基于图论的分配模型。
2)针对认知无线电网络的特点,在图论理论基础上,深入研究了多个用户使用同一信道时的干扰图模型,比较分析了基于图论模型的多种频谱分配算法的特点和性能。
3)针对频谱分配算法所要达到系统性能高、收敛性能快和公平性好的目的,以随机分布式的认知网络为研究对象,提出联合功率控制的动态频谱分配算法。算法通过联合功率控制机制,减少了接入相同信道的认知用户间的综合干扰使得多个用户可以同时使用同一信道,同时以最大独立集为分配起点,允许同时分配信道给互不干扰的多个用户,从而有效减少分配总次数和用户间信息交互量,有利于算法的快速收敛。最后考虑到用户需求和历史分配信息对算法的影响,提出基于需求和历史信息的频谱分配算法,引入用户优先级和信道优先级的概念使得算法更加满足公平性要求。仿真结果验证了联合功率控制的动态频谱分配算法较无功率控制下的动态频谱分配算法性能有所提高,并证明了改进算法在系统效益、公平性和收敛性能等方面的有效性。
With the sustained growth of wireless communication services,the confliction of the limited radio spectrum resources and the increased radio spectrum demand hampers the development of wireless communication. Cognitive radio as a new spectrum share technology can opportunistically access and utilize the searched available spectrum by interacting with the environment, so then improve the utilization of spectrum resources and ease the shortage of spectrum resources. Specifically, dynamic spectrum allocation algorithm produces an effect on utilization of wireless spectrum, also play a crucial role to the performance of cognitive radio networks.
This paper focuses on dynamic spectrum allocation algorithms in Cognitive Radio Networks. During the allocation, several cognitive users can simultaneously utilize the same channel which will inevitably lead to interference between users, the power control mechanism can be introduced to avoid this problem. Reasonable power control mechanism can not only acquire balance between enlarging communication area and reducing communication interference, but also cut down energy expenditure of terminals.
The paper designs joint power control in dynamic spectrum allocation to reduce interference between users, thereby improve spectrum efficiency. The main contents include:
1) Firstly, the background and basis concept of cognitive radio was introduced, then dynamic spectrum allocation algorithms and power control technology were expounded, especially the important role of power control mechanism during spectrum allocation was analyzed, finally existing allocation models specially the graph based model were illustrated.
2) In order to fit characters of cognitive radio, based on graph theory, the interference graph model when several cognitive users simultaneously utilize the same channel was studied, further more, characters and performance of some spectrum allocation algorithms were compared and analyzed.
3) For the sake of high system performance, fast convergence performance and well fairness, under stochastic distributed network environment, an improved dynamic spectrum allocation algorithm of joint power control mechanism was proposed. Joint power control mechanism can avoid interference between users that access the same channel, this in turn, meet more users’transmission requirements. At the same time, allocation begins with the maximal independent set (MIS) that allows assigning a particular channel simultaneously to a set of links with no interference between each other which can cut back the number of allocation and reduce information exchange among users so that it can enable fast convergence. In the end, the influence of user require and history information were analyzed, and an dynamic spectrum allocation algorithm based on demand and historical information was presented, by introducing user priority and channel priority to meet fairness ulteriorly. Simulation results show that the performance of dynamic spectrum allocation algorithm of joint power control is much better than that of dynamic spectrum allocation algorithm without power control, simultaneously confirm the validity of the improved algorithm in system performance, fairness and convergence performance.
本文针对认知无线电网络中的动态频谱分配算法展开研究。由于在动态频谱分配过程中,存在多个认知用户同时占用同一频段的情况,不可避免会引入相互干扰,采用功率控制机制可以避免此问题。合理的功率控制不仅可以在扩大认知用户通信范围和减小通信干扰之间取得平衡,而且可以减少终端能耗。本文拟在动态频谱分配中联合功率控制机制来减小同频用户间干扰,从而提高频谱利用率。
主要研究内容包括:
1)首先简要介绍了认知无线电的背景和相关知识,然后详细阐述了动态频谱分配和功率控制技术,重点分析了功率控制在动态频谱分配过程中的重要作用,最后分析了常用的分配模型,着重研究基于图论的分配模型。
2)针对认知无线电网络的特点,在图论理论基础上,深入研究了多个用户使用同一信道时的干扰图模型,比较分析了基于图论模型的多种频谱分配算法的特点和性能。
3)针对频谱分配算法所要达到系统性能高、收敛性能快和公平性好的目的,以随机分布式的认知网络为研究对象,提出联合功率控制的动态频谱分配算法。算法通过联合功率控制机制,减少了接入相同信道的认知用户间的综合干扰使得多个用户可以同时使用同一信道,同时以最大独立集为分配起点,允许同时分配信道给互不干扰的多个用户,从而有效减少分配总次数和用户间信息交互量,有利于算法的快速收敛。最后考虑到用户需求和历史分配信息对算法的影响,提出基于需求和历史信息的频谱分配算法,引入用户优先级和信道优先级的概念使得算法更加满足公平性要求。仿真结果验证了联合功率控制的动态频谱分配算法较无功率控制下的动态频谱分配算法性能有所提高,并证明了改进算法在系统效益、公平性和收敛性能等方面的有效性。
With the sustained growth of wireless communication services,the confliction of the limited radio spectrum resources and the increased radio spectrum demand hampers the development of wireless communication. Cognitive radio as a new spectrum share technology can opportunistically access and utilize the searched available spectrum by interacting with the environment, so then improve the utilization of spectrum resources and ease the shortage of spectrum resources. Specifically, dynamic spectrum allocation algorithm produces an effect on utilization of wireless spectrum, also play a crucial role to the performance of cognitive radio networks.
This paper focuses on dynamic spectrum allocation algorithms in Cognitive Radio Networks. During the allocation, several cognitive users can simultaneously utilize the same channel which will inevitably lead to interference between users, the power control mechanism can be introduced to avoid this problem. Reasonable power control mechanism can not only acquire balance between enlarging communication area and reducing communication interference, but also cut down energy expenditure of terminals.
The paper designs joint power control in dynamic spectrum allocation to reduce interference between users, thereby improve spectrum efficiency. The main contents include:
1) Firstly, the background and basis concept of cognitive radio was introduced, then dynamic spectrum allocation algorithms and power control technology were expounded, especially the important role of power control mechanism during spectrum allocation was analyzed, finally existing allocation models specially the graph based model were illustrated.
2) In order to fit characters of cognitive radio, based on graph theory, the interference graph model when several cognitive users simultaneously utilize the same channel was studied, further more, characters and performance of some spectrum allocation algorithms were compared and analyzed.
3) For the sake of high system performance, fast convergence performance and well fairness, under stochastic distributed network environment, an improved dynamic spectrum allocation algorithm of joint power control mechanism was proposed. Joint power control mechanism can avoid interference between users that access the same channel, this in turn, meet more users’transmission requirements. At the same time, allocation begins with the maximal independent set (MIS) that allows assigning a particular channel simultaneously to a set of links with no interference between each other which can cut back the number of allocation and reduce information exchange among users so that it can enable fast convergence. In the end, the influence of user require and history information were analyzed, and an dynamic spectrum allocation algorithm based on demand and historical information was presented, by introducing user priority and channel priority to meet fairness ulteriorly. Simulation results show that the performance of dynamic spectrum allocation algorithm of joint power control is much better than that of dynamic spectrum allocation algorithm without power control, simultaneously confirm the validity of the improved algorithm in system performance, fairness and convergence performance.
引文
[1] Tuttlebee W.. Software Defined Radio: Origins, Drivers and International Perspectives[M]. New York: Wiley, 2002.
[2] Capar F., Weiss T., etc. Analysis of Coexistence Strategies for Cellular and Wireless Local Area Networks[C]. Vehicular Technology Conference. October 2003.
[3] Federal Communications Commission. Spectrum Policy Task Force Report[R]. ET Docket No. 02-135, Nov. 2002.
[4] Mitola J., Maguire G.. Cognitive radio: Making software radios more personal[J]. IEEE Personal Communications Magazine. 1999, 6(4):13-18.
[5] Vuran M.C., Akyildiz I.F.. A-MAC: Adaptive Medium Access Control for Next Generation Wireless Terminals[J]. IEEE/ACM transactions on networking. 2007,15(3):574-587.
[6] Stevenson C.R., Cordeiro C., etc. Functional Requirements for the 802.22 WRAN Standard. IEEE doc.: IEEE 802.22-05/0007r40. Sept.2005.
[7] A.T. Hoang, Y.C. Liang. A Two-Phase Channel and Power Allocation Scheme for Cognitive Radio Networks[C]. Personal,Indoor and Mobile Radio Communications. Sept. 2006.
[8] Hoang A.T., Liang Y.C.. Downlink Channel Assignment and Power Control for Cognitive Radio Networks[J]. IEEE transactions on wireless communications. 2008,7(8):3106-3117.
[9] Hoang A.T., Liang Y.C.. Maximizing spectrum utilization of Cognitive radio networks using channel allocation and power control[C]. Vehicular Technology Conference. Sept. 2006.
[10] Behzad A., Rubin I.. Multiple Access Protocol for Power-Controlled Wireless Access Nets[J]. IEEE Transactions on Mobile Computing. 2004,3(4):307–316.
[11] Bambos N., Chen S.C., etc. Radio link admission algorithms for wireless networks with power control and active link quality protection[J]. Fourteenth Annual Joint Conference of the IEEE Computer and Communications Societies. 1995,1:97-104.
[12] Mitra D.. An asynchronous distributed algorithm for power control in Cellular radio systems. in Proceedings of 4th WINLAB Workshop on Third Generation Wireless Information Networks. Rutgers University ,NewBrunswick,NJ. Oct.1993.
[13] Zheng H., Peng C.. Collaboration and fairness in opportunistic spectrum access[C]. Proc. of the 2005 IEEE Int’l Conf. on Communications. IEEE Communications Society Press. 2005.
[14] Peng C, Zheng H, Zhao BY. Utilization and fairness in spectrum assignment for opportunistic spectrum access[J]. Mobile Networks and Applications. 2006, 11(4):555?576.
[15] Zhao J, Zheng H, Yang G. Distributed coordination in dynamic spectrum allocationnetworks[C]. Proc. of the 2005 1st IEEE Int’l Symp on New Frontiers in Dynamic Spectrum Access Networks(DySPAN 2005). Baltimore: IEEE Press, 2005,259?268.
[16]陈劫,李少谦,廖楚林.认知无线电网络中基于需求的频谱资源分配算法研究[J].计算机应用,2008,28(9):2188-2194.
[17]谢显中,周通等.一种基于流量需求的动态频谱分配算法[J].通信技术,2008,41(10):9-11.
[18] Wang W. and Liu X.. List-coloring based channel allocation for open-spectrum wireless networks[C]. in Proceedings of IEEE 62nd Vehicular Technology Conference. 2005, 1:690-694.
[19] Liu X, Wang W. On the characteristics of spectrum-agile communication networks[C]. Proc. of the 2005 1st IEEE Int’l Symp. on New Frontiers in Dynamic Spectrum Access Networks (DySPAN 2005). Baltimore: IEEE Press, 2005. 214?223.
[20] Friend D.H., ElNainay M.Y., etc. Architecture and performance of an island genetic algorithm-based cognitive network[C]. Consumer Communications and Networking Conference. 2008,993–997.
[21] EI-Nainay, Mustafa Y,etc. Channel allocation & power control for dynamic spectrum cognitive networks using a localized island genetic algorithm[C]. New Frontiers in Dynamic Spectrum Access Networks. Oct. 2008.
[22] MustafaY., El-Nainay. Island Genetic Algorithm-based Cognitive Networks. July1,2009
[23] Gupta P., Kumar P.R.. The Capacity of Wireless Networks[J]. IEEE Trans. Information Theory. 2000,2(46):338-404.
[24] Fudenberg D. and Tirole J.. Game Theory. Cambridge and London :MIT Press. 2000.
[25] Nie N., Comaniciu C.. Adaptive channel allocation spectrum etiquette for cognitive radio networks. New Frontiers in Dynamic Spectrum Access Networks (DySPAN 2005). 2005,269-278.
[26] N.Nie, Comaniciu C., Prathima.A. A game theoretic approach to interference management in cognitive networks[J].Wireless Communications.2007,143:199-219.
[27] He H., Chen J., etc. Game Theoretic Analysis of Joint Channel Selection and Power Allocation in Cognitive Radio Networks[C]. Cognitive Radio Oriented Wireless Networks and Communications. 2008.
[28] Song Y, Zhang C, Fang Y. Joint Channel and Power Allocation in Wireless Mesh Networks: A Game Theoretical Perspective[J]. Selected Areas in Communications. 2008, 26 (7): 1149--1159.
[29]程赓,李昀照,刘威等.认知无线电网络路由及频谱分配联合策略研究[J].电子与信息学报,2008,30(3):695-698.
[30] Gong M.X., Midkiff S.F., Shiwen M.. Design principles for distributed channel assignment inwireless Ad hoc networks[C]. 2005 IEEE International conference on Communications. 2005: 3401-3406.
[31] Gong M.X., Midkiff S.F.. Distributed channel assignment protocols: A cross-layer approach [C]. Wireless Communications and Networking Conference(WCNC’05). 2005, 2195-2200.
[32] So J. and Vaidya N.. A routing protocol for utilizing multiple channels in multi-Hop wireless networks with a single transceiver[C]. UIUC Technical Report. 2004.
[33] Krishnamurthy S., Thoppian M., etc. Control channel based MAC-layer configuration, routing and situation awareness for cognitive radio networks[C]. Military Communications Conference(MILCOM’05). 2005,455-460.
[34] Mitola J., Cognitive radio: An integrated agent architecture of software defined radio[D]. Doctor of Technology. 2000.
[35] Rieser C.J. Biologically inspired cognitive radio engine model utilizing distributed genetic algorithms for secure and robust wireless communications and networking[D]. Ph.D. Dissertation. 2004.
[36] Haykin S.. Cognitive radio: brain-empowered wireless communications[J]. Selected Areas in Communications. 2005, 23(2):201-220.
[37] FCC-03-322. Facilitating opportunities for flexible, efficient and reliable spectrum use employing cognitive radio technologies. http://hraun-foss.fcc.gov/edoes-public/attach -match/ FCC-03-322A1.pdf
[38] Haykin S., Cognitive radio: brain-empowered wireless communications[J].IEEE Journal on Selected Areas in Communications, 2005, 23 (2): 201–220.
[39] Mitola J. Cognitive radio: an integrated agent architecture for software defined radio[D]. Ph.D Thesis, KTH Royal Institute of Technology, 2000.
[40] Federal Communications Commission.Establishment of interference temperature metric to quantify and manage interference and to expand available unlicensed operation in certain fixed mobile and satellite frequency bands. ET Docket 03. 289,Notice of Inquiry and Proposed Rulemaking.
[41] Claney T..Achievable Capacity Under the Interference Temperature Model[C]. IEEE INFOCOM 2007,26th IEEE International Conference on Computer Communications. 2007,794-802.
[42] Clancy T.C., Arbaugh W.A.. Measuring Interference Temperature[J]. Virginia Tech Wireless Personal Communications Symposium. 2006.
[43] Cao L.,Zheng H.. Distributed spectrum allocation via local bargaining[C]. IEEE sensor and AdHoc Communications and Networks(SECON 2005).2005,475-486.
[44]刘帅,刘玉涛等.基于极大独立集的协作竞价频谱分配算法[J].科学技术与工程, 2009,9(17):5132-5135.
[45] Kloeck C., Jaekel H.,etc. Dynamic and local combined pricing, allocation and Billing system with cognitive radios[C].The First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks(DySPAN 2005).2005:73-81.
[46]樊路,刘玉涛等.认知无线电中基于极大独立集的频谱分配算法[J].科技技术与工程, 2009,9(16):4645-4661.
[47] Hao D.D.,Zou S.H.,Cheng S.D.. Heuristic algorithms for dynamic spectrum assignment in open spectrum system[J]. Journal of Software.2008,19(3):479-491.
[48]冯文江,王茹茹,蒋卫恒,吴迪.认知无线电中联合功率控制的动态频谱分配算法[J].计算机应用研究, 2010,27(12):4680-4683.
[2] Capar F., Weiss T., etc. Analysis of Coexistence Strategies for Cellular and Wireless Local Area Networks[C]. Vehicular Technology Conference. October 2003.
[3] Federal Communications Commission. Spectrum Policy Task Force Report[R]. ET Docket No. 02-135, Nov. 2002.
[4] Mitola J., Maguire G.. Cognitive radio: Making software radios more personal[J]. IEEE Personal Communications Magazine. 1999, 6(4):13-18.
[5] Vuran M.C., Akyildiz I.F.. A-MAC: Adaptive Medium Access Control for Next Generation Wireless Terminals[J]. IEEE/ACM transactions on networking. 2007,15(3):574-587.
[6] Stevenson C.R., Cordeiro C., etc. Functional Requirements for the 802.22 WRAN Standard. IEEE doc.: IEEE 802.22-05/0007r40. Sept.2005.
[7] A.T. Hoang, Y.C. Liang. A Two-Phase Channel and Power Allocation Scheme for Cognitive Radio Networks[C]. Personal,Indoor and Mobile Radio Communications. Sept. 2006.
[8] Hoang A.T., Liang Y.C.. Downlink Channel Assignment and Power Control for Cognitive Radio Networks[J]. IEEE transactions on wireless communications. 2008,7(8):3106-3117.
[9] Hoang A.T., Liang Y.C.. Maximizing spectrum utilization of Cognitive radio networks using channel allocation and power control[C]. Vehicular Technology Conference. Sept. 2006.
[10] Behzad A., Rubin I.. Multiple Access Protocol for Power-Controlled Wireless Access Nets[J]. IEEE Transactions on Mobile Computing. 2004,3(4):307–316.
[11] Bambos N., Chen S.C., etc. Radio link admission algorithms for wireless networks with power control and active link quality protection[J]. Fourteenth Annual Joint Conference of the IEEE Computer and Communications Societies. 1995,1:97-104.
[12] Mitra D.. An asynchronous distributed algorithm for power control in Cellular radio systems. in Proceedings of 4th WINLAB Workshop on Third Generation Wireless Information Networks. Rutgers University ,NewBrunswick,NJ. Oct.1993.
[13] Zheng H., Peng C.. Collaboration and fairness in opportunistic spectrum access[C]. Proc. of the 2005 IEEE Int’l Conf. on Communications. IEEE Communications Society Press. 2005.
[14] Peng C, Zheng H, Zhao BY. Utilization and fairness in spectrum assignment for opportunistic spectrum access[J]. Mobile Networks and Applications. 2006, 11(4):555?576.
[15] Zhao J, Zheng H, Yang G. Distributed coordination in dynamic spectrum allocationnetworks[C]. Proc. of the 2005 1st IEEE Int’l Symp on New Frontiers in Dynamic Spectrum Access Networks(DySPAN 2005). Baltimore: IEEE Press, 2005,259?268.
[16]陈劫,李少谦,廖楚林.认知无线电网络中基于需求的频谱资源分配算法研究[J].计算机应用,2008,28(9):2188-2194.
[17]谢显中,周通等.一种基于流量需求的动态频谱分配算法[J].通信技术,2008,41(10):9-11.
[18] Wang W. and Liu X.. List-coloring based channel allocation for open-spectrum wireless networks[C]. in Proceedings of IEEE 62nd Vehicular Technology Conference. 2005, 1:690-694.
[19] Liu X, Wang W. On the characteristics of spectrum-agile communication networks[C]. Proc. of the 2005 1st IEEE Int’l Symp. on New Frontiers in Dynamic Spectrum Access Networks (DySPAN 2005). Baltimore: IEEE Press, 2005. 214?223.
[20] Friend D.H., ElNainay M.Y., etc. Architecture and performance of an island genetic algorithm-based cognitive network[C]. Consumer Communications and Networking Conference. 2008,993–997.
[21] EI-Nainay, Mustafa Y,etc. Channel allocation & power control for dynamic spectrum cognitive networks using a localized island genetic algorithm[C]. New Frontiers in Dynamic Spectrum Access Networks. Oct. 2008.
[22] MustafaY., El-Nainay. Island Genetic Algorithm-based Cognitive Networks. July1,2009
[23] Gupta P., Kumar P.R.. The Capacity of Wireless Networks[J]. IEEE Trans. Information Theory. 2000,2(46):338-404.
[24] Fudenberg D. and Tirole J.. Game Theory. Cambridge and London :MIT Press. 2000.
[25] Nie N., Comaniciu C.. Adaptive channel allocation spectrum etiquette for cognitive radio networks. New Frontiers in Dynamic Spectrum Access Networks (DySPAN 2005). 2005,269-278.
[26] N.Nie, Comaniciu C., Prathima.A. A game theoretic approach to interference management in cognitive networks[J].Wireless Communications.2007,143:199-219.
[27] He H., Chen J., etc. Game Theoretic Analysis of Joint Channel Selection and Power Allocation in Cognitive Radio Networks[C]. Cognitive Radio Oriented Wireless Networks and Communications. 2008.
[28] Song Y, Zhang C, Fang Y. Joint Channel and Power Allocation in Wireless Mesh Networks: A Game Theoretical Perspective[J]. Selected Areas in Communications. 2008, 26 (7): 1149--1159.
[29]程赓,李昀照,刘威等.认知无线电网络路由及频谱分配联合策略研究[J].电子与信息学报,2008,30(3):695-698.
[30] Gong M.X., Midkiff S.F., Shiwen M.. Design principles for distributed channel assignment inwireless Ad hoc networks[C]. 2005 IEEE International conference on Communications. 2005: 3401-3406.
[31] Gong M.X., Midkiff S.F.. Distributed channel assignment protocols: A cross-layer approach [C]. Wireless Communications and Networking Conference(WCNC’05). 2005, 2195-2200.
[32] So J. and Vaidya N.. A routing protocol for utilizing multiple channels in multi-Hop wireless networks with a single transceiver[C]. UIUC Technical Report. 2004.
[33] Krishnamurthy S., Thoppian M., etc. Control channel based MAC-layer configuration, routing and situation awareness for cognitive radio networks[C]. Military Communications Conference(MILCOM’05). 2005,455-460.
[34] Mitola J., Cognitive radio: An integrated agent architecture of software defined radio[D]. Doctor of Technology. 2000.
[35] Rieser C.J. Biologically inspired cognitive radio engine model utilizing distributed genetic algorithms for secure and robust wireless communications and networking[D]. Ph.D. Dissertation. 2004.
[36] Haykin S.. Cognitive radio: brain-empowered wireless communications[J]. Selected Areas in Communications. 2005, 23(2):201-220.
[37] FCC-03-322. Facilitating opportunities for flexible, efficient and reliable spectrum use employing cognitive radio technologies. http://hraun-foss.fcc.gov/edoes-public/attach -match/ FCC-03-322A1.pdf
[38] Haykin S., Cognitive radio: brain-empowered wireless communications[J].IEEE Journal on Selected Areas in Communications, 2005, 23 (2): 201–220.
[39] Mitola J. Cognitive radio: an integrated agent architecture for software defined radio[D]. Ph.D Thesis, KTH Royal Institute of Technology, 2000.
[40] Federal Communications Commission.Establishment of interference temperature metric to quantify and manage interference and to expand available unlicensed operation in certain fixed mobile and satellite frequency bands. ET Docket 03. 289,Notice of Inquiry and Proposed Rulemaking.
[41] Claney T..Achievable Capacity Under the Interference Temperature Model[C]. IEEE INFOCOM 2007,26th IEEE International Conference on Computer Communications. 2007,794-802.
[42] Clancy T.C., Arbaugh W.A.. Measuring Interference Temperature[J]. Virginia Tech Wireless Personal Communications Symposium. 2006.
[43] Cao L.,Zheng H.. Distributed spectrum allocation via local bargaining[C]. IEEE sensor and AdHoc Communications and Networks(SECON 2005).2005,475-486.
[44]刘帅,刘玉涛等.基于极大独立集的协作竞价频谱分配算法[J].科学技术与工程, 2009,9(17):5132-5135.
[45] Kloeck C., Jaekel H.,etc. Dynamic and local combined pricing, allocation and Billing system with cognitive radios[C].The First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks(DySPAN 2005).2005:73-81.
[46]樊路,刘玉涛等.认知无线电中基于极大独立集的频谱分配算法[J].科技技术与工程, 2009,9(16):4645-4661.
[47] Hao D.D.,Zou S.H.,Cheng S.D.. Heuristic algorithms for dynamic spectrum assignment in open spectrum system[J]. Journal of Software.2008,19(3):479-491.
[48]冯文江,王茹茹,蒋卫恒,吴迪.认知无线电中联合功率控制的动态频谱分配算法[J].计算机应用研究, 2010,27(12):4680-4683.