异构环境下的网络选择和资源分配研究
|
摘要
随着无线通信技术的高速发展,有限的无线资源与新型业务的各类需求之间的矛盾不断增加。另一方面,现有多种无线接入技术(Radio Access Technology, RAT)的共存形成了异构环境,在这样的客观条件下,如何对多网络覆盖下的用户进行合理有效的网络选择、对异构网络资源充分利用来缓解无线资源和用户需求间的矛盾,在近期引起了广泛的关注。
异构网络的联合无线资源管理存在集中式、分布式以及混合式三种模式,其中分布式模式架构具有较高灵活性,且易于扩展。因此,本文立足于分布式的异构网络资源管理模式,分别以网络选择、网络选择联合资源分配为研究重点,围绕多个研究目标,展开了深入的研究。
由于多RATs覆盖下属性信息的复杂性,本文综合利用模糊逻辑的推理能力和神经网络的学习特性,提出一种以用户为中心的,且用户通过其内置的模糊神经网络模型进行网络选择的算法。当多个用户均应用此算法时,仿真表明网络接入点间可以达到较好的负载均衡。
针对基于正交频分多址接入(Orthogonal Frequency Division Multiple Access, OFDM A)技术的多RATs存在的异构环境上行方向,首先提出了保证比例公平性的资源分配方案。该方案在默认用户选择所有可接入网络进行数据发送的条件下,最大化用户间的比例公平性,即通过迭代计算得到用户向每个RATs接入点的发送功率以及RATs分配的带宽资源。考虑到分配的带宽以资源单元为最小颗粒度,最后对所分配的带宽进行调整。仿真表明所提方案以损失部分吞吐量为代价,可以达到较高的用户公平性。继而进一步,对上行支持多业务的、在满足时延受限业务用户最小速率的要求下,最大化尽力服务业务用户的比例公平性的问题进行研究,且提出了联合网络选择和资源分配的两层迭代方案,以及低复杂度的启发式方案。虽然启发式方案性能差于迭代方案,但尽力服务用户仍可以达到比较高的公平性。
对基于多种多址接入技术的多RATs存在异构环境下行方向,考虑到不同多址技术对应分配的无线资源有所不同,将其统一映射到用户可以达到的数据速率上。首先在默认用户接入所有可用网络条件下,以网络效用为优化目标展开研究,通过对归纳问题的对偶求解,提出一个最优资源分配的迭代算法。进一步,针对下行的支持多业务的、在满足时延受限业务用户最小速率的要求下,最大化尽力服务业务用户的比例公平性的联合网络选择和资源分配问题展开研究,将其归纳为混合整数规划问题,然后采用连续放松的方法,并转求其对偶问题。而通过对问题的分析,提出一个联合网络选择和资源分配的迭代方案。分析与仿真结果表明,该方案可以达到较高用户公平性。
With the rapid development of wireless communication, the contradiction between limited wireless resources and the various needs of new traffic services is increasing. In the mean time, the existing multiple radio access technologies form the heterogeneous environments. In such background, how to make reasonably and effective network selection for users, and take full advantage of heterogeneous network resources are very vital for easing the contradiction between the wireless resources and the needs of users, which also have attracted widespread attention.
This dissertation describes three types of the joint radio resource management architectures for heterogeneous wireless networks. Based on the distributed radio resource management architecture, this dissertation focuses on the subjects of network selection and resource allocation.
Network selection, also known as radio access technology selection, is the most important part of accessing control and handoff management. For distributed network architecture, this dissertation presents a user-centric network selection strategy with the purpose of load balancing by using a combination of fuzzy logic and neural network technology.
This dissertation studies the problem of joint network selection and resource allocation with regard to the uplink and downlink transmission directions, respectively. For uplink transmission, OFDMA-based radio access technologies are considered, this dissertation forms a proportional fairness resource allocation problem with the condition that users may access all available networks in the multi-user multi-access scene. Furthermore, this dissertation then investigates jointly network selection and resource allocation problem in multi-service multi-user multi-access scene, with the purpose of maximizing the proportion fairness of best effort users, and under the condition that delay constraint users must be satisfied. Since the proposed problem is a mixed integer programming problem, the continuous relaxation is applied, and then the dual problem is solved. Therefore, the two-layer iterative solution, which could achieve the near upper bound, is proposed. Considering the complexity of the two-layer iteration solution, this dissertation further proposes a low complexity heuristic algorithm. Although the performance of the proposed heuristic algorithm is worse than the two-layer iterative algorithm, best effort users can still achieve high fairness.
For downlink transmission, this dissertation considers variety types of access technology, such as TDMA, CDMA and OFDMA. To make convenience of study, the different resources are mapped to users'data rate. And then, network selection and resource allocation problems are investigated. With the condition that users may get data rates from all available networks, this dissertation forms a utility based resource allocation problem in the multi-user multi-access scene. Furthermore, similarly to uplink, this dissertation then investigates joint network selection and resource allocation problem in multi-service multi-user downlink scene, with the purpose of maximizing the proportion fairness of best effort users, and under the condition that delay constraint users must be satisfied. Since the formed problem is mixed integer programming, the continuous relaxation is used and the dual problem is solved. Through analysis, this dissertation proposes a jointly network selection and resource allocation iterative algorithm for downlink.
异构网络的联合无线资源管理存在集中式、分布式以及混合式三种模式,其中分布式模式架构具有较高灵活性,且易于扩展。因此,本文立足于分布式的异构网络资源管理模式,分别以网络选择、网络选择联合资源分配为研究重点,围绕多个研究目标,展开了深入的研究。
由于多RATs覆盖下属性信息的复杂性,本文综合利用模糊逻辑的推理能力和神经网络的学习特性,提出一种以用户为中心的,且用户通过其内置的模糊神经网络模型进行网络选择的算法。当多个用户均应用此算法时,仿真表明网络接入点间可以达到较好的负载均衡。
针对基于正交频分多址接入(Orthogonal Frequency Division Multiple Access, OFDM A)技术的多RATs存在的异构环境上行方向,首先提出了保证比例公平性的资源分配方案。该方案在默认用户选择所有可接入网络进行数据发送的条件下,最大化用户间的比例公平性,即通过迭代计算得到用户向每个RATs接入点的发送功率以及RATs分配的带宽资源。考虑到分配的带宽以资源单元为最小颗粒度,最后对所分配的带宽进行调整。仿真表明所提方案以损失部分吞吐量为代价,可以达到较高的用户公平性。继而进一步,对上行支持多业务的、在满足时延受限业务用户最小速率的要求下,最大化尽力服务业务用户的比例公平性的问题进行研究,且提出了联合网络选择和资源分配的两层迭代方案,以及低复杂度的启发式方案。虽然启发式方案性能差于迭代方案,但尽力服务用户仍可以达到比较高的公平性。
对基于多种多址接入技术的多RATs存在异构环境下行方向,考虑到不同多址技术对应分配的无线资源有所不同,将其统一映射到用户可以达到的数据速率上。首先在默认用户接入所有可用网络条件下,以网络效用为优化目标展开研究,通过对归纳问题的对偶求解,提出一个最优资源分配的迭代算法。进一步,针对下行的支持多业务的、在满足时延受限业务用户最小速率的要求下,最大化尽力服务业务用户的比例公平性的联合网络选择和资源分配问题展开研究,将其归纳为混合整数规划问题,然后采用连续放松的方法,并转求其对偶问题。而通过对问题的分析,提出一个联合网络选择和资源分配的迭代方案。分析与仿真结果表明,该方案可以达到较高用户公平性。
With the rapid development of wireless communication, the contradiction between limited wireless resources and the various needs of new traffic services is increasing. In the mean time, the existing multiple radio access technologies form the heterogeneous environments. In such background, how to make reasonably and effective network selection for users, and take full advantage of heterogeneous network resources are very vital for easing the contradiction between the wireless resources and the needs of users, which also have attracted widespread attention.
This dissertation describes three types of the joint radio resource management architectures for heterogeneous wireless networks. Based on the distributed radio resource management architecture, this dissertation focuses on the subjects of network selection and resource allocation.
Network selection, also known as radio access technology selection, is the most important part of accessing control and handoff management. For distributed network architecture, this dissertation presents a user-centric network selection strategy with the purpose of load balancing by using a combination of fuzzy logic and neural network technology.
This dissertation studies the problem of joint network selection and resource allocation with regard to the uplink and downlink transmission directions, respectively. For uplink transmission, OFDMA-based radio access technologies are considered, this dissertation forms a proportional fairness resource allocation problem with the condition that users may access all available networks in the multi-user multi-access scene. Furthermore, this dissertation then investigates jointly network selection and resource allocation problem in multi-service multi-user multi-access scene, with the purpose of maximizing the proportion fairness of best effort users, and under the condition that delay constraint users must be satisfied. Since the proposed problem is a mixed integer programming problem, the continuous relaxation is applied, and then the dual problem is solved. Therefore, the two-layer iterative solution, which could achieve the near upper bound, is proposed. Considering the complexity of the two-layer iteration solution, this dissertation further proposes a low complexity heuristic algorithm. Although the performance of the proposed heuristic algorithm is worse than the two-layer iterative algorithm, best effort users can still achieve high fairness.
For downlink transmission, this dissertation considers variety types of access technology, such as TDMA, CDMA and OFDMA. To make convenience of study, the different resources are mapped to users'data rate. And then, network selection and resource allocation problems are investigated. With the condition that users may get data rates from all available networks, this dissertation forms a utility based resource allocation problem in the multi-user multi-access scene. Furthermore, similarly to uplink, this dissertation then investigates joint network selection and resource allocation problem in multi-service multi-user downlink scene, with the purpose of maximizing the proportion fairness of best effort users, and under the condition that delay constraint users must be satisfied. Since the formed problem is mixed integer programming, the continuous relaxation is used and the dual problem is solved. Through analysis, this dissertation proposes a jointly network selection and resource allocation iterative algorithm for downlink.
引文
[1]IEEE 802.21 Media Independent Handover Services[S],2012.
[2]3GPP TS 23.234:3GPP system to Wireless Local Area Network (WLAN) interworking; System description[S],2012.
[3]李军.异构无线网络融合理论与技术实现[M].北京,电子工业出版社,2009.
[4]Aiash M, Mapp G, Lasebae A, Loo J, Sardis F, et al. A survey of potential architectures for communication in heterogeneous networks[C]. Proc. of IEEE Wireless Telecommunications Symposium (WTS),2012.
[5]3GPP TS 23.402:Architecture enhancements for non-3GPP accesses[S],2013.
[6]纪阳,张平.端到端重配置无线网络技术[M].北京,北京邮电大学出版社,2006.
[7]Mitola J. The software radio architecrure[J]. IEEE Communications Magazine, 1995,33(5):26-38.
[8]Mitola J, Maguire GQ. Cognitive radios:Making software radios more personal[J]. IEEE Personal Communications,1999,6(4):13-18.
[9]Mehta M, Drew N, Vardoulias G, Greco N, Niedermeier C. Reconfigurable terminals:An overview of architectural solutions[J]. IEEE Communications Magazine,2001,39(8) 8:82-89.
[10]Amano H. A survey on dynamically reconfigurable processors [J]. IEICE Transactions on Communications.2006,89(12):3179-3187.
[11]Munoz J, Alonso JV, Garcia FQ, Costas S, Pillado M, et al. A cognitive mobile BTS solution with software-defined radioelectric sensing[J]. Sensors,2013,13(2): 2051-2075.
[12]Lopez-Perez D, Guvenc I, Chu X. Mobility management challenges in 3GPP heterogeneous networks[J]. IEEE Communications Magazine,2012,50(12): 70-78.
[13]Al-Surmi I, Othman M, Mohd Ali B. Mobility management for IP-based next generation mobile networks:Review, challenge and perspective[J]. Journal of Network and Computer Applications,2012,35(1):295-315.
[14]Chung Y W, Lee S W. Modeling and performance analysis of power efficient multi-tier location management in interworked WLAN and cellular network[J]. Mathematical and Computer Modelling,2012.
[15]Cho I, Okamura K, Kim TW, Hong CS. Performance analysis of IP mobility with multiple care-of addresses in heterogeneous wireless networks[J]. Wireless Networks,2013:1-12.
[16]Lian R, Tian H, Fei W, Miao J, Wang C. QoS-aware load balancing algorithm for joint group call admission control in heterogeneous networks[C]. Proc. of IEEE Vehicular Technology Conference, Spring,2012.
[17]Kim S. Adaptive call admission control scheme for heterogeneous overlay networks[J]. Journal of Communications and Networks,2012,14(4):461-466.
[18]Fernandes S, Karmouch A. Vertical mobility management architectures in wireless networks:A comprehensive survey and future directions [J]. IEEE Communications Surveys & Tutorials,2012,14(1):45-63.
[19]Zekri M, Jouaber B, Zeghlache D. A review on mobility management and vertical handover solutions over heterogeneous wireless networks[J]. Computer Communications,2012.
[20]Piamrat K, Ksentini A, Bonnin JM, Viho C. Radio resource management in emerging heterogeneous wireless networks[J]. Computer Communications,2011, 34(9):1066-1076.
[21]闫志刚,黄晓庆,王军,黄宇红.无线多连接的概念与实现技术[C].2008世界通信大会(IEEE International Conference on Communications, ICC2008)中国论坛.
[22]雷蕾,闫志刚.多频带无线通信系统的多连接实现方案[J].电信工程技术与标准化,2009,22(1)：81-85.
[23]3GPP, Improvement of Radio Resource Management (RRM) across RNS and RNS/BSS[R], Technical Report 25.881, v5.0.0,2000.
[24]3 GPP, Improvement of Radio Resource Management (RRM) across RNS and RNS/BSS Post-Rel-5[R], Technical Report 25.891, v0.3.0,2003.
[25]Gustafsson E, Jonsson A. Always best connected [J]. IEEE Wireless Communications Magazine,2003,10(1):49-55.
[26]Wang LS, Kuo GS. Mathematical modeling for network selection in heterogeneous wireless networks-a tutorial[J]. IEEE Communications Surveys & Turorials,2012,2(99):1-22.
[27]Chan H, Fan P, Cao Z. A utility-based network selection scheme for multiple services in heterogeneous networks[C]. Proc. of IEEE International Conference on Wireless Networks, Communications and Mobile Computing,2005,2: 1175-1180.
[28]Nguyen-Vuong QT, Ghamri-Doudane Y, Agoulmine N. On utility models for access network selection in wireless heterogeneous networks[C]. Proc. of IEEE Network Operations and Management Symposium,2008:144-151.
[29]Kosmides P, Rouskas A, Anagnostou M. Utility-based RAT selection optimization in heterogeneous wireless networks[J]. Pervasive and Mobile Computing,2013.
[30]Hwang CL, Yoon K. Multiple attribute decision making[M]. Berlin:Springer, 1981.
[31]Xu L, Guo D, Chen X, Shi C. A network selection algorithm based on AHP in satellite heterogeneous networks[C]. Proc. of 2012 Second International Conference on Electric Technology and Civil Engineering. IEEE Computer Society,2012:100-103.
[32]Verma R, Singh NP. GRA based network selection in heterogeneous wireless networks[J]. Wireless Personal Communications,2013:1-16.
[33]Savitha K, Chandrasekar DR. Network selection using topsis in vertical handover decision schemes for heterogeneous wireless networks[J]. arXiv preprint arXiv:1106.2402,2011.
[34]Chamodrakas I, Martakos D. A utility-based fuzzy TOPSIS method for energy efficient network selection in heterogeneous wireless networks[J]. Applied Soft Computing,2012,12(7):1929-1938.
[35]Bari F, Leung V. Application of ELECTRE to network selection in a hetereogeneous wireless network environment[C]. Proc. of IEEE Wireless Communications and Networking Conference(WCNC),2007:3810-3815.
[36]Savitha K, Chandrasekar C. Trusted network selection using SAW and TOPSIS algorithms for heterogeneous wireless networks[J]. arXiv preprint arXiv:1108.0141,2011.
[37]Sgora A, Chatzimisios P, Vergados DD. Access network selection in a heterogeneous environment using the AHP and fuzzy TOPSIS methods[M]. Mobile Lightweight Wireless Systems. Springer Berlin Heidelberg,2010:88-98.
[38]Lahby M, Cherkaoui L, Adib A. Network selection algorithm based on Diff-AHP and TOPSIS in heterogeneous wireless networks[C]. Proc. of IEEE International Conference on Multimedia Computing and Systems (ICMCS),2012:485-490.
[39]Yang L, Guo D. A satellite heterogeneous network selection algorithm combining AHP and TOPSIS[J].2012.
[40]Charilas DE, Markaki OI, Psarras J, Constantinou P. Application of Fuzzy AHP and ELECTRE to network selection[M]. Mobile Lightweight Wireless Systems. Springer Berlin Heidelberg,2009:63-73.
[41]Klir GJ, Yuan B. Fuzzy sets and fuzzy logic[M]. New Jersey:Prentice Hall,1995.
[42]Hou J, O'Brien DC. Vertical handover-decision-making algorithm using fuzzy logic for the integrated Radio-and-OW system[J]. Wireless Communications, IEEE Transactions on,2006,5(1):176-185.
[43]Radhika K, Reddy AVG. Network selection in heterogeneous wireless networks based on fuzzy multiple criteria decision making[C]. Proc. of IEEE 3rd International Conference on Electronics Computer Technology (ICECT),2011,6: 136-139.
[44]Chamodrakas I, Martakos D. A utility-based fuzzy TOPSIS method for energy efficient network selection in heterogeneous wireless networks[J]. Applied Soft Computing,2012,12(7):1929-1938.
[45]Chang YH, Yeh CH, Chang YW. A new method selection approach for fuzzy group multicriteria decision making[J]. Applied Soft Computing,2013.
[46]Giupponi L, Agusti R, Perez-Romero J, Sallent O. Fuzzy neural control for economic-driven radio resource management in beyond 3G networks[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part C:Applications and Reviews,2009,39(2):170-189.
[47]Fan J, Zhang S, Zhou W. A Semi-distributed Network Selection Scheme in Heterogeneous Wireless Netw.orks[M]. Wireless Internet. Springer Berlin Heidelberg,2012:287-297.
[48]LI M, XU Y, MIAO R. Network selection for cognitive radio based on fuzzy learning[J]. IEICE transactions on communications,2011,94(12):3490-3497.
[49]Han Z, Niyato D, Saad W, Hj(?)rungnes A. Game theory in wireless and communication networks:theory, models, and applications[M]. Cambridge University Press,2011.
[50]Cesana M, Gatti N, Malanchini I. Game theoretic analysis of wireless access network selection:models, inefficiency bounds, and algorithms[C]. Proc. of ICST 3rd International Conference on Performance Evaluation Methodologies and Tools,2008:6.
[51]Niyato D, Hossain E. Dynamics of network selection in heterogeneous wireless networks:an evolutionary game approach[J]. IEEE Transactions on Vehicular Technology,2009,58(4):2008-2017.
[52]Zhu K, Niyato D, Wang P. Network selection in heterogeneous wireless networks: evolution with incomplete information[C]. Proc. of IEEE Wireless Communications and Networking Conference (WCNC),2010.
[53]Xu P, Fang X, Liu X. A non-cooperative pairwise matrices game model for heterogeneous network selection[C]. Proc. of IEEE International Conference on Communications and Mobile Computing (CMC),,2010,3:387-391.
[54]Niyato D, Hossain E. Competitive pricing in heterogeneous wireless access networks:Issues and approaches[J]. IEEE Network,2008,22(6):4-11.
[55]Sibanda CCL, Bagula AB. Network selection for mobile nodes in heterogeneous wireless networks using Knapsack problem Dynamic algorithms[C]. Proc. of IEEE Telecommunications Forum (TELFOR),2012:174-177.
[56]Andersson K, Ahlund C. Optimized access network selection in a combined WLAN/LTE environment[J]. Wireless Personal Communications,2011,61(4): 739-751.
[57]Gelabert X, Perez-Romero J, Sallent O, Agusti R. A Markovian approach to radio access technology selection in heterogeneous multiaccess/multiservice wireless networks[J]. IEEE Transactions on Mobile Computing,2008,7(10):1257-1270.
[58]Niyato D, Hossain E. A cooperative game framework for bandwidth allocation in 4G heterogeneous wireless networks[C]. Proc. of IEEE International Conference on Communications, ICC'06,2006,9:4357-4362.
[59]Niyato D, Hossain E. A noncooperative game-theoretic framework for radio resource management in 4G heterogeneous wireless access networks[J]. IEEE Transactions on Mobile Computing,2008,7(3):332-345.
[60]Niyato D, Hossain E. A game theoretic analysis of service competition and pricing in heterogeneous wireless access networks[J]. IEEE Transactions on Wireless Communications,2008,7(12):5150-5155.
[61]Choi Y, Kim H, Han S, Han Y. Joint resource allocation for parallel multi-radio access in heterogeneous wireless networks[J]. IEEE Transactions on Wireless Communication,2010,9(11):3324-3329.
[62]Sundar RS, Kumar SN. Performance improvement of heterogeneous wireless networks using modified newton method[J]. International Journal of Software Engineering & Applications (IJSEA),2012,3(3):79-90.
[63]Choi Y, Lee Y, Cioffi JM. Optimization of cooperative inter-operability in heterogeneous networks with cognitive ability[J]. IEEE Communications Letters, 2011,15(11):1178-1180.
[64]Mao J, Hu Z, Wang CR, Lian RR, Tian H. Optimal resource allocation for multi-access in heterogeneous wireless networks[C]. Proc. of IEEE Vehicular Technology Conference, Spring,2012.
[65]Mao J, Hu Z, Yang K, Wang CR, Tian H. Joint power and bandwidth allocation algorithm with QoS support in heterogeneous wireless networks[J]. IEEE Communications Letters,2012,16(4):479-481.
[66]Jaffe JM. Bottleneck flow control [J]. IEEE Transactions on Communication, 1981,29(7):954-962.
[67]Kelly FP, Maulloo A, Tan D. Rate control for communication networks:shadow prices, proportional fairness and stability[J]. Journal of Operations Research Society,1998,49(3):237-252.
[68]Jain R. The Art of Computer Systems Performance Analysis:techniques for experimental design, measurement, simulation and modeling[M]. New York, USA:Wiley,1991.
[69]Blau I, Wunder G, Karla I, Sigle R. Decentralized utility maximization in heterogeneous multicell scenarios with interference limited and orthogonal air interfaces[J]. EURASIP Journal on Wireless Communications and Networking, 2009,9(2):470-481.
[70]Wang W, Liu X, Vicente J, Mohapatra P. Integration Gain of Heterogeneous WiFi/WiMAX Networks[J]. IEEE Transactions on Mobile Computing,2011, 10(8):1131-1143.
[71]Nguyen HA, Van NT, Deokjai C. How to maximize user satisfaction degree in multi-service IP networks [C]. Proc. of First Asian Conference on Intelligent Information and Database Systems, Dong Hoi,2009:471-476.
[72]Zhu X, Agrawal P, Singh JP, Alpcan T; Girod B. Distributed rate allocation policies for multihomed video streaming over heterogeneous access networks [J]. IEEE Transactions on Multimedia,2009,11(4):752-764.
[73]Zadeh LA. Fuzzy sets[J]. Information and control,1965,8(3):338-353.
[74]刘增良,刘有才.模糊逻辑与神经网络-理论研究与探索[M].北京航空航天大学出版社,1996.
[75]吴晓莉,林哲辉.MATLAB辅助模糊系统设计[M].西安电子科技大学出版社,2002.
[76]Boyd S, Vandenberghe L. Convex optimization[M]. New York, USA:Cambridge University Press,2004.
[77]Yu W, Lui R. Dual methods for nonconvex spectrum optimization of multicarrier systems[J]. IEEE Transactions on Communications,2006,54(7):1310-1322.
[78]Palomar DP, Chiang M. A tutorial on decomposition methods for network utility maximization[J]. IEEE Journal on Selected Areas in Communications,2006, 24(8):1439-1451.
[79]Lin CT, Lee CSG. Neural-network-based fuzzy logic control and decision system[J]. IEEE Transactions on Computers,1991,40(12):1320-1336.
[80]Shi WX, Fan SS, Wang N, Xia CJ. Fuzzy neural network based access selection algorithm in heterogeneous wireless networks[J]. Journal of China Institute of Communications,2010,31(9):151-156.
[81]Ramesh Babu HS, Gowrishankar SPS. An intelligent fuzzy neural call admission control mechanism for guaranteed QoS in heterogeneous wireless networks[C]. Proc. of the International MultiConference of Engineers and Computer Scientists. 2010,1.
[82]Kim H, Han Y. A proportional fair scheduling for multicarrier transmission systems[J]. IEEE Communications Letter,2005,9(3):210-212.
[83]Li Q, Hu QY, Qian Y, et al. A proportional fair radio resource allocation for heterogeneous cellular networks with relays[C]. Proc. of IEEE Global Communications Conference,2012.
[84]Neely MJ, Modiano E, Li CP. Fairness and optimal stochastic control for heterogeneous networks[J]. IEEE/ACM Transactions on Networking,2008,16(2): 396-409.
[85]Tao M, Liang Y, Zhang F. Resource allocation for delay differentiated traffic in multiuser OFDM systems[J]. IEEE Transactions on Wireless Communication, 2008,7(6):2190-2201.
[86]Boyd S, Xiao L, Mutapcic A. Subgradient Methods[M]. Cambridge University Press, New York, NY, USA,2004.
[87]Parson JD. Mobile Radio Propagation Channel[M].2nd ed. New York:Wiley, 2001.
[88]Shen W, Zeng Q. Resource management schemes for multiple traffic in integrated heterogeneous wireless and mobile networks[C]. Proc. of 17th International Conference on Computer Communications and Networks (ICCCN),2008.
[89]Luo C, Ji H, Li Y. Utility based multi-service bandwidth allocation in the 4G heterogeneous wireless access networks[C]. Proc. of IEEE Wireless Communications and Networking Conference (WCNC),2009.
[90]Pei X, Jiang T, Qu D, Zhu G, Liu J. Radio resource management and access control mechanism based on a novel economic model in heterogeneous wireless networks[J]. IEEE Transactions on Vehicular Technology,2010,59(6): 3047-3056.
[91]Bin L, Wenxiao S, Na L. A hierarchical semi-centralized architecture for load balancing of heterogeneous wireless networks[C]. Proc. of IEEE Networks Security Wireless Communications and Trusted Computing (NSWCTC),2010 Second International Conference on,2010,2:28-31.
[92]Ismail M, Zhuang W. Decentralized radio resource allocation for single-network and multi-homing services in cooperative heterogeneous wireless access medium[J]. IEEE Transactions on Wireless Communications,2012,11(11): 4085-4095.
[93]Ismail M, Zhuang W. A distributed multi-service resource allocation algorithm in heterogeneous wireless access medium[J]. IEEE Journal on Selected Areas In Communications,2012,30(2):425-432.
[94]Ismail M, Abdrabou A, Zhuang W. Cooperative decentralized resource allocation in heterogeneous wireless access medium[J]. IEEE Transactions on Wireless Communication,2013,12(2):714-724.
[95]Goldsmith A. Wireless Communications[M]. Cambridge University Press, New York, USA,2005.
[96]Jang J, Lee KB. Transmit power adaptation for multiuser OFDM systems[J]. IEEE Journal on Selected Areas in Communications,2003,21(2):171-178.
[97]Vivek M. Enhanced wireless mesh networking for ns-2 simulator[J]. ACM SIGCOMM Computer Communication Review,2007,37(3):69-72.
[2]3GPP TS 23.234:3GPP system to Wireless Local Area Network (WLAN) interworking; System description[S],2012.
[3]李军.异构无线网络融合理论与技术实现[M].北京,电子工业出版社,2009.
[4]Aiash M, Mapp G, Lasebae A, Loo J, Sardis F, et al. A survey of potential architectures for communication in heterogeneous networks[C]. Proc. of IEEE Wireless Telecommunications Symposium (WTS),2012.
[5]3GPP TS 23.402:Architecture enhancements for non-3GPP accesses[S],2013.
[6]纪阳,张平.端到端重配置无线网络技术[M].北京,北京邮电大学出版社,2006.
[7]Mitola J. The software radio architecrure[J]. IEEE Communications Magazine, 1995,33(5):26-38.
[8]Mitola J, Maguire GQ. Cognitive radios:Making software radios more personal[J]. IEEE Personal Communications,1999,6(4):13-18.
[9]Mehta M, Drew N, Vardoulias G, Greco N, Niedermeier C. Reconfigurable terminals:An overview of architectural solutions[J]. IEEE Communications Magazine,2001,39(8) 8:82-89.
[10]Amano H. A survey on dynamically reconfigurable processors [J]. IEICE Transactions on Communications.2006,89(12):3179-3187.
[11]Munoz J, Alonso JV, Garcia FQ, Costas S, Pillado M, et al. A cognitive mobile BTS solution with software-defined radioelectric sensing[J]. Sensors,2013,13(2): 2051-2075.
[12]Lopez-Perez D, Guvenc I, Chu X. Mobility management challenges in 3GPP heterogeneous networks[J]. IEEE Communications Magazine,2012,50(12): 70-78.
[13]Al-Surmi I, Othman M, Mohd Ali B. Mobility management for IP-based next generation mobile networks:Review, challenge and perspective[J]. Journal of Network and Computer Applications,2012,35(1):295-315.
[14]Chung Y W, Lee S W. Modeling and performance analysis of power efficient multi-tier location management in interworked WLAN and cellular network[J]. Mathematical and Computer Modelling,2012.
[15]Cho I, Okamura K, Kim TW, Hong CS. Performance analysis of IP mobility with multiple care-of addresses in heterogeneous wireless networks[J]. Wireless Networks,2013:1-12.
[16]Lian R, Tian H, Fei W, Miao J, Wang C. QoS-aware load balancing algorithm for joint group call admission control in heterogeneous networks[C]. Proc. of IEEE Vehicular Technology Conference, Spring,2012.
[17]Kim S. Adaptive call admission control scheme for heterogeneous overlay networks[J]. Journal of Communications and Networks,2012,14(4):461-466.
[18]Fernandes S, Karmouch A. Vertical mobility management architectures in wireless networks:A comprehensive survey and future directions [J]. IEEE Communications Surveys & Tutorials,2012,14(1):45-63.
[19]Zekri M, Jouaber B, Zeghlache D. A review on mobility management and vertical handover solutions over heterogeneous wireless networks[J]. Computer Communications,2012.
[20]Piamrat K, Ksentini A, Bonnin JM, Viho C. Radio resource management in emerging heterogeneous wireless networks[J]. Computer Communications,2011, 34(9):1066-1076.
[21]闫志刚,黄晓庆,王军,黄宇红.无线多连接的概念与实现技术[C].2008世界通信大会(IEEE International Conference on Communications, ICC2008)中国论坛.
[22]雷蕾,闫志刚.多频带无线通信系统的多连接实现方案[J].电信工程技术与标准化,2009,22(1)：81-85.
[23]3GPP, Improvement of Radio Resource Management (RRM) across RNS and RNS/BSS[R], Technical Report 25.881, v5.0.0,2000.
[24]3 GPP, Improvement of Radio Resource Management (RRM) across RNS and RNS/BSS Post-Rel-5[R], Technical Report 25.891, v0.3.0,2003.
[25]Gustafsson E, Jonsson A. Always best connected [J]. IEEE Wireless Communications Magazine,2003,10(1):49-55.
[26]Wang LS, Kuo GS. Mathematical modeling for network selection in heterogeneous wireless networks-a tutorial[J]. IEEE Communications Surveys & Turorials,2012,2(99):1-22.
[27]Chan H, Fan P, Cao Z. A utility-based network selection scheme for multiple services in heterogeneous networks[C]. Proc. of IEEE International Conference on Wireless Networks, Communications and Mobile Computing,2005,2: 1175-1180.
[28]Nguyen-Vuong QT, Ghamri-Doudane Y, Agoulmine N. On utility models for access network selection in wireless heterogeneous networks[C]. Proc. of IEEE Network Operations and Management Symposium,2008:144-151.
[29]Kosmides P, Rouskas A, Anagnostou M. Utility-based RAT selection optimization in heterogeneous wireless networks[J]. Pervasive and Mobile Computing,2013.
[30]Hwang CL, Yoon K. Multiple attribute decision making[M]. Berlin:Springer, 1981.
[31]Xu L, Guo D, Chen X, Shi C. A network selection algorithm based on AHP in satellite heterogeneous networks[C]. Proc. of 2012 Second International Conference on Electric Technology and Civil Engineering. IEEE Computer Society,2012:100-103.
[32]Verma R, Singh NP. GRA based network selection in heterogeneous wireless networks[J]. Wireless Personal Communications,2013:1-16.
[33]Savitha K, Chandrasekar DR. Network selection using topsis in vertical handover decision schemes for heterogeneous wireless networks[J]. arXiv preprint arXiv:1106.2402,2011.
[34]Chamodrakas I, Martakos D. A utility-based fuzzy TOPSIS method for energy efficient network selection in heterogeneous wireless networks[J]. Applied Soft Computing,2012,12(7):1929-1938.
[35]Bari F, Leung V. Application of ELECTRE to network selection in a hetereogeneous wireless network environment[C]. Proc. of IEEE Wireless Communications and Networking Conference(WCNC),2007:3810-3815.
[36]Savitha K, Chandrasekar C. Trusted network selection using SAW and TOPSIS algorithms for heterogeneous wireless networks[J]. arXiv preprint arXiv:1108.0141,2011.
[37]Sgora A, Chatzimisios P, Vergados DD. Access network selection in a heterogeneous environment using the AHP and fuzzy TOPSIS methods[M]. Mobile Lightweight Wireless Systems. Springer Berlin Heidelberg,2010:88-98.
[38]Lahby M, Cherkaoui L, Adib A. Network selection algorithm based on Diff-AHP and TOPSIS in heterogeneous wireless networks[C]. Proc. of IEEE International Conference on Multimedia Computing and Systems (ICMCS),2012:485-490.
[39]Yang L, Guo D. A satellite heterogeneous network selection algorithm combining AHP and TOPSIS[J].2012.
[40]Charilas DE, Markaki OI, Psarras J, Constantinou P. Application of Fuzzy AHP and ELECTRE to network selection[M]. Mobile Lightweight Wireless Systems. Springer Berlin Heidelberg,2009:63-73.
[41]Klir GJ, Yuan B. Fuzzy sets and fuzzy logic[M]. New Jersey:Prentice Hall,1995.
[42]Hou J, O'Brien DC. Vertical handover-decision-making algorithm using fuzzy logic for the integrated Radio-and-OW system[J]. Wireless Communications, IEEE Transactions on,2006,5(1):176-185.
[43]Radhika K, Reddy AVG. Network selection in heterogeneous wireless networks based on fuzzy multiple criteria decision making[C]. Proc. of IEEE 3rd International Conference on Electronics Computer Technology (ICECT),2011,6: 136-139.
[44]Chamodrakas I, Martakos D. A utility-based fuzzy TOPSIS method for energy efficient network selection in heterogeneous wireless networks[J]. Applied Soft Computing,2012,12(7):1929-1938.
[45]Chang YH, Yeh CH, Chang YW. A new method selection approach for fuzzy group multicriteria decision making[J]. Applied Soft Computing,2013.
[46]Giupponi L, Agusti R, Perez-Romero J, Sallent O. Fuzzy neural control for economic-driven radio resource management in beyond 3G networks[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part C:Applications and Reviews,2009,39(2):170-189.
[47]Fan J, Zhang S, Zhou W. A Semi-distributed Network Selection Scheme in Heterogeneous Wireless Netw.orks[M]. Wireless Internet. Springer Berlin Heidelberg,2012:287-297.
[48]LI M, XU Y, MIAO R. Network selection for cognitive radio based on fuzzy learning[J]. IEICE transactions on communications,2011,94(12):3490-3497.
[49]Han Z, Niyato D, Saad W, Hj(?)rungnes A. Game theory in wireless and communication networks:theory, models, and applications[M]. Cambridge University Press,2011.
[50]Cesana M, Gatti N, Malanchini I. Game theoretic analysis of wireless access network selection:models, inefficiency bounds, and algorithms[C]. Proc. of ICST 3rd International Conference on Performance Evaluation Methodologies and Tools,2008:6.
[51]Niyato D, Hossain E. Dynamics of network selection in heterogeneous wireless networks:an evolutionary game approach[J]. IEEE Transactions on Vehicular Technology,2009,58(4):2008-2017.
[52]Zhu K, Niyato D, Wang P. Network selection in heterogeneous wireless networks: evolution with incomplete information[C]. Proc. of IEEE Wireless Communications and Networking Conference (WCNC),2010.
[53]Xu P, Fang X, Liu X. A non-cooperative pairwise matrices game model for heterogeneous network selection[C]. Proc. of IEEE International Conference on Communications and Mobile Computing (CMC),,2010,3:387-391.
[54]Niyato D, Hossain E. Competitive pricing in heterogeneous wireless access networks:Issues and approaches[J]. IEEE Network,2008,22(6):4-11.
[55]Sibanda CCL, Bagula AB. Network selection for mobile nodes in heterogeneous wireless networks using Knapsack problem Dynamic algorithms[C]. Proc. of IEEE Telecommunications Forum (TELFOR),2012:174-177.
[56]Andersson K, Ahlund C. Optimized access network selection in a combined WLAN/LTE environment[J]. Wireless Personal Communications,2011,61(4): 739-751.
[57]Gelabert X, Perez-Romero J, Sallent O, Agusti R. A Markovian approach to radio access technology selection in heterogeneous multiaccess/multiservice wireless networks[J]. IEEE Transactions on Mobile Computing,2008,7(10):1257-1270.
[58]Niyato D, Hossain E. A cooperative game framework for bandwidth allocation in 4G heterogeneous wireless networks[C]. Proc. of IEEE International Conference on Communications, ICC'06,2006,9:4357-4362.
[59]Niyato D, Hossain E. A noncooperative game-theoretic framework for radio resource management in 4G heterogeneous wireless access networks[J]. IEEE Transactions on Mobile Computing,2008,7(3):332-345.
[60]Niyato D, Hossain E. A game theoretic analysis of service competition and pricing in heterogeneous wireless access networks[J]. IEEE Transactions on Wireless Communications,2008,7(12):5150-5155.
[61]Choi Y, Kim H, Han S, Han Y. Joint resource allocation for parallel multi-radio access in heterogeneous wireless networks[J]. IEEE Transactions on Wireless Communication,2010,9(11):3324-3329.
[62]Sundar RS, Kumar SN. Performance improvement of heterogeneous wireless networks using modified newton method[J]. International Journal of Software Engineering & Applications (IJSEA),2012,3(3):79-90.
[63]Choi Y, Lee Y, Cioffi JM. Optimization of cooperative inter-operability in heterogeneous networks with cognitive ability[J]. IEEE Communications Letters, 2011,15(11):1178-1180.
[64]Mao J, Hu Z, Wang CR, Lian RR, Tian H. Optimal resource allocation for multi-access in heterogeneous wireless networks[C]. Proc. of IEEE Vehicular Technology Conference, Spring,2012.
[65]Mao J, Hu Z, Yang K, Wang CR, Tian H. Joint power and bandwidth allocation algorithm with QoS support in heterogeneous wireless networks[J]. IEEE Communications Letters,2012,16(4):479-481.
[66]Jaffe JM. Bottleneck flow control [J]. IEEE Transactions on Communication, 1981,29(7):954-962.
[67]Kelly FP, Maulloo A, Tan D. Rate control for communication networks:shadow prices, proportional fairness and stability[J]. Journal of Operations Research Society,1998,49(3):237-252.
[68]Jain R. The Art of Computer Systems Performance Analysis:techniques for experimental design, measurement, simulation and modeling[M]. New York, USA:Wiley,1991.
[69]Blau I, Wunder G, Karla I, Sigle R. Decentralized utility maximization in heterogeneous multicell scenarios with interference limited and orthogonal air interfaces[J]. EURASIP Journal on Wireless Communications and Networking, 2009,9(2):470-481.
[70]Wang W, Liu X, Vicente J, Mohapatra P. Integration Gain of Heterogeneous WiFi/WiMAX Networks[J]. IEEE Transactions on Mobile Computing,2011, 10(8):1131-1143.
[71]Nguyen HA, Van NT, Deokjai C. How to maximize user satisfaction degree in multi-service IP networks [C]. Proc. of First Asian Conference on Intelligent Information and Database Systems, Dong Hoi,2009:471-476.
[72]Zhu X, Agrawal P, Singh JP, Alpcan T; Girod B. Distributed rate allocation policies for multihomed video streaming over heterogeneous access networks [J]. IEEE Transactions on Multimedia,2009,11(4):752-764.
[73]Zadeh LA. Fuzzy sets[J]. Information and control,1965,8(3):338-353.
[74]刘增良,刘有才.模糊逻辑与神经网络-理论研究与探索[M].北京航空航天大学出版社,1996.
[75]吴晓莉,林哲辉.MATLAB辅助模糊系统设计[M].西安电子科技大学出版社,2002.
[76]Boyd S, Vandenberghe L. Convex optimization[M]. New York, USA:Cambridge University Press,2004.
[77]Yu W, Lui R. Dual methods for nonconvex spectrum optimization of multicarrier systems[J]. IEEE Transactions on Communications,2006,54(7):1310-1322.
[78]Palomar DP, Chiang M. A tutorial on decomposition methods for network utility maximization[J]. IEEE Journal on Selected Areas in Communications,2006, 24(8):1439-1451.
[79]Lin CT, Lee CSG. Neural-network-based fuzzy logic control and decision system[J]. IEEE Transactions on Computers,1991,40(12):1320-1336.
[80]Shi WX, Fan SS, Wang N, Xia CJ. Fuzzy neural network based access selection algorithm in heterogeneous wireless networks[J]. Journal of China Institute of Communications,2010,31(9):151-156.
[81]Ramesh Babu HS, Gowrishankar SPS. An intelligent fuzzy neural call admission control mechanism for guaranteed QoS in heterogeneous wireless networks[C]. Proc. of the International MultiConference of Engineers and Computer Scientists. 2010,1.
[82]Kim H, Han Y. A proportional fair scheduling for multicarrier transmission systems[J]. IEEE Communications Letter,2005,9(3):210-212.
[83]Li Q, Hu QY, Qian Y, et al. A proportional fair radio resource allocation for heterogeneous cellular networks with relays[C]. Proc. of IEEE Global Communications Conference,2012.
[84]Neely MJ, Modiano E, Li CP. Fairness and optimal stochastic control for heterogeneous networks[J]. IEEE/ACM Transactions on Networking,2008,16(2): 396-409.
[85]Tao M, Liang Y, Zhang F. Resource allocation for delay differentiated traffic in multiuser OFDM systems[J]. IEEE Transactions on Wireless Communication, 2008,7(6):2190-2201.
[86]Boyd S, Xiao L, Mutapcic A. Subgradient Methods[M]. Cambridge University Press, New York, NY, USA,2004.
[87]Parson JD. Mobile Radio Propagation Channel[M].2nd ed. New York:Wiley, 2001.
[88]Shen W, Zeng Q. Resource management schemes for multiple traffic in integrated heterogeneous wireless and mobile networks[C]. Proc. of 17th International Conference on Computer Communications and Networks (ICCCN),2008.
[89]Luo C, Ji H, Li Y. Utility based multi-service bandwidth allocation in the 4G heterogeneous wireless access networks[C]. Proc. of IEEE Wireless Communications and Networking Conference (WCNC),2009.
[90]Pei X, Jiang T, Qu D, Zhu G, Liu J. Radio resource management and access control mechanism based on a novel economic model in heterogeneous wireless networks[J]. IEEE Transactions on Vehicular Technology,2010,59(6): 3047-3056.
[91]Bin L, Wenxiao S, Na L. A hierarchical semi-centralized architecture for load balancing of heterogeneous wireless networks[C]. Proc. of IEEE Networks Security Wireless Communications and Trusted Computing (NSWCTC),2010 Second International Conference on,2010,2:28-31.
[92]Ismail M, Zhuang W. Decentralized radio resource allocation for single-network and multi-homing services in cooperative heterogeneous wireless access medium[J]. IEEE Transactions on Wireless Communications,2012,11(11): 4085-4095.
[93]Ismail M, Zhuang W. A distributed multi-service resource allocation algorithm in heterogeneous wireless access medium[J]. IEEE Journal on Selected Areas In Communications,2012,30(2):425-432.
[94]Ismail M, Abdrabou A, Zhuang W. Cooperative decentralized resource allocation in heterogeneous wireless access medium[J]. IEEE Transactions on Wireless Communication,2013,12(2):714-724.
[95]Goldsmith A. Wireless Communications[M]. Cambridge University Press, New York, USA,2005.
[96]Jang J, Lee KB. Transmit power adaptation for multiuser OFDM systems[J]. IEEE Journal on Selected Areas in Communications,2003,21(2):171-178.
[97]Vivek M. Enhanced wireless mesh networking for ns-2 simulator[J]. ACM SIGCOMM Computer Communication Review,2007,37(3):69-72.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |