异构无线网络中频谱资源动态分配
|
摘要
为了适应不同的通信环境和不断增长的用户业务需求，无线通信技术相继经历了从第一代到第四代的演进，异构无线网络成为无线通信网络发展的必然趋势，其异构性体现在：(1)多种接入技术和接入网共同部署，(2)多层低功率小基站与宏蜂窝基站重叠覆盖，(3)业务类型逐渐多样化，业务分布随时间和空间而变化，(4)无线终端随着认知技术的发展而呈现多频多模的发展趋势。然而，支持无线通信的频谱资源是有限的，传统的频谱固定分配方法造成了资源“紧缺”和“浪费”的矛盾现象。因此在当前的异构无线网络环境下，按业务分布的变化周期进行频谱资源动态分配的研究显得尤为重要，本文对其中的频谱分配算法以及与其息息相关的干扰管理和干扰控制进行了系统的研究。具体内容如下：
1.研究了基于克隆选择优化的频谱动态分配算法。首先，针对不同接入网的基站在重叠覆盖区域造成的干扰，基于基站分布拓扑构造了干扰图和基站干扰矩阵。接着，针对不同接入网对应的不同粒度的信道之间的重叠关系，进一步构造了信道图和信道干扰矩阵。基于基站干扰矩阵和信道干扰矩阵，以相互干扰的基站不能被分配同频信道为约束条件，将频谱分配建模为非线性约束0-1整数规划问题，进而提出了基于克隆选择优化的频谱分配算法，包括在算法步骤中设计了适用于该问题的抗体编码方式，并针对干扰约束条件而增加了抗体修正操作。仿真结果表明，所提算法相比于基于贪婪算法的频谱分配，增加了网络频谱效益，提高了频谱资源利用率。
2.针对每种接入网由六边形小区无缝覆盖的异构无线网络场景，研究了空域干扰约束下的频谱动态分配算法。首先提出基于空域干扰约束的干扰控制模型：对位于小区内某位置的用户而言，将单一接入网中采用固定频谱分配时该用户受到的小区间干扰设置为该用户的最大干扰门限，控制频谱动态分配过程中该用户接收到的干扰不超过此最大干扰门限；进一步限制小区内满足干扰约束的区域(i.e.用户的潜在位置)比例达到基站的覆盖率要求。基于此干扰控制模型，建模并设计两种启发式算法求解频谱分配优化问题，提出了空域干扰约束下的频谱动态分配算法。仿真显示，该算法能在增加网络频谱效益的同时，提高基站的频谱需求满足率。
3.关注基站位置不规则分布的异构无线网络场景，提出了确保覆盖概率的频谱动态分配算法。在仅考虑平均路径损耗的信道条件下，考虑小区内用户的空间分布及不同业务的比例，将用户SINR(signal to interference plus noise ratio)性能巧妙地转化为小区基站的覆盖性能，提出基于覆盖概率的干扰控制模型，从保证基站的覆盖性能出发，达到保证小区内任意位置的用户SINR要求的目的。基于此干扰控制模型，建模频谱分配优化问题，并基于图着色理论提出确保覆盖概率的频谱动态分配算法。与已有算法相比，所提算法能够有效控制基站间干扰，在满足用户SINR门限要求的前提下，增加频谱复用，进而提高网络频谱效益。
4.研究了阴影衰落信道条件下的确保覆盖概率的频谱动态分配算法。忽略背景热噪声，考虑到阴影衰落因子服从对数正态分布，首先近似计算了干扰信号强度以及用户SIR(signal to interference ratio)的概率密度函数，进而分析在阴影衰落信道条件下确保覆盖概率的干扰控制模型，并基于此干扰控制模型，建模和求解频谱分配问题。仿真显示，该算法能够增加频谱复用，提高网络频谱效益，并且在实际信道环境中能有效控制基站之间的干扰和满足用户的SIR要求。
5.在由宏蜂窝和家庭基站组成的双层异构网络中，将频谱资源划分为若干资源块，研究了基于队列状态的资源块分配。首先考虑到基站端为每个下行链路的用户业务设置独立的有限长队列缓存，以避免缓冲队列长度无限增大、保持网络系统稳定为目标，依据李雅普诺夫稳定性理论，建模资源块分配优化问题。接着根据用户业务的缓冲队列状态和基站间干扰关系构造加权干扰图，在将资源块分配优化问题转化为最大加权独立集问题的基础上，提出基于队列状态的资源块分配算法。仿真结果表明，所提算法可以有效匹配资源块和业务队列，保证队列系统稳定，提高系统吞吐量。
The evolution of wireless communication technology brings us a heterogeneouswireless networks (HWNs) environment. The heterogeneity includes: various radioaccess technologies (RATs) and radio access networks (RANs) co-exist; small basestations (BSs) overlap with macro BS; the types of service are more and more rich,and users distribution varies with time and space; multi-band and multi-mode terminal-s are developing with the cognitive radio technology. However, the spectrum resourceis limited. Traditional fixed spectrum allocation approach results in the paradox of re-source”scarcity” and”waste”. Therefore, this dissertation will study dynamic spectrumallocation (DSA) and the related interference control (IC) in the current HWNs scene.The main achievements and results of this dissertation are listed as follows:
1. DSA algorithm based on clonal selection optimization is studied. Since stronginterference will happen in the overlapping area if different BS transmit in the samespectrum band, we first construct interference graph (IG) from BSs distribution topol-ogy. In addition, the channels with various widths for different RANs may overlapwith each other, which is reflected by using channel graph (CG). Note that in orderto achieve the purpose of IC, interfering BSs cannot be allocated the same or over-lapping channels. So based on the constructed IG and CG, the DSA problem is for-mulated as a nonlinear-constrained0-1integer programming. For this problem, theclonal selection optimization-based DSA algorithm is proposed. In the algorithm, wedesign a new coding scheme for the antibody, and add the antibody correction opera-tion for satisfying the constraints. Simulation results show that the proposed algorithmcould improve the network spectrum utility and spectrum utilization compared with thegreedy allocation algorithm.
2. Assuming each RAN in the HWNs deploys hexagonal cells for the seamlesscoverage, we design the DSA algorithm under the spatial interference constraint. First,considering that users may randomly locate over the cell, we propose the spatial inter-ference constraint, in which the interference experienced by the user at a point is con-trolled below the level suffered when using fixed spectrum allocation in only a singlenetwork, and the proportion of the cell area where interference is controlled reachesthe required area coverage probability. Then under the spatial interference constraint,we formulate the DSA problem and propose two greedy heuristic algorithms for its solution. Simulation results show that the DSA algorithm could improve the networkspectrum utility for operators and increase the satisfaction rate of spectrum demandsfor BSs.
3. Concerned about the HWNs scenario where BSs distribution isn’t regular ashexagonal cells, we further design a DSA algorithm with special interest on guar-anteeing the cell coverage probability. First, under the path loss channel condition,considering users spatial distribution and the ratio of different services, we proposecoverage probability-based IC model. This IC model guarantees SINR requirementsof different services and ensures the coverage performance of BSs. Under such an ICmodel, we formulate the DSA problem and design an algorithm for its solution basedon graph coloring. Compared with existing algorithms, the proposed algorithm can in-crease the network spectrum utility while effectively controlling the interference amongBSs and meeting SINR requirements of users.
4. For the case of the shadow fading channel condition, we investigate the cov-erage probability driven DSA algorithm. Ignoring the background thermal noise andconsidering the impact of log-normal shadowing, we first approximate the probabilitydensity function of the interference signal strength and users SIR. Then we analyzethe coverage probability-based IC model under the shadow fading channel condition.Based on the IC model, we solve the DSA problem using the similar approach in the3rd part. Simulation results indicate that this DSA algorithm can increase the spectrumreuse, improve the network spectrum utility, control effectively the interference amongBSs and satisfy the SIR requirements of users under the actual channel condition.
5. In spectrum-sharing hybrid macrocell-femtocell networks, the spectrum re-source is divided into resource blocks, and we design a queue-aware resource alloca-tion scheme. For the downlink transmission, BS maintains a separate queue for eachuser. To keep the length of every queue finite, i.e. stabilize the network, we formulatethe resource allocation optimization problem based on the Lyapunov stability theory.Then considering the queue length and the dominant interference, we construct theweighted interference graph, and solve the resource allocation problem based on themaximum weighted independent set algorithm. Through match the resource block-s and the traffic queue, simulations show the proposed queue-aware algorithm canguarantee the queue-length stability, and improve throughput in the finite-queue trafficmodel.
1.研究了基于克隆选择优化的频谱动态分配算法。首先，针对不同接入网的基站在重叠覆盖区域造成的干扰，基于基站分布拓扑构造了干扰图和基站干扰矩阵。接着，针对不同接入网对应的不同粒度的信道之间的重叠关系，进一步构造了信道图和信道干扰矩阵。基于基站干扰矩阵和信道干扰矩阵，以相互干扰的基站不能被分配同频信道为约束条件，将频谱分配建模为非线性约束0-1整数规划问题，进而提出了基于克隆选择优化的频谱分配算法，包括在算法步骤中设计了适用于该问题的抗体编码方式，并针对干扰约束条件而增加了抗体修正操作。仿真结果表明，所提算法相比于基于贪婪算法的频谱分配，增加了网络频谱效益，提高了频谱资源利用率。
2.针对每种接入网由六边形小区无缝覆盖的异构无线网络场景，研究了空域干扰约束下的频谱动态分配算法。首先提出基于空域干扰约束的干扰控制模型：对位于小区内某位置的用户而言，将单一接入网中采用固定频谱分配时该用户受到的小区间干扰设置为该用户的最大干扰门限，控制频谱动态分配过程中该用户接收到的干扰不超过此最大干扰门限；进一步限制小区内满足干扰约束的区域(i.e.用户的潜在位置)比例达到基站的覆盖率要求。基于此干扰控制模型，建模并设计两种启发式算法求解频谱分配优化问题，提出了空域干扰约束下的频谱动态分配算法。仿真显示，该算法能在增加网络频谱效益的同时，提高基站的频谱需求满足率。
3.关注基站位置不规则分布的异构无线网络场景，提出了确保覆盖概率的频谱动态分配算法。在仅考虑平均路径损耗的信道条件下，考虑小区内用户的空间分布及不同业务的比例，将用户SINR(signal to interference plus noise ratio)性能巧妙地转化为小区基站的覆盖性能，提出基于覆盖概率的干扰控制模型，从保证基站的覆盖性能出发，达到保证小区内任意位置的用户SINR要求的目的。基于此干扰控制模型，建模频谱分配优化问题，并基于图着色理论提出确保覆盖概率的频谱动态分配算法。与已有算法相比，所提算法能够有效控制基站间干扰，在满足用户SINR门限要求的前提下，增加频谱复用，进而提高网络频谱效益。
4.研究了阴影衰落信道条件下的确保覆盖概率的频谱动态分配算法。忽略背景热噪声，考虑到阴影衰落因子服从对数正态分布，首先近似计算了干扰信号强度以及用户SIR(signal to interference ratio)的概率密度函数，进而分析在阴影衰落信道条件下确保覆盖概率的干扰控制模型，并基于此干扰控制模型，建模和求解频谱分配问题。仿真显示，该算法能够增加频谱复用，提高网络频谱效益，并且在实际信道环境中能有效控制基站之间的干扰和满足用户的SIR要求。
5.在由宏蜂窝和家庭基站组成的双层异构网络中，将频谱资源划分为若干资源块，研究了基于队列状态的资源块分配。首先考虑到基站端为每个下行链路的用户业务设置独立的有限长队列缓存，以避免缓冲队列长度无限增大、保持网络系统稳定为目标，依据李雅普诺夫稳定性理论，建模资源块分配优化问题。接着根据用户业务的缓冲队列状态和基站间干扰关系构造加权干扰图，在将资源块分配优化问题转化为最大加权独立集问题的基础上，提出基于队列状态的资源块分配算法。仿真结果表明，所提算法可以有效匹配资源块和业务队列，保证队列系统稳定，提高系统吞吐量。
The evolution of wireless communication technology brings us a heterogeneouswireless networks (HWNs) environment. The heterogeneity includes: various radioaccess technologies (RATs) and radio access networks (RANs) co-exist; small basestations (BSs) overlap with macro BS; the types of service are more and more rich,and users distribution varies with time and space; multi-band and multi-mode terminal-s are developing with the cognitive radio technology. However, the spectrum resourceis limited. Traditional fixed spectrum allocation approach results in the paradox of re-source”scarcity” and”waste”. Therefore, this dissertation will study dynamic spectrumallocation (DSA) and the related interference control (IC) in the current HWNs scene.The main achievements and results of this dissertation are listed as follows:
1. DSA algorithm based on clonal selection optimization is studied. Since stronginterference will happen in the overlapping area if different BS transmit in the samespectrum band, we first construct interference graph (IG) from BSs distribution topol-ogy. In addition, the channels with various widths for different RANs may overlapwith each other, which is reflected by using channel graph (CG). Note that in orderto achieve the purpose of IC, interfering BSs cannot be allocated the same or over-lapping channels. So based on the constructed IG and CG, the DSA problem is for-mulated as a nonlinear-constrained0-1integer programming. For this problem, theclonal selection optimization-based DSA algorithm is proposed. In the algorithm, wedesign a new coding scheme for the antibody, and add the antibody correction opera-tion for satisfying the constraints. Simulation results show that the proposed algorithmcould improve the network spectrum utility and spectrum utilization compared with thegreedy allocation algorithm.
2. Assuming each RAN in the HWNs deploys hexagonal cells for the seamlesscoverage, we design the DSA algorithm under the spatial interference constraint. First,considering that users may randomly locate over the cell, we propose the spatial inter-ference constraint, in which the interference experienced by the user at a point is con-trolled below the level suffered when using fixed spectrum allocation in only a singlenetwork, and the proportion of the cell area where interference is controlled reachesthe required area coverage probability. Then under the spatial interference constraint,we formulate the DSA problem and propose two greedy heuristic algorithms for its solution. Simulation results show that the DSA algorithm could improve the networkspectrum utility for operators and increase the satisfaction rate of spectrum demandsfor BSs.
3. Concerned about the HWNs scenario where BSs distribution isn’t regular ashexagonal cells, we further design a DSA algorithm with special interest on guar-anteeing the cell coverage probability. First, under the path loss channel condition,considering users spatial distribution and the ratio of different services, we proposecoverage probability-based IC model. This IC model guarantees SINR requirementsof different services and ensures the coverage performance of BSs. Under such an ICmodel, we formulate the DSA problem and design an algorithm for its solution basedon graph coloring. Compared with existing algorithms, the proposed algorithm can in-crease the network spectrum utility while effectively controlling the interference amongBSs and meeting SINR requirements of users.
4. For the case of the shadow fading channel condition, we investigate the cov-erage probability driven DSA algorithm. Ignoring the background thermal noise andconsidering the impact of log-normal shadowing, we first approximate the probabilitydensity function of the interference signal strength and users SIR. Then we analyzethe coverage probability-based IC model under the shadow fading channel condition.Based on the IC model, we solve the DSA problem using the similar approach in the3rd part. Simulation results indicate that this DSA algorithm can increase the spectrumreuse, improve the network spectrum utility, control effectively the interference amongBSs and satisfy the SIR requirements of users under the actual channel condition.
5. In spectrum-sharing hybrid macrocell-femtocell networks, the spectrum re-source is divided into resource blocks, and we design a queue-aware resource alloca-tion scheme. For the downlink transmission, BS maintains a separate queue for eachuser. To keep the length of every queue finite, i.e. stabilize the network, we formulatethe resource allocation optimization problem based on the Lyapunov stability theory.Then considering the queue length and the dominant interference, we construct theweighted interference graph, and solve the resource allocation problem based on themaximum weighted independent set algorithm. Through match the resource block-s and the traffic queue, simulations show the proposed queue-aware algorithm canguarantee the queue-length stability, and improve throughput in the finite-queue trafficmodel.
引文
[1] S. R. Theodore,“Wireless Communications: Principles and Practice,” New Jer-sey: Prentice Hall PTR,1996.
[2]李建东,杨家玮,个人通信,北京:人民邮电出版社,1998.
[3]李建东,郭梯云,邬国扬,移动通信(第四版),西安:西安电子科技大学出版社,2006.
[4]杨家玮,盛敏,刘勤,移动通信基础,北京:电子工业出版社,2008.
[5] J. P. Romero, O. Sallent, R. Agusti., et al,“Radio Resource Management Strate-gies in UMTS,” Wiley,2005.
[6]沈嘉,索士强,全海洋等,3GPP长期演进(LTE)技术原理与系统设计,北京:人民邮电出版社,2008.
[7]惠蕾放,无线网络中的资源管理问题研究,西安电子科大学博士论文,2012.
[8]张克平, LTE-B3G/4G移动通信系统无线技术,北京:电子工业出版社,2008.
[9] S. Parkvall, D. Astely,“”The Evolution of LTE towards IMT-Advanced,” J. Com-mun.,4(3), pp.146-154, Apr.2009.
[10] M. Chowdhury, Y. Jang, and Z. Haas,“Network evolution and QoS provisioningfor integrated femtocell/macrocell networks,” Int. J. Wireless Mobile Networks,2(3), pp.1-16, Aug.2010.
[11]3GPP TR36.912V2.0.0,“3rd Generation Partnership Project; Technical Spec-ification Group Radio Access Network; Feasibility study for Further Advance-ments for E-UTRA (LTE-Advanced)(Release9),” Aug.2009.
[12] A. Khandekar, N. Bhushan, T.F. Ji, V. Vanghi,“LTE-Advanced: Heterogeneousnetworks,”2010European Wireless Conference, pp.978-982, Apr.2010.
[13] D. Lopez-Perez, L. Guvenc, G. de la Roche, et al,“Enhanced intercell interfer-ence coordination challenges in heterogeneous networks,” IEEE Wirel. Com-mun.,18(3), pp.22-30, Jun.2011.
[14] V. Chandrasekhar, J. Andrews, A. Gatherer,“Femtocell networks: a survey,”IEEE Commun. Mag.,46(9), pp.59-67, Sept.2008.
[15] J. Mitola, Q. Gerald, J. R. Ma,“Cognitive Radios: Making Software Radios MorePersonal,” IEEE Pers. Commun.,6(4), pp.13-18, Aug.1999.
[16]杨小牛,楼才义,徐建良,软件无线电原理与应用,北京:电子工业出版,2001.
[17] J. Mitola,“Cognitive Radio: An Integated Agent Architeeture for Software De-fined Radio,” Stoekholm, Sweden: Royal Institute of Teelinology(KTH),2000.
[18] FCC,“Facilitating opportunities for flexible, effieient and reliable spectrum useemploying cognitive radio technologies,” ET Docket No.03-322, Dec.2003.
[19] R.W.Thomas, L.A.Dasilva, andA.B.Maekenzie,“Cognitive networks,” in Proc.IEEE DySPAN, pp.352-360, Nov.2005.
[20] P. Demestichas, G. DimitrakoPoulos, J. Strassner, and D. Bourse,“Introducingreconfigurability and cognitive networks concepts in the wireless world,” IEEEVeh.Technol. Mag., l(2), pp.32-39, Jun.2006.
[21] G.L. Sun, G.D. Zhao, J. Qiu, Y.(G.) Li,“Benefits brought by cognitive radio forthe next generation cellular networks: A perspective from industry,” Phy. Com-mun.,5(1), pp.2-9, Mar.2012.
[22] IEEE1900.4,“IEEE Standard for Architectural Building Blocks EnablingNetwork-Device Distributed Decision Making for Optimized Radio Resource Us-age in Heterogeneous Wireless Access Networks,” Feb.2009.
[23]3GPP TSG RAN#45,“Revised SID on LTE-Advaneed (RP-090735),” LTE-Advanced rapporteur (NTT DOCOMO), Sept.2009.
[24] NTIA spectrum allocation chart [Online]. Available:http://www.ntia.doc.gov/osmhome/allochrt.html.
[25] S. Almeida, J. Queijo, L. M. Correia,“Spatial and Temporal Traffic DistributionModels for GSM,” in Proc. IEEE VTC, pp.131-135, Sept.1999.
[26] FCC,“Spectrum policy task force report,” Tech. Rep. ET Docket02-155, Nov.2002.
[27] T. Kamakaris, M. M. Buddhikot, and R. Iyer,“A Case for Coordinated DynamicSpectrum Access in Cellular Networks,” in Proc. IEEE DySPAN, pp.289-298,Nov.2005.
[28] Q. Zhao, B. M. Sadler,“A Survey of Dynamic Spectrum Access,” IEEE SignalProcess. Mag.,24(3), pp.79-89, May2007.
[29] I. F. Akyildiz, W. Lee, M. C. Vuran, and S. Mohanty,“NeXt generation/dynamicspectrum access/cognitive radio wireless networks: A survey,” Comput. Net-works,50(13), pp.2127-2159, Sept.2006.
[30] R. Berry, M. L. Honig, R. Vohra,“Spectrum markets: motivation, challenges,and implications,” IEEE Commun. Mag.,48(11), pp.146-155, Nov.2010.
[31]丁哲,异构可重配置网络无线资源管理关键技术研究,哈尔滨工业大学博士论文,2011.
[32] L. Xu, R. Toenjes, T. Paila, et al,“DRiVE-ing to the Internet: Dynamic Radio forIP Services in Vehicular Environments,” in Proc. IEEE LCN, pp.281-289, Nov.2000.
[33] P. Leaves, S. Ghaheri-Niri, R. Tafazolli, et al,“Dynamic spectrum allocation in amulti-radio environment: concept and algorithm,” IEEE Conference Publication,pp.53-57, Mar.2001.
[34] C. Hamacher,“Required Guard Bands for Co-operation of DVB-T and UMTS,”in Proc. IEEE PIMRC, pp.1550-1554, Sept.2002.
[35] P. Leaves, J. Huschke, R. Tafazolli,“A Summary of Dynamic Spectrum Alloca-tion Results from DRiVE,” in Proc. IST Mobile&Wireless Telecommunica-tionsSummit2002, pp.245-250, Jun.2002.
[36] R. Tonjes, K. Mobner, T. Lohmar, et al,“OverDRiVE-Spectrum Efficient Multi-cast Services to Vehicles,” in Proc. IST Mobile&Wireless TelecommunicationsSummit2002, pp.473-477, Jun.2002.
[37] P. Leaves, S. Ghaheri-Niri, R. Tafazolli, and J. Huschke,“Dynamic spectrumallocation in hybrid networks with imperfect load prediction,” in Proc. Third Inter-national Conference on3G Mobile Communication Technologies, pp.444-448,May2002.
[38] P. Leaves, K. Moessner, R. Tafazolli, et al,“Dynamic spectrum allocation incomposite reconfigurable wireless networks,” IEEE Commun. Mag.,42(5), pp.72-81, May2004.
[39] G. Dimitrakopoulos, K. Moessner, C. Kloeck, et al,“Adaptive Resource Man-agement Platform for Reconfigurable Networks,” Mobile Networks Appl.,11(6),pp.799-811, Dec.2006.
[40] D. Bourse, R. Agusti, P. Ballon, et al,“The E2R II Flexible Spectrum Manage-ment (FSM) Framework and Cognitive Pilot Channel (CPC) Concept-Technicaland Business Analysis and Recommendations,” E2R II White Paper, July2007.
[41] V. Rodriguez, K. Moessner, R. Tafazolli,“Market Driven Dynamic Spectrum Al-location over Space and Time among Radio-Access Networks: DVB-T and B3GCDMA with Heterogeneous Terminals,” Mobile Networks Appl.,11(6), pp.847-860, Dec.2006.
[42] P. Houze, D. Ruiz, S. Ben Jemaa, et al,“Dynamic Spectrum Allocation Algorithmfor Cognitive Networks,” in Proc. ICWMC, Mar.2007.
[43] J. Perez-Romero, O. Sallent, R. Agusti, et al,“A novel on-demand cognitive pilotchannel enabling dynamic spectrum allocation,” in Proc. IEEE DySPAN, pp.46-54, Apr.2007.
[44] A. Kaloxylos, T. Rosowski, K. Tsagkaris, et al,“The E3Architecture for FutureCognitive Mobile Networks,” in Proc. IEEE PIMRC, pp.1601-1605, Sept.2009.
[45] A. Galani, K. Tsagkaris, N. Koutsouris, et al,“Design and Assessment of Func-tional Architecture for Optimized Spectrum and Radio Resource Managementin Heterogeneous Wireless Networks,” Int. J. Network Manage.,20(4), pp.219-241, Aug.2010.
[46] D. Thilakawardana, K. Moessner, R. Tafazolli,“Darwinian approach for dynamicspectrum allocation in next generation systems,” IET Commun.,2(6), pp.827-836, July2008.
[47] J. Nasreddine, J. Perez-Romero, O. Sallent,“Advanced Spectrum Managementfor the Downlink of WCDMA Systems using Genetic Algorithms,” in Proc. IEEEVTC, pp.1-6, Apr.2009.
[48] F. Bernardo, R. Agustí, J. Pérez-Romero, et al,“Dynamic spectrum assignmentin multicell OFDMA networks enabling a secondary spectrum usage,” Wirel.Commun..Mob. Comput.,9(11), pp.1502-1519, Nov.2009.
[49]黎文边,林粤伟,王小猛等,“认知无线网络中基于微观经济学的动态频谱管理算法,”电子与信息学报,31(4), pp.897-902, Apr.2009.
[50] V.B. Le, Z.Y. Feng, D. Bourse, and P. Zhang,“A Cell Based Dynamic Spec-trum Management Scheme with Interference Mitigation for Cognitive Networks,”Wirel. Pers. Commun.,49(2), pp.275-293, Apr.2009.
[51] M. M. Buddhikot, P. Kolodzy, S. Miller, et al,“DIMSUMnet: new directions inwireless networking using coordinated dynamic spectrum,” in Proc. IEEE WoW-MoM, pp.78-85, Jun.2005.
[52] M. M. Buddhikot, and K. Ryan,“Spectrum management in coordinated dynamicspectrum access based cellular networks,” in Proc. IEEE DySPAN, pp.229-307,Nov.2005.
[53] M. M. Buddhikot,“Understanding Dynamic Spectrum Access: Models, Taxono-my and Challenges,” in Proc. IEEE DySPAN, pp.649-663, Apr.2007.
[54] A. P. Subramanian, H. Gupta,“Fast Spectrum Allocation in Coordinated Dy-namic Spectrum Access Based Cellular Networks,” in Proc. IEEE DySPAN, pp.320-330, Apr.2007.
[55] A. P. Subramanian, M. Al-Ayyoub, H. Gupta, et al,“Near-Optimal Dynamic Spec-trum Allocation in Cellular Networks,” in Proc. IEEE DySPAN, pp.323-333, Oct.2008.
[56] ETSI, TR102682, V1.1.1,“Reconfigurable Radio Systems (RRS); Function-al Architecture (FA) for the Management and Control of Reconfigurable RadioSystems,” July2009.
[57] ETSI, TR102838, V1.1.1,“Reconfigurable Radio Systems (RRS); Summary offeasibility studies and potential standardization topics,” Oct.2009.
[58] P. Gupta and P. R. Kumar,“The capacity of wireless networks,” IEEE Trans. Inf.Theory,46(2), pp.388-404, Mar.2000.
[59] C.Y. Peng, H. Zheng, B. Zhao,“Utilization and fairness in spectrum assignmentfor opportunistic spectrum access,” Mobile Networks Appl.,11(4), pp.555-576,Aug.2006.
[60] X. Zhou, S. Gandhi, S. Suri, et al,“eBay in the Sky: strategy-proof wirelessspectrum auctions,” in Proc. ACM MobiCom, pp.2-13, Sept.2008.
[61] J.C. Jia, Q. Zhang, M.Y. Liu,“Revenue generation for truthful spectrum auctionin dynamic spectrum access,” in Proc. ACM MobiHoc, pp.3-12, May2009.
[62] X. Zhou, H. Zheng,“Breaking bidder collusion in large-scale spectrum auctions,”in Proc. ACM MobiHoc, pp.121-130, Sept.2010.
[63] Z.J. Zhao, Z. Peng, S.L. Zheng, et al,“Cognitive radio spectrum allocation us-ing evolutionary algorithms,” IEEE Trans. Wirel. Commun.,8(9), pp.4421-4425,Sept.2009.
[64] L. Kovacs, A. Vidacs,“Interference-Tolerant Spatio-Temporal Dynamic Spec-trum Allocation,” in Proc. IEEE DySPAN, pp.403-411, Apr.2007.
[65] L. Kovacs, A. Vidacs, J. Tapolcai,“Spatio-Temporal Dynamic Spectrum Alloca-tion with Interference Handling,” in Proc. IEEE ICC, pp.5575-5580, Jun.2007.
[66] L. Toka, A. Vidacs,“General distributed economic framework for dynamic spec-trum allocation,” Comput. Commun.,32(18), pp.1955-1964, Dec.2009.
[67] L. Toka, A. Korosi, A. Vidacs,“On Distributed Dynamic Spectrum Allocation forSequential Arrivals,” in Proc. IEEE DySPAN, pp.1-12, Apr.2010.
[68] L Yang, L.L. Cao, H. Zheng,“Physical Interference Driven Dynamic SpectrumManagement,” in Proc. IEEE DySPAN, pp.1-12, Oct.2008.
[69] L.L. Cao, L. Yang, Z. Xia, et al,“Optimus: SINR-Driven Spectrum Distributionvia Constraint Transformation,” in Proc. IEEE DySPAN, pp.1-12, Apr.2010.
[70] G. Alnwaimi, K. Arshad, K. Moessner,“Dynamic Spectrum Allocation Algorithmwith Interference Management in Co-Existing Networks,” IEEE Commun. Lett.,15(9), pp.932-934, Sept.2011.
[71] S. Im, Y. Kang, W. Kim, et al,“Dynamic Spectrum Allocation with Efficient SINR-Based Interference Management,” in Proc. IEEE VTC, pp.1-5, Sept.2011.
[72] Z.Y. Feng, W. Li, Q. Li, et al,“Dynamic Spectrum Management for WCDMA/DVBHeterogeneous Systems,” IEEE Trans. Wirel. Commun.,10(5), pp.1582-1593,May2011.
[73] R. Zhang,“On Peak versus Average Interference Power Constraints for Protect-ing Primary Users in Cognitive Radio Networks,” IEEE Trans. Wirel. Commun.,8(4), pp.2112-2220, Apr.2009.
[74] E. DallAnese, S. J. Kim, G. B. Giannakis, and S. Pupolin,“Power Control forCognitive Radio Networks Under Channel Uncertainty,” IEEE Trans. Wirel. Com-mun.,10(10), pp.3541-3551, Oct.2011.
[75]汪定伟,王俊伟,王洪峤等,智能优化方法,北京:高等教育出版社,2007.
[76] J. G. Andrews, H. Claussen, M. Dohler, et al,“Femtocells: Past, Present, andFuture,” IEEE J. Sel. Areas. Commun.,30(3), pp.497-508, Apr.2012.
[77] D. Knisely, T. Yoshizawa, F. Favichia,“Standardization of femtocells in3GPP,”IEEE Commun. Mag.,47(9), pp.68-75, Sept.2009.
[78] Small cell forum. http://www.smallcellforum.org/.
[79] Informa Telecoms&Media,“Femtocell market status,” Dec.2010.
[80] D. Lopez-Perez, A. Valcarce, G. de la Roche, et al,“OFDMA Femtocells: Aroadmap on interference avoidance,” IEEE Commun. Mag.,47(9), pp.41-48,Sept.2009.
[81] V. Chandrasekhar, J. Andrews,“Spectrum allocation in tiered cellular networks,”IEEE Trans. Commun.,57(10), pp.3059-3068, Oct.2009.
[82] W.C. Cheng, H.L. Zhang, L.Q. Zhao and Y.Z. Li,“Energy Efficient Spectrum Al-location for Green Radio in Two-tier Cellular Networks,” in Proc. IEEE GLOBE-COM, pp.1-5, Dec.2010.
[83] M. Andrews, V. Capdevielle, A. Feki, and P. Gupta,“Autonomous SpectrumSharing For mixed LTE Femto and Macro Cells Deployments,” in Proc. IEEEINFOCOM, pp.1-5, Mar.2010.
[84] G. Guvenc, M.R. Jeong, F. Watanabe, and H. Inamura,“A Hybrid FrequencyAssignment for Femtocells and Coverage Area Analysis for Co-Channel Opera-tion,” IEEE Commun. Lett.,12(12), pp.880-882, Dec.2008.
[85] Y. Bai, J.J. Zhou, and L. Chen,“Hybrid spectrum sharing for coexistence ofmacrocell and Femtocell,” in Proc. IEEE ICCTA, pp.162-166, Oct.2009.
[86] J. Y. Lee, S. J. Bae, Y. M. Kwon, and M. Y. Chung,“Interference Analysisfor Femtocell Deployment in OFDMA Systems Based on Fractional Frequen-cy Reuse,” IEEE Commun. Lett.,15(4), pp.425-427, Apr.2011.
[87] T. D. Novlan, R. K. Ganti, A. Ghosh, and J. G. Andrews,“Analytical Evaluation ofFractional Frequency Reuse for Heterogeneous Cellular Networks,” IEEE Trans.Commun.,60(7), pp.2029-2039, Jul.2012.
[88] C. C. Wang, Q. S. Quek, and K. Marios,“Throughput Optimization, SpectrumAllocation, and Access Control in Two-Tier Femtocell Networks,” IEEE J. Sel.Areas. Commun.,30(3), pp.561-574, Apr.2012.
[89] V. Chandrasekhar, J.G. Andrews, T. Muharemovic, et al,“Power control in two-tier femtocell networks,” IEEE Trans. Wirel. Commun.,8(8), pp.4316-4328, Aug.2009.
[90] X. Kang, R. Zhang, and M. Motani,“Price-Based Resource Allocation forSpectrum-Sharing Femtocell Networks: A Stackelberg Game Approach,” IEEEJ. Sel. Areas. Commun.,30(3), pp.538-549, Apr.2012.
[91] S. M. Cheng, W. Chon Ao, F. M. Tseng, and K. C. Chen,“Design and Analysisof Downlink Spectrum Sharing in Two-Tier Cognitive Femto Networks,” IEEETrans. Veh. Technol.,61(5), pp.2194-2207, Jun.2012.
[92] K. Zheng, Y. Wang, C. Lin, et al,“Graph-based interference coordinationscheme in orthogonal frequency-division multiplexing access femtocell network-s,” IET Commun.,5(17), pp.2533-2541, Nov.2011.
[93] M. Y. Arslan,.J. Yoon, K. Sundaresan, et al,“A Resource Management Systemfor Interference Mitigation in Enterprise OFDMA Femtocells,” IEEE ACM Trans.Networking, Article in Press, Nov.2012.
[94] W. Li, T. Su, W. Zheng, and X.M. Wen,“Clustering Based Resource Allocationfor Inter-femtocell Interference Management,” J. Comput. Inf. Syst.,8(4), pp.1457-1466, Apr.2012.
[95] P. Lin, J. Zhang, Q Zhang, and M. Hamdi,“Revenue Improvement for WirelessService Providers in Hybrid Macrocell-Femtocell Networks,” IEEE Trans. Veh.Technol.,61(9), pp.4109-4117, Nov.2012.
[96] Y. S. Liang, W. H. Chung, G. K. Ni,et al,“Resource Allocation with InterferenceAvoidance in OFDMA Femtocell Networks,” IEEE Trans. Veh. Technol.,61(5),pp.2243-2255, Jun.2012.
[97] Z. Lu, T. Bansal, P. Sinha,“Achieving User-Level Fairness in Open-Access Fem-tocell based Architecture,” IEEE Trans. Mob. Comput.,12(10), pp.1943-1954,Oct.2013.
[98] J. Kim,, D. H. Cho,“A joint power and subchannel allocation scheme maxi-mizing system capacity in dense femtocell downlink systems,” IEEE Trans. Veh.Technol.,59(9), pp.4340-4353, Nov.2010.
[99] K. Lee, O. Jo, and D. H. Cho,“Cooperative Resource Allocation for Guarantee-ing Intercell Fairness in Femtocell Networks,” IEEE Commun. Lett.,15(2), pp.214-216, Feb.2011.
[100] J. Xiang, Y. Zhang, T. Skeie, and L. Xie,“Downlink Spectrum Sharing for Cogni-tive Radio Femtocell Networks,” IEEE Syst. J.,4(4), pp.524-534, Dec.2010.
[101] L. Li, C.Q. Xu, and M.X. Tao,“Resource Allocation in Open Access OFDMAFemtocell Networks,” IEEE Wirel. Commun. Lett.,1(6), pp.625-628, Dec.2012.
[102] H. Zhang, W. Zheng, X. Chu, et al,“Joint Subchannel and Power Allocation inInterference-Limited OFDMA Femtocells with Heterogeneous QoS Guarantee,”in Proc. IEEE Globecom, pp.4572-4577, Dec.2012.
[103] H.J. Zhang, X.L. Chu, W. Zheng, et al,“Interference-Aware Resource Allocationin Co-Channel Deployment of OFDMA Femtocells,” in Proc. IEEE ICC, pp.4663-4667, Jun.2012.
[104] V.H. Nguyen, and L.B. Le,“Distributed Resource Allocation for OFDMA Femto-cell Networks with Macrocell Protection,” in Proc. IEEE WCNC, pp.440-445,Apr.2013.
[105] J. W. Huang, and V. Krishnamurthy,“Cognitive Base Stations in LTE/3GPP Fem-tocells: A Correlated Equilibrium Game-Theoretic Approach,” IEEE Trans. Com-mun.,59(12), pp3485-3493, Dec.2011.
[106] D. Lopez-Perez, X.L. Chu, A. V. Vasilakos, and Holger Claussen,“Power Mini-mization Based Resource Allocation for Interference Mitigation in OFDMA Fem-tocell Networks,” IEEE J. Sel. Areas Commun., pp.1-12, May2013.
[107]柴争义,刘芳,“基于免疫克隆选择优化的认知无线网络频谱分配,”通信学报,31(11), pp.92-100, Nov.2010.
[108]王晓飞,陈岳兵,张希等,“基于免疫克隆选择的认知无线网络频谱分配研究,”电子与信息学报,33(7), pp.1561-1567, Jul.2011.
[109]杨淼,安建平,“认知无线网络中一种基于蚁群优化的频谱分配算法,”电子与信息学报,33(10), pp.2306-2311, Oct.2011.
[110] S. Hurley,“Planning effective cellular mobile radio networks,” IEEE Trans.Veh.Technol.,51(2), pp.243-253, Mar.2002.
[111] F. Luna, C. Blum, E. Alba, et al,“ACO vs EAs for solving a real-world frequencyassignment problem in GSM networks,” in Proc. ACM GECCO, pp.94-101, Jul.2007.
[112] H. Kamal, M. Coupechoux, P. Godlewski,“A Tabu Search DSA algorithm forreward maximization in cellular networks,” in Proc. IEEE WiMob, pp.40-45, Oct.2010.
[113]焦李成,杜海峰,刘芳,公茂果,免疫优化计算、学习与识别,北京:科学出版社,2007.
[114] L. N. de Castro, F. J. Von Zuben,“Learning and optimization using the clonalselection principle,” IEEE Trans. Evol. Comput.,6(3), pp.239-251, Jun.2002.
[115] P. J. Kolodzy,“Interference temperature: a metric for dynamic spectrum utiliza-tion,” Int. J. Network Manage.,16(2), pp.103-113, Mar./Apr.2006.
[116] T.C. Clancy,“Formalizing the interference temperature model,” Wirel. Commun.Mob. Comput.,7(9), pp.1077-1086, Nov.2007.
[117] Y. Xing, C. N. Mathur, M. A. Haleem, et al,“Dynamic spectrum access with QoSand interference temperature constraints,” IEEE Trans. Mob. Comput.,6(4), pp.423-433, April2007.
[118] C. Ghosh, S. Roy, D. Cavalcant,“Coexistence challenges for heterogeneouscognitive wireless networks in TV white spaces,” IEEE Wirel. Commun.,18(4),pp.22-31, Aug.2011.
[119]徐玖平,李军,多目标决策的理论与方法,北京：清华大学出版社,2005.
[120]同济大学数学系编,高等数学(上册)(第6版),北京：高等教育出版社,2007.
[121] R. Prasad, and Adriaan Kegel,“Improved Assessment of Interference Limits inCellular Radio Performance,” IEEE Trans. Veh. Technol.,40(2), pp.412-419,May1991.
[122] A. A. Abu-Dayya, and N. C. Beaulieu,“Outage Probabilities in the Presence ofCorrelated Lognormal Interferers,” IEEE Trans. Veh. Technol.,43(1), pp.164-173, Feb.1994.
[123] M. Pratesi, F. Santucci, and F. Graziosi,“Generalized moment matching for thelinear combination of lognormal RVs: application to outage analysis in wirelesssystems,” IEEE Trans. Wireless Commun.,5(5), pp.1122-1132, May2006.
[124] K. Sundaresan and S. Rangarajan,“Efficient Resource Management in OFDMAFemto Cells,” in Proc. ACM Mobihoc, pp.33-42, May2009.
[125] M. Arslan, J. Yoon, K. Sundaresan, et al,”FERMI: A Femtocell Resource Man-agement System for Interference Mitigation in OFDMA Networks,” in Proc. ACMMobiCom, pp.25-36, Sept.2011.
[126] M. Andrews, and L. Zhang,“Scheduling Algorithms for MultiCarrier WirelessData Systems,” IEEE/ACM Trans. Networking,19(2), pp.447-55, Apr.2011.
[127] G. Song, and Y. Li,“Cross-layer optimization for OFDM wireless networks-part I:theoretical framework,” IEEE Trans. Wireless Commun.,4(2), pp.614-624, Mar.2005.
[128] J. Jang, and K.B. Lee,“Transmit power adaptation for multiuser OFDM systems,”IEEE J. Sel. Areas Commun.,21(2), pp.171-178, Feb.2003.
[129] M. J. Neely, Stochastic network optimization with application to communicationand queueing systems, Morgan&Claypool Publishers,2010.
[130] L. Tassiulas, and A. Ephremides,“Stability properties of constrained queueingsystems and scheduling policies for maximum throughput in multihop radio net-works,” IEEE Trans. Autom. Control,37(12), pp.1936-1948, Dec.1992.
[131] S. Sakai, M. Togasaki, and K. Yamazaki,“A note on greedy algorithms for themaximum weighted independent set problem,” Discrete Appl. Math.,126(2-3),pp.313-322, Mar.2003.
[132] L. Cao, and H. Zheng,“Distributed Spectrum Allocation via Local Bargaining,”in Proc. IEEE SECON, pp.475-486, Sept.2005.
[2]李建东,杨家玮,个人通信,北京:人民邮电出版社,1998.
[3]李建东,郭梯云,邬国扬,移动通信(第四版),西安:西安电子科技大学出版社,2006.
[4]杨家玮,盛敏,刘勤,移动通信基础,北京:电子工业出版社,2008.
[5] J. P. Romero, O. Sallent, R. Agusti., et al,“Radio Resource Management Strate-gies in UMTS,” Wiley,2005.
[6]沈嘉,索士强,全海洋等,3GPP长期演进(LTE)技术原理与系统设计,北京:人民邮电出版社,2008.
[7]惠蕾放,无线网络中的资源管理问题研究,西安电子科大学博士论文,2012.
[8]张克平, LTE-B3G/4G移动通信系统无线技术,北京:电子工业出版社,2008.
[9] S. Parkvall, D. Astely,“”The Evolution of LTE towards IMT-Advanced,” J. Com-mun.,4(3), pp.146-154, Apr.2009.
[10] M. Chowdhury, Y. Jang, and Z. Haas,“Network evolution and QoS provisioningfor integrated femtocell/macrocell networks,” Int. J. Wireless Mobile Networks,2(3), pp.1-16, Aug.2010.
[11]3GPP TR36.912V2.0.0,“3rd Generation Partnership Project; Technical Spec-ification Group Radio Access Network; Feasibility study for Further Advance-ments for E-UTRA (LTE-Advanced)(Release9),” Aug.2009.
[12] A. Khandekar, N. Bhushan, T.F. Ji, V. Vanghi,“LTE-Advanced: Heterogeneousnetworks,”2010European Wireless Conference, pp.978-982, Apr.2010.
[13] D. Lopez-Perez, L. Guvenc, G. de la Roche, et al,“Enhanced intercell interfer-ence coordination challenges in heterogeneous networks,” IEEE Wirel. Com-mun.,18(3), pp.22-30, Jun.2011.
[14] V. Chandrasekhar, J. Andrews, A. Gatherer,“Femtocell networks: a survey,”IEEE Commun. Mag.,46(9), pp.59-67, Sept.2008.
[15] J. Mitola, Q. Gerald, J. R. Ma,“Cognitive Radios: Making Software Radios MorePersonal,” IEEE Pers. Commun.,6(4), pp.13-18, Aug.1999.
[16]杨小牛,楼才义,徐建良,软件无线电原理与应用,北京:电子工业出版,2001.
[17] J. Mitola,“Cognitive Radio: An Integated Agent Architeeture for Software De-fined Radio,” Stoekholm, Sweden: Royal Institute of Teelinology(KTH),2000.
[18] FCC,“Facilitating opportunities for flexible, effieient and reliable spectrum useemploying cognitive radio technologies,” ET Docket No.03-322, Dec.2003.
[19] R.W.Thomas, L.A.Dasilva, andA.B.Maekenzie,“Cognitive networks,” in Proc.IEEE DySPAN, pp.352-360, Nov.2005.
[20] P. Demestichas, G. DimitrakoPoulos, J. Strassner, and D. Bourse,“Introducingreconfigurability and cognitive networks concepts in the wireless world,” IEEEVeh.Technol. Mag., l(2), pp.32-39, Jun.2006.
[21] G.L. Sun, G.D. Zhao, J. Qiu, Y.(G.) Li,“Benefits brought by cognitive radio forthe next generation cellular networks: A perspective from industry,” Phy. Com-mun.,5(1), pp.2-9, Mar.2012.
[22] IEEE1900.4,“IEEE Standard for Architectural Building Blocks EnablingNetwork-Device Distributed Decision Making for Optimized Radio Resource Us-age in Heterogeneous Wireless Access Networks,” Feb.2009.
[23]3GPP TSG RAN#45,“Revised SID on LTE-Advaneed (RP-090735),” LTE-Advanced rapporteur (NTT DOCOMO), Sept.2009.
[24] NTIA spectrum allocation chart [Online]. Available:http://www.ntia.doc.gov/osmhome/allochrt.html.
[25] S. Almeida, J. Queijo, L. M. Correia,“Spatial and Temporal Traffic DistributionModels for GSM,” in Proc. IEEE VTC, pp.131-135, Sept.1999.
[26] FCC,“Spectrum policy task force report,” Tech. Rep. ET Docket02-155, Nov.2002.
[27] T. Kamakaris, M. M. Buddhikot, and R. Iyer,“A Case for Coordinated DynamicSpectrum Access in Cellular Networks,” in Proc. IEEE DySPAN, pp.289-298,Nov.2005.
[28] Q. Zhao, B. M. Sadler,“A Survey of Dynamic Spectrum Access,” IEEE SignalProcess. Mag.,24(3), pp.79-89, May2007.
[29] I. F. Akyildiz, W. Lee, M. C. Vuran, and S. Mohanty,“NeXt generation/dynamicspectrum access/cognitive radio wireless networks: A survey,” Comput. Net-works,50(13), pp.2127-2159, Sept.2006.
[30] R. Berry, M. L. Honig, R. Vohra,“Spectrum markets: motivation, challenges,and implications,” IEEE Commun. Mag.,48(11), pp.146-155, Nov.2010.
[31]丁哲,异构可重配置网络无线资源管理关键技术研究,哈尔滨工业大学博士论文,2011.
[32] L. Xu, R. Toenjes, T. Paila, et al,“DRiVE-ing to the Internet: Dynamic Radio forIP Services in Vehicular Environments,” in Proc. IEEE LCN, pp.281-289, Nov.2000.
[33] P. Leaves, S. Ghaheri-Niri, R. Tafazolli, et al,“Dynamic spectrum allocation in amulti-radio environment: concept and algorithm,” IEEE Conference Publication,pp.53-57, Mar.2001.
[34] C. Hamacher,“Required Guard Bands for Co-operation of DVB-T and UMTS,”in Proc. IEEE PIMRC, pp.1550-1554, Sept.2002.
[35] P. Leaves, J. Huschke, R. Tafazolli,“A Summary of Dynamic Spectrum Alloca-tion Results from DRiVE,” in Proc. IST Mobile&Wireless Telecommunica-tionsSummit2002, pp.245-250, Jun.2002.
[36] R. Tonjes, K. Mobner, T. Lohmar, et al,“OverDRiVE-Spectrum Efficient Multi-cast Services to Vehicles,” in Proc. IST Mobile&Wireless TelecommunicationsSummit2002, pp.473-477, Jun.2002.
[37] P. Leaves, S. Ghaheri-Niri, R. Tafazolli, and J. Huschke,“Dynamic spectrumallocation in hybrid networks with imperfect load prediction,” in Proc. Third Inter-national Conference on3G Mobile Communication Technologies, pp.444-448,May2002.
[38] P. Leaves, K. Moessner, R. Tafazolli, et al,“Dynamic spectrum allocation incomposite reconfigurable wireless networks,” IEEE Commun. Mag.,42(5), pp.72-81, May2004.
[39] G. Dimitrakopoulos, K. Moessner, C. Kloeck, et al,“Adaptive Resource Man-agement Platform for Reconfigurable Networks,” Mobile Networks Appl.,11(6),pp.799-811, Dec.2006.
[40] D. Bourse, R. Agusti, P. Ballon, et al,“The E2R II Flexible Spectrum Manage-ment (FSM) Framework and Cognitive Pilot Channel (CPC) Concept-Technicaland Business Analysis and Recommendations,” E2R II White Paper, July2007.
[41] V. Rodriguez, K. Moessner, R. Tafazolli,“Market Driven Dynamic Spectrum Al-location over Space and Time among Radio-Access Networks: DVB-T and B3GCDMA with Heterogeneous Terminals,” Mobile Networks Appl.,11(6), pp.847-860, Dec.2006.
[42] P. Houze, D. Ruiz, S. Ben Jemaa, et al,“Dynamic Spectrum Allocation Algorithmfor Cognitive Networks,” in Proc. ICWMC, Mar.2007.
[43] J. Perez-Romero, O. Sallent, R. Agusti, et al,“A novel on-demand cognitive pilotchannel enabling dynamic spectrum allocation,” in Proc. IEEE DySPAN, pp.46-54, Apr.2007.
[44] A. Kaloxylos, T. Rosowski, K. Tsagkaris, et al,“The E3Architecture for FutureCognitive Mobile Networks,” in Proc. IEEE PIMRC, pp.1601-1605, Sept.2009.
[45] A. Galani, K. Tsagkaris, N. Koutsouris, et al,“Design and Assessment of Func-tional Architecture for Optimized Spectrum and Radio Resource Managementin Heterogeneous Wireless Networks,” Int. J. Network Manage.,20(4), pp.219-241, Aug.2010.
[46] D. Thilakawardana, K. Moessner, R. Tafazolli,“Darwinian approach for dynamicspectrum allocation in next generation systems,” IET Commun.,2(6), pp.827-836, July2008.
[47] J. Nasreddine, J. Perez-Romero, O. Sallent,“Advanced Spectrum Managementfor the Downlink of WCDMA Systems using Genetic Algorithms,” in Proc. IEEEVTC, pp.1-6, Apr.2009.
[48] F. Bernardo, R. Agustí, J. Pérez-Romero, et al,“Dynamic spectrum assignmentin multicell OFDMA networks enabling a secondary spectrum usage,” Wirel.Commun..Mob. Comput.,9(11), pp.1502-1519, Nov.2009.
[49]黎文边,林粤伟,王小猛等,“认知无线网络中基于微观经济学的动态频谱管理算法,”电子与信息学报,31(4), pp.897-902, Apr.2009.
[50] V.B. Le, Z.Y. Feng, D. Bourse, and P. Zhang,“A Cell Based Dynamic Spec-trum Management Scheme with Interference Mitigation for Cognitive Networks,”Wirel. Pers. Commun.,49(2), pp.275-293, Apr.2009.
[51] M. M. Buddhikot, P. Kolodzy, S. Miller, et al,“DIMSUMnet: new directions inwireless networking using coordinated dynamic spectrum,” in Proc. IEEE WoW-MoM, pp.78-85, Jun.2005.
[52] M. M. Buddhikot, and K. Ryan,“Spectrum management in coordinated dynamicspectrum access based cellular networks,” in Proc. IEEE DySPAN, pp.229-307,Nov.2005.
[53] M. M. Buddhikot,“Understanding Dynamic Spectrum Access: Models, Taxono-my and Challenges,” in Proc. IEEE DySPAN, pp.649-663, Apr.2007.
[54] A. P. Subramanian, H. Gupta,“Fast Spectrum Allocation in Coordinated Dy-namic Spectrum Access Based Cellular Networks,” in Proc. IEEE DySPAN, pp.320-330, Apr.2007.
[55] A. P. Subramanian, M. Al-Ayyoub, H. Gupta, et al,“Near-Optimal Dynamic Spec-trum Allocation in Cellular Networks,” in Proc. IEEE DySPAN, pp.323-333, Oct.2008.
[56] ETSI, TR102682, V1.1.1,“Reconfigurable Radio Systems (RRS); Function-al Architecture (FA) for the Management and Control of Reconfigurable RadioSystems,” July2009.
[57] ETSI, TR102838, V1.1.1,“Reconfigurable Radio Systems (RRS); Summary offeasibility studies and potential standardization topics,” Oct.2009.
[58] P. Gupta and P. R. Kumar,“The capacity of wireless networks,” IEEE Trans. Inf.Theory,46(2), pp.388-404, Mar.2000.
[59] C.Y. Peng, H. Zheng, B. Zhao,“Utilization and fairness in spectrum assignmentfor opportunistic spectrum access,” Mobile Networks Appl.,11(4), pp.555-576,Aug.2006.
[60] X. Zhou, S. Gandhi, S. Suri, et al,“eBay in the Sky: strategy-proof wirelessspectrum auctions,” in Proc. ACM MobiCom, pp.2-13, Sept.2008.
[61] J.C. Jia, Q. Zhang, M.Y. Liu,“Revenue generation for truthful spectrum auctionin dynamic spectrum access,” in Proc. ACM MobiHoc, pp.3-12, May2009.
[62] X. Zhou, H. Zheng,“Breaking bidder collusion in large-scale spectrum auctions,”in Proc. ACM MobiHoc, pp.121-130, Sept.2010.
[63] Z.J. Zhao, Z. Peng, S.L. Zheng, et al,“Cognitive radio spectrum allocation us-ing evolutionary algorithms,” IEEE Trans. Wirel. Commun.,8(9), pp.4421-4425,Sept.2009.
[64] L. Kovacs, A. Vidacs,“Interference-Tolerant Spatio-Temporal Dynamic Spec-trum Allocation,” in Proc. IEEE DySPAN, pp.403-411, Apr.2007.
[65] L. Kovacs, A. Vidacs, J. Tapolcai,“Spatio-Temporal Dynamic Spectrum Alloca-tion with Interference Handling,” in Proc. IEEE ICC, pp.5575-5580, Jun.2007.
[66] L. Toka, A. Vidacs,“General distributed economic framework for dynamic spec-trum allocation,” Comput. Commun.,32(18), pp.1955-1964, Dec.2009.
[67] L. Toka, A. Korosi, A. Vidacs,“On Distributed Dynamic Spectrum Allocation forSequential Arrivals,” in Proc. IEEE DySPAN, pp.1-12, Apr.2010.
[68] L Yang, L.L. Cao, H. Zheng,“Physical Interference Driven Dynamic SpectrumManagement,” in Proc. IEEE DySPAN, pp.1-12, Oct.2008.
[69] L.L. Cao, L. Yang, Z. Xia, et al,“Optimus: SINR-Driven Spectrum Distributionvia Constraint Transformation,” in Proc. IEEE DySPAN, pp.1-12, Apr.2010.
[70] G. Alnwaimi, K. Arshad, K. Moessner,“Dynamic Spectrum Allocation Algorithmwith Interference Management in Co-Existing Networks,” IEEE Commun. Lett.,15(9), pp.932-934, Sept.2011.
[71] S. Im, Y. Kang, W. Kim, et al,“Dynamic Spectrum Allocation with Efficient SINR-Based Interference Management,” in Proc. IEEE VTC, pp.1-5, Sept.2011.
[72] Z.Y. Feng, W. Li, Q. Li, et al,“Dynamic Spectrum Management for WCDMA/DVBHeterogeneous Systems,” IEEE Trans. Wirel. Commun.,10(5), pp.1582-1593,May2011.
[73] R. Zhang,“On Peak versus Average Interference Power Constraints for Protect-ing Primary Users in Cognitive Radio Networks,” IEEE Trans. Wirel. Commun.,8(4), pp.2112-2220, Apr.2009.
[74] E. DallAnese, S. J. Kim, G. B. Giannakis, and S. Pupolin,“Power Control forCognitive Radio Networks Under Channel Uncertainty,” IEEE Trans. Wirel. Com-mun.,10(10), pp.3541-3551, Oct.2011.
[75]汪定伟,王俊伟,王洪峤等,智能优化方法,北京:高等教育出版社,2007.
[76] J. G. Andrews, H. Claussen, M. Dohler, et al,“Femtocells: Past, Present, andFuture,” IEEE J. Sel. Areas. Commun.,30(3), pp.497-508, Apr.2012.
[77] D. Knisely, T. Yoshizawa, F. Favichia,“Standardization of femtocells in3GPP,”IEEE Commun. Mag.,47(9), pp.68-75, Sept.2009.
[78] Small cell forum. http://www.smallcellforum.org/.
[79] Informa Telecoms&Media,“Femtocell market status,” Dec.2010.
[80] D. Lopez-Perez, A. Valcarce, G. de la Roche, et al,“OFDMA Femtocells: Aroadmap on interference avoidance,” IEEE Commun. Mag.,47(9), pp.41-48,Sept.2009.
[81] V. Chandrasekhar, J. Andrews,“Spectrum allocation in tiered cellular networks,”IEEE Trans. Commun.,57(10), pp.3059-3068, Oct.2009.
[82] W.C. Cheng, H.L. Zhang, L.Q. Zhao and Y.Z. Li,“Energy Efficient Spectrum Al-location for Green Radio in Two-tier Cellular Networks,” in Proc. IEEE GLOBE-COM, pp.1-5, Dec.2010.
[83] M. Andrews, V. Capdevielle, A. Feki, and P. Gupta,“Autonomous SpectrumSharing For mixed LTE Femto and Macro Cells Deployments,” in Proc. IEEEINFOCOM, pp.1-5, Mar.2010.
[84] G. Guvenc, M.R. Jeong, F. Watanabe, and H. Inamura,“A Hybrid FrequencyAssignment for Femtocells and Coverage Area Analysis for Co-Channel Opera-tion,” IEEE Commun. Lett.,12(12), pp.880-882, Dec.2008.
[85] Y. Bai, J.J. Zhou, and L. Chen,“Hybrid spectrum sharing for coexistence ofmacrocell and Femtocell,” in Proc. IEEE ICCTA, pp.162-166, Oct.2009.
[86] J. Y. Lee, S. J. Bae, Y. M. Kwon, and M. Y. Chung,“Interference Analysisfor Femtocell Deployment in OFDMA Systems Based on Fractional Frequen-cy Reuse,” IEEE Commun. Lett.,15(4), pp.425-427, Apr.2011.
[87] T. D. Novlan, R. K. Ganti, A. Ghosh, and J. G. Andrews,“Analytical Evaluation ofFractional Frequency Reuse for Heterogeneous Cellular Networks,” IEEE Trans.Commun.,60(7), pp.2029-2039, Jul.2012.
[88] C. C. Wang, Q. S. Quek, and K. Marios,“Throughput Optimization, SpectrumAllocation, and Access Control in Two-Tier Femtocell Networks,” IEEE J. Sel.Areas. Commun.,30(3), pp.561-574, Apr.2012.
[89] V. Chandrasekhar, J.G. Andrews, T. Muharemovic, et al,“Power control in two-tier femtocell networks,” IEEE Trans. Wirel. Commun.,8(8), pp.4316-4328, Aug.2009.
[90] X. Kang, R. Zhang, and M. Motani,“Price-Based Resource Allocation forSpectrum-Sharing Femtocell Networks: A Stackelberg Game Approach,” IEEEJ. Sel. Areas. Commun.,30(3), pp.538-549, Apr.2012.
[91] S. M. Cheng, W. Chon Ao, F. M. Tseng, and K. C. Chen,“Design and Analysisof Downlink Spectrum Sharing in Two-Tier Cognitive Femto Networks,” IEEETrans. Veh. Technol.,61(5), pp.2194-2207, Jun.2012.
[92] K. Zheng, Y. Wang, C. Lin, et al,“Graph-based interference coordinationscheme in orthogonal frequency-division multiplexing access femtocell network-s,” IET Commun.,5(17), pp.2533-2541, Nov.2011.
[93] M. Y. Arslan,.J. Yoon, K. Sundaresan, et al,“A Resource Management Systemfor Interference Mitigation in Enterprise OFDMA Femtocells,” IEEE ACM Trans.Networking, Article in Press, Nov.2012.
[94] W. Li, T. Su, W. Zheng, and X.M. Wen,“Clustering Based Resource Allocationfor Inter-femtocell Interference Management,” J. Comput. Inf. Syst.,8(4), pp.1457-1466, Apr.2012.
[95] P. Lin, J. Zhang, Q Zhang, and M. Hamdi,“Revenue Improvement for WirelessService Providers in Hybrid Macrocell-Femtocell Networks,” IEEE Trans. Veh.Technol.,61(9), pp.4109-4117, Nov.2012.
[96] Y. S. Liang, W. H. Chung, G. K. Ni,et al,“Resource Allocation with InterferenceAvoidance in OFDMA Femtocell Networks,” IEEE Trans. Veh. Technol.,61(5),pp.2243-2255, Jun.2012.
[97] Z. Lu, T. Bansal, P. Sinha,“Achieving User-Level Fairness in Open-Access Fem-tocell based Architecture,” IEEE Trans. Mob. Comput.,12(10), pp.1943-1954,Oct.2013.
[98] J. Kim,, D. H. Cho,“A joint power and subchannel allocation scheme maxi-mizing system capacity in dense femtocell downlink systems,” IEEE Trans. Veh.Technol.,59(9), pp.4340-4353, Nov.2010.
[99] K. Lee, O. Jo, and D. H. Cho,“Cooperative Resource Allocation for Guarantee-ing Intercell Fairness in Femtocell Networks,” IEEE Commun. Lett.,15(2), pp.214-216, Feb.2011.
[100] J. Xiang, Y. Zhang, T. Skeie, and L. Xie,“Downlink Spectrum Sharing for Cogni-tive Radio Femtocell Networks,” IEEE Syst. J.,4(4), pp.524-534, Dec.2010.
[101] L. Li, C.Q. Xu, and M.X. Tao,“Resource Allocation in Open Access OFDMAFemtocell Networks,” IEEE Wirel. Commun. Lett.,1(6), pp.625-628, Dec.2012.
[102] H. Zhang, W. Zheng, X. Chu, et al,“Joint Subchannel and Power Allocation inInterference-Limited OFDMA Femtocells with Heterogeneous QoS Guarantee,”in Proc. IEEE Globecom, pp.4572-4577, Dec.2012.
[103] H.J. Zhang, X.L. Chu, W. Zheng, et al,“Interference-Aware Resource Allocationin Co-Channel Deployment of OFDMA Femtocells,” in Proc. IEEE ICC, pp.4663-4667, Jun.2012.
[104] V.H. Nguyen, and L.B. Le,“Distributed Resource Allocation for OFDMA Femto-cell Networks with Macrocell Protection,” in Proc. IEEE WCNC, pp.440-445,Apr.2013.
[105] J. W. Huang, and V. Krishnamurthy,“Cognitive Base Stations in LTE/3GPP Fem-tocells: A Correlated Equilibrium Game-Theoretic Approach,” IEEE Trans. Com-mun.,59(12), pp3485-3493, Dec.2011.
[106] D. Lopez-Perez, X.L. Chu, A. V. Vasilakos, and Holger Claussen,“Power Mini-mization Based Resource Allocation for Interference Mitigation in OFDMA Fem-tocell Networks,” IEEE J. Sel. Areas Commun., pp.1-12, May2013.
[107]柴争义,刘芳,“基于免疫克隆选择优化的认知无线网络频谱分配,”通信学报,31(11), pp.92-100, Nov.2010.
[108]王晓飞,陈岳兵,张希等,“基于免疫克隆选择的认知无线网络频谱分配研究,”电子与信息学报,33(7), pp.1561-1567, Jul.2011.
[109]杨淼,安建平,“认知无线网络中一种基于蚁群优化的频谱分配算法,”电子与信息学报,33(10), pp.2306-2311, Oct.2011.
[110] S. Hurley,“Planning effective cellular mobile radio networks,” IEEE Trans.Veh.Technol.,51(2), pp.243-253, Mar.2002.
[111] F. Luna, C. Blum, E. Alba, et al,“ACO vs EAs for solving a real-world frequencyassignment problem in GSM networks,” in Proc. ACM GECCO, pp.94-101, Jul.2007.
[112] H. Kamal, M. Coupechoux, P. Godlewski,“A Tabu Search DSA algorithm forreward maximization in cellular networks,” in Proc. IEEE WiMob, pp.40-45, Oct.2010.
[113]焦李成,杜海峰,刘芳,公茂果,免疫优化计算、学习与识别,北京:科学出版社,2007.
[114] L. N. de Castro, F. J. Von Zuben,“Learning and optimization using the clonalselection principle,” IEEE Trans. Evol. Comput.,6(3), pp.239-251, Jun.2002.
[115] P. J. Kolodzy,“Interference temperature: a metric for dynamic spectrum utiliza-tion,” Int. J. Network Manage.,16(2), pp.103-113, Mar./Apr.2006.
[116] T.C. Clancy,“Formalizing the interference temperature model,” Wirel. Commun.Mob. Comput.,7(9), pp.1077-1086, Nov.2007.
[117] Y. Xing, C. N. Mathur, M. A. Haleem, et al,“Dynamic spectrum access with QoSand interference temperature constraints,” IEEE Trans. Mob. Comput.,6(4), pp.423-433, April2007.
[118] C. Ghosh, S. Roy, D. Cavalcant,“Coexistence challenges for heterogeneouscognitive wireless networks in TV white spaces,” IEEE Wirel. Commun.,18(4),pp.22-31, Aug.2011.
[119]徐玖平,李军,多目标决策的理论与方法,北京：清华大学出版社,2005.
[120]同济大学数学系编,高等数学(上册)(第6版),北京：高等教育出版社,2007.
[121] R. Prasad, and Adriaan Kegel,“Improved Assessment of Interference Limits inCellular Radio Performance,” IEEE Trans. Veh. Technol.,40(2), pp.412-419,May1991.
[122] A. A. Abu-Dayya, and N. C. Beaulieu,“Outage Probabilities in the Presence ofCorrelated Lognormal Interferers,” IEEE Trans. Veh. Technol.,43(1), pp.164-173, Feb.1994.
[123] M. Pratesi, F. Santucci, and F. Graziosi,“Generalized moment matching for thelinear combination of lognormal RVs: application to outage analysis in wirelesssystems,” IEEE Trans. Wireless Commun.,5(5), pp.1122-1132, May2006.
[124] K. Sundaresan and S. Rangarajan,“Efficient Resource Management in OFDMAFemto Cells,” in Proc. ACM Mobihoc, pp.33-42, May2009.
[125] M. Arslan, J. Yoon, K. Sundaresan, et al,”FERMI: A Femtocell Resource Man-agement System for Interference Mitigation in OFDMA Networks,” in Proc. ACMMobiCom, pp.25-36, Sept.2011.
[126] M. Andrews, and L. Zhang,“Scheduling Algorithms for MultiCarrier WirelessData Systems,” IEEE/ACM Trans. Networking,19(2), pp.447-55, Apr.2011.
[127] G. Song, and Y. Li,“Cross-layer optimization for OFDM wireless networks-part I:theoretical framework,” IEEE Trans. Wireless Commun.,4(2), pp.614-624, Mar.2005.
[128] J. Jang, and K.B. Lee,“Transmit power adaptation for multiuser OFDM systems,”IEEE J. Sel. Areas Commun.,21(2), pp.171-178, Feb.2003.
[129] M. J. Neely, Stochastic network optimization with application to communicationand queueing systems, Morgan&Claypool Publishers,2010.
[130] L. Tassiulas, and A. Ephremides,“Stability properties of constrained queueingsystems and scheduling policies for maximum throughput in multihop radio net-works,” IEEE Trans. Autom. Control,37(12), pp.1936-1948, Dec.1992.
[131] S. Sakai, M. Togasaki, and K. Yamazaki,“A note on greedy algorithms for themaximum weighted independent set problem,” Discrete Appl. Math.,126(2-3),pp.313-322, Mar.2003.
[132] L. Cao, and H. Zheng,“Distributed Spectrum Allocation via Local Bargaining,”in Proc. IEEE SECON, pp.475-486, Sept.2005.
© 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 |