基于双门限的协作频谱感知优化方案研究
|
摘要
随着无线电通信技术发展的日新月异,人们的生产生活也因此变得越来越便捷、高效。与此同时,各无线电用户间对有限的频谱资源的竞争也日趋激烈。认知无线电技术被认为是缓解频谱资源紧张问题的一种有效技术手段,得到广泛关注和研究。频谱检测作为其核心技术之一,目的是使认知用户通过感知频谱空穴的方式,侦测未被占用的授权信道,伺机接入以“共用”的方式提高频谱利用率。同时,认知用户间通过协作可以解决单用户频谱感知过程中的隐蔽终端问题,提高系统的抗干扰能力,获得更优的检测效果。
为了实现协作频谱感知优化策略的研究目的,本文将围绕无线电频谱检测特点和结构,双门限能量检测机制和协作网络的融合策略等主线内容展开研究,主要完成以下工作：
1)分析了常用频谱检测模型的特点及应用条件,选取能量检测为本文频谱检测的基本方法。重点研究了多用户协作感知系统在不同融合准则下的性能表现,引入全局错误概率为主要性能指标。经过理论推导得出K秩融合准则最优投票值的计算公式,为双门限协作感知系统的优化奠定了基础。
2)结合所推公式,改进传统K秩准则的固定投票门限模式。以最小化错误概率为约束条件,从投票值动态调整角度完成感知系统性能优化,有效解决了传统K秩准则投票值固定不适应外部环境变化的问题。满足双门限感知系统的高效率,抗干扰,可扩展的性能要求。
3)引入EGC融合算法,通过与变投票值K秩准则的联合,改进了软硬结合的分区算法,并建立了数学模型。通过在以瑞利为代表的衰落信道下进行了仿真对比。从算法运行效率和结果显示来看,改善了协作系统的感知效果,降低了系统的错误概率,为衰落环境下的系统通信提供保证。
The rapid expansion of wireless communication technology has provided a more powerful and convenient means for people's production and life. However, the wireless spectrum resource as the other valuable natural ones is becoming more and more precious. Research on cognitive radio technology has been extensive attention, taking into account of limited spectrum resource in recent years. As the core technology of cognitive radio, spectrum detection offers perception users a way to access the licensed spectrum bands in an opportunistic way. By means of sensing spectrum holes cognitive radio systems can improve spectrum utilization. Meanwhile, cooperative spectrum sensing mitigates the effects of shadowing and multipath fading, when only one cognitive radio is used, and enhances the ability of the system to oppose disturbance.
To achieve the research aim of optimization strategy for collaborative spectrum sensing, the main researches of this thesis are around the characteristics and structure of radio spectrum detection, the mechanism of double-threshold energy detection and the fusion methods of collaborative network. The main work of this thesis has achieved as follows:
1) This thesis has analyzed the characteristics and application conditions of common spectrum detection model. Energy detector is selected as basic methods of detection for this thesis. Focusing on performance of multi-user cooperative perception system using different fusion rules, induced the global error probability as the main performance indicators. The optimal fusion threshold of the k-out-of-N rule is obtained by theoretical derivation, which establishes the base of the double threshold collaborative sensing system optimization in order to minimize the system error probability.
2) Combined with the derived expression, this thesis improved the traditional k-out-of-N rule fixed voting threshold application in fusion center. Perception system performance optimization is respectively accomplished by dynamic adjustment of voting threshold in order to minimize the system error probability. This effectively solves that traditional fixed-voting threshold does not adapt to the changes in the external environment, which satisfies high efficiency, anti-interference, scalable performance demand of double threshold perception system.
3) This thesis improved partition algorithm by the combination of EGC fusion algorithm and variable-threshold k-out-of-N rule, and established the mathematical model. The operation efficiency and results display the effect of perception in collaboration system is improved and the global error probability is degraded by simulation in AWGN and Rayleigh channel, which provides guarantee for system communication under the fading environment.
为了实现协作频谱感知优化策略的研究目的,本文将围绕无线电频谱检测特点和结构,双门限能量检测机制和协作网络的融合策略等主线内容展开研究,主要完成以下工作：
1)分析了常用频谱检测模型的特点及应用条件,选取能量检测为本文频谱检测的基本方法。重点研究了多用户协作感知系统在不同融合准则下的性能表现,引入全局错误概率为主要性能指标。经过理论推导得出K秩融合准则最优投票值的计算公式,为双门限协作感知系统的优化奠定了基础。
2)结合所推公式,改进传统K秩准则的固定投票门限模式。以最小化错误概率为约束条件,从投票值动态调整角度完成感知系统性能优化,有效解决了传统K秩准则投票值固定不适应外部环境变化的问题。满足双门限感知系统的高效率,抗干扰,可扩展的性能要求。
3)引入EGC融合算法,通过与变投票值K秩准则的联合,改进了软硬结合的分区算法,并建立了数学模型。通过在以瑞利为代表的衰落信道下进行了仿真对比。从算法运行效率和结果显示来看,改善了协作系统的感知效果,降低了系统的错误概率,为衰落环境下的系统通信提供保证。
The rapid expansion of wireless communication technology has provided a more powerful and convenient means for people's production and life. However, the wireless spectrum resource as the other valuable natural ones is becoming more and more precious. Research on cognitive radio technology has been extensive attention, taking into account of limited spectrum resource in recent years. As the core technology of cognitive radio, spectrum detection offers perception users a way to access the licensed spectrum bands in an opportunistic way. By means of sensing spectrum holes cognitive radio systems can improve spectrum utilization. Meanwhile, cooperative spectrum sensing mitigates the effects of shadowing and multipath fading, when only one cognitive radio is used, and enhances the ability of the system to oppose disturbance.
To achieve the research aim of optimization strategy for collaborative spectrum sensing, the main researches of this thesis are around the characteristics and structure of radio spectrum detection, the mechanism of double-threshold energy detection and the fusion methods of collaborative network. The main work of this thesis has achieved as follows:
1) This thesis has analyzed the characteristics and application conditions of common spectrum detection model. Energy detector is selected as basic methods of detection for this thesis. Focusing on performance of multi-user cooperative perception system using different fusion rules, induced the global error probability as the main performance indicators. The optimal fusion threshold of the k-out-of-N rule is obtained by theoretical derivation, which establishes the base of the double threshold collaborative sensing system optimization in order to minimize the system error probability.
2) Combined with the derived expression, this thesis improved the traditional k-out-of-N rule fixed voting threshold application in fusion center. Perception system performance optimization is respectively accomplished by dynamic adjustment of voting threshold in order to minimize the system error probability. This effectively solves that traditional fixed-voting threshold does not adapt to the changes in the external environment, which satisfies high efficiency, anti-interference, scalable performance demand of double threshold perception system.
3) This thesis improved partition algorithm by the combination of EGC fusion algorithm and variable-threshold k-out-of-N rule, and established the mathematical model. The operation efficiency and results display the effect of perception in collaboration system is improved and the global error probability is degraded by simulation in AWGN and Rayleigh channel, which provides guarantee for system communication under the fading environment.
引文
[1]杨洁,杨育.无线电频谱资源管理研究现状分析[J].无线电工程.2008(09)
[2]http://bwrc.eecs.berkeley.edu/Research/MCMA/CR White paper_nal 1.pdf.
[3]J. Mitola and GQ. Maguire. Cognitive radio:Making Software Radios More Personal[J]. IEEE Personal Communications,1999,6(4):13-18.
[4]J. Mitola. Cognitive Radio:An Integrated Agent Architecture for Software Defined Radio[D]. Sweden:Royal Institute of Technology,2000.
[5]D. Maldonado, B. Le, A. Hugine, T.W. Rondeau and C.W. Bostian. Cognitive radio applications to dynamic spectrum allocation:a discussion and an illustrative example [C].//IEEE. In Proceedings of IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks. USA:IEEE Press,2005. 597-600.
[6]D. Cabric, I. D. O'Donnell, M. S. Chen and R.W. Brodersen. Spectrum sharing radios [J]. IEEE Circuits and Systems Magazine.2006,6(2):30-45.
[7]韩昭芳.认知无线电中协作频谱感知策略优化的研究[D].北京：北京邮电大学,2011.
[8]林威.基于认知无线电技术的频谱资源利用研究[D].哈尔滨：哈尔滨工业大学,2010.
[9]T.C. Clancy. Dynamic Spectrum Access in Cognitive Radio Networks[D]. USA: University of Maryland,2006.
[10]彭玉芳.认知无线电技术及频谱管理[J].中国无线电.2009(07)：36-37.
[11]乔晓强,赵杭生,陈勇.认知无线电与频谱管理[J].军事通信技术.2009,30(1)：37-40.
[12]V. Brik, E.Rozner, S.Banarjee. DSAP:A Protocol for Coordinated Spectrum Access[C].//IEEE. First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.USA:IEEE Press,2005:611-614.
[13]C. Raman, R. D. Yates, N. Mandayam. Scheduling variable rate links via a spectrum server[C].//IEEE. First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.USA: IEEE Press,2005: 110-118
[14]J. Zhao, H. Zheng, G H. Yang. Distributed Coordination in Dynamic Spectrum Allocation Networks[C].//IEEE. First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.USA: IEEE Press,2005:259-268
[15]L. Ma, X. Han, C. C. Shen. First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, Baltimore, USA, 2005: 203-213
[16]Federal Communications Commision. Notice of Proposed Rule Making. ET Docket 04-113.2004
[17]IEEE Standards Coordinating Committee 41 (Dynamic Spectrum AccessNetworks). http://www.scc41.org/
[18]姜微.基于能量检测的频谱检测技术研究[D].哈尔滨：哈尔滨工程大学,2010.
[19]裴庆祺,李红宁,赵弘洋,李男,闵莹.认知无线电网络安全综述.通信学报.2013(1)：144-158.
[20]张晓,邓建国.干扰温度机制的研究进展[J].中兴通讯技术.2007,13(3)：19-23.
[21]叶奕亮.OFDM在多径环境及多径衰落时的特性研究[J].电信建设.2004(6)：17-21.
[22]潘建国,翟旭平.基于能量检测的频谱感知方法[J].上海大学学报.2009,15(1)：54-59.
[23]冯文江,郭瑜,胡志远.认知无线电中的频谱感知技术[J].重庆大学学报.2007,30(11)：46-49.
[24]刘雪梅.基于循环平稳特征的频谱感知算法概述[J].通信技术.2011,44(12)：21-23.
[25]张吴晔,包志华.基于循环平稳特征的频谱检测[J].通信技术.2010,43(9)：41-47.
[26]H. Urkowitz. Energy detection of unknown deterministic signals[J]. Proceedings of the IEEE.1967,55(4):523-531.
[27]Chunhua Sun, Wei Zhang, K.B. Letaief. Cooperative spectrum sensing for cognitive radios under bandwidth constraints[C].//IEEE. IEEE WCNC 2007. USA:IEEE Press,2007:1-5.
[28]A.Ghasemi, E S.Sousa. Collaborative spectrum sensing for opportunistic access in fading environment[C].//IEEE. Proc. IEEE DySPAN 2005. USA:IEEE Press, 2005:131-136.
[29]G..Ganesan, Y.G.Li. Cooperative spectrum sensing in cognitive radio networks[C].//IEEE. Proc. IEEE DySPAN 2005. USA:IEEE Press,2005: 137-143.
[30]J.Unnikrishnan, V.V.Veeravalli. Cooperative sensing for primary detection in cognitive radio[J]. Selected Topics in Signal Processing.2008,2 (1):18-27.
[31]N. Ahmed, D. Hadaller, and S. Keshav. GUESS:gossiping updates for efficient spectrum sensing[C].//in Proc. International workshop on Decentralized resource sharing in mobile computing and networking, Los Angeles, California, USA,2006, pp.12-17.
[32]M. Gandetto and C. Regazzoni. Spectrum sensing:A distributed approach for cognitive terminals[J]. IEEE J. Select. Areas Commun.2007,25(3)546-557.
[33]张楠,李娴,胡中豫,孙强.基于数据融合理论的分布式协作频谱感知方法研究[J].微电子学与计算机.2010,27(3)：133-135.
[34]G. Ganesan, Y. G. Li, Cooperative spectrum sensing in cognitive radio-part i: two user networks[J]. IEEE Transactions on Wireless Communications.2007, 6(6):2204-2213.
[35]W.Zhang, K.Letaief, Cooperative spectrum sensing with transmit and relay diversity in cognitive radio networks[J]. IEEE Transactions on Wireless Communications.2008,7(12):4761-4766.
[36]褚御芝,郑宝玉,季薇.协同频谱感知中的融合策略[J].南京邮电大学学报.2010,30(3)：39-45.
[37]F.E.Visser, G.J.M.Jassen and P. Pawelczak. Multinode spectrum sensing based on energy detection for dynamic spectrum access[C].//IEEE.67th IEEE Vehicular Technology Conference.2008:1394-1398.
[38]R.S. Blum, S.A. Kassam, H.V. Poor. Distributed detection with multiple sensors I. Advanced topics[J]. Proceedings of the IEEE.1997,85(1):64-79.
[39]Jiang Zhu, Zhengguang Xu,Furong Wang, Benxiong Huang, Bo Zhang. Double threshold energy detection of cooperative spectrum sensing in cognitive radio [C]. //IEEE. Cognitive Radio Oriented Wireless Networks and Communications. 2008:1-5.
[40]O.A. Alghamdi and M.Z.A hmed. New optimization method for cooperative spectrum sensing in cognitive radio spectrum sensing in cognitive radio networks [C].//IEEE. Wireless Advanced (WiAd) 2011.2011:54-59.
[41]李子,蔡跃.Rayleigh衰落信道的仿真模型.解放军理工大学学报.2004.5(2)：1-8.
[42]汪洋,葛临东.多径独立Rayleigh衰落信道仿真模型.信息工程大学学报,2007,8(2)：202-205.
[43]董洁,陈岩.Rayleigh信道下多用户合作能量检测方法的研究.桂林电子科技大学学报,2008,28(5)：392-394..
[44]杜威,宋琦军,肖凯宁,张洪顺.Rice衰落信道的仿真方法研究.重庆邮电大学学报.2007,19(5)：546-550.
[45]王保云,郑宝玉.Nakagami衰落环境下合并接收的性能分析.南京邮电学院学报.2003,23(4)：51-54.
[2]http://bwrc.eecs.berkeley.edu/Research/MCMA/CR White paper_nal 1.pdf.
[3]J. Mitola and GQ. Maguire. Cognitive radio:Making Software Radios More Personal[J]. IEEE Personal Communications,1999,6(4):13-18.
[4]J. Mitola. Cognitive Radio:An Integrated Agent Architecture for Software Defined Radio[D]. Sweden:Royal Institute of Technology,2000.
[5]D. Maldonado, B. Le, A. Hugine, T.W. Rondeau and C.W. Bostian. Cognitive radio applications to dynamic spectrum allocation:a discussion and an illustrative example [C].//IEEE. In Proceedings of IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks. USA:IEEE Press,2005. 597-600.
[6]D. Cabric, I. D. O'Donnell, M. S. Chen and R.W. Brodersen. Spectrum sharing radios [J]. IEEE Circuits and Systems Magazine.2006,6(2):30-45.
[7]韩昭芳.认知无线电中协作频谱感知策略优化的研究[D].北京：北京邮电大学,2011.
[8]林威.基于认知无线电技术的频谱资源利用研究[D].哈尔滨：哈尔滨工业大学,2010.
[9]T.C. Clancy. Dynamic Spectrum Access in Cognitive Radio Networks[D]. USA: University of Maryland,2006.
[10]彭玉芳.认知无线电技术及频谱管理[J].中国无线电.2009(07)：36-37.
[11]乔晓强,赵杭生,陈勇.认知无线电与频谱管理[J].军事通信技术.2009,30(1)：37-40.
[12]V. Brik, E.Rozner, S.Banarjee. DSAP:A Protocol for Coordinated Spectrum Access[C].//IEEE. First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.USA:IEEE Press,2005:611-614.
[13]C. Raman, R. D. Yates, N. Mandayam. Scheduling variable rate links via a spectrum server[C].//IEEE. First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.USA: IEEE Press,2005: 110-118
[14]J. Zhao, H. Zheng, G H. Yang. Distributed Coordination in Dynamic Spectrum Allocation Networks[C].//IEEE. First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.USA: IEEE Press,2005:259-268
[15]L. Ma, X. Han, C. C. Shen. First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, Baltimore, USA, 2005: 203-213
[16]Federal Communications Commision. Notice of Proposed Rule Making. ET Docket 04-113.2004
[17]IEEE Standards Coordinating Committee 41 (Dynamic Spectrum AccessNetworks). http://www.scc41.org/
[18]姜微.基于能量检测的频谱检测技术研究[D].哈尔滨：哈尔滨工程大学,2010.
[19]裴庆祺,李红宁,赵弘洋,李男,闵莹.认知无线电网络安全综述.通信学报.2013(1)：144-158.
[20]张晓,邓建国.干扰温度机制的研究进展[J].中兴通讯技术.2007,13(3)：19-23.
[21]叶奕亮.OFDM在多径环境及多径衰落时的特性研究[J].电信建设.2004(6)：17-21.
[22]潘建国,翟旭平.基于能量检测的频谱感知方法[J].上海大学学报.2009,15(1)：54-59.
[23]冯文江,郭瑜,胡志远.认知无线电中的频谱感知技术[J].重庆大学学报.2007,30(11)：46-49.
[24]刘雪梅.基于循环平稳特征的频谱感知算法概述[J].通信技术.2011,44(12)：21-23.
[25]张吴晔,包志华.基于循环平稳特征的频谱检测[J].通信技术.2010,43(9)：41-47.
[26]H. Urkowitz. Energy detection of unknown deterministic signals[J]. Proceedings of the IEEE.1967,55(4):523-531.
[27]Chunhua Sun, Wei Zhang, K.B. Letaief. Cooperative spectrum sensing for cognitive radios under bandwidth constraints[C].//IEEE. IEEE WCNC 2007. USA:IEEE Press,2007:1-5.
[28]A.Ghasemi, E S.Sousa. Collaborative spectrum sensing for opportunistic access in fading environment[C].//IEEE. Proc. IEEE DySPAN 2005. USA:IEEE Press, 2005:131-136.
[29]G..Ganesan, Y.G.Li. Cooperative spectrum sensing in cognitive radio networks[C].//IEEE. Proc. IEEE DySPAN 2005. USA:IEEE Press,2005: 137-143.
[30]J.Unnikrishnan, V.V.Veeravalli. Cooperative sensing for primary detection in cognitive radio[J]. Selected Topics in Signal Processing.2008,2 (1):18-27.
[31]N. Ahmed, D. Hadaller, and S. Keshav. GUESS:gossiping updates for efficient spectrum sensing[C].//in Proc. International workshop on Decentralized resource sharing in mobile computing and networking, Los Angeles, California, USA,2006, pp.12-17.
[32]M. Gandetto and C. Regazzoni. Spectrum sensing:A distributed approach for cognitive terminals[J]. IEEE J. Select. Areas Commun.2007,25(3)546-557.
[33]张楠,李娴,胡中豫,孙强.基于数据融合理论的分布式协作频谱感知方法研究[J].微电子学与计算机.2010,27(3)：133-135.
[34]G. Ganesan, Y. G. Li, Cooperative spectrum sensing in cognitive radio-part i: two user networks[J]. IEEE Transactions on Wireless Communications.2007, 6(6):2204-2213.
[35]W.Zhang, K.Letaief, Cooperative spectrum sensing with transmit and relay diversity in cognitive radio networks[J]. IEEE Transactions on Wireless Communications.2008,7(12):4761-4766.
[36]褚御芝,郑宝玉,季薇.协同频谱感知中的融合策略[J].南京邮电大学学报.2010,30(3)：39-45.
[37]F.E.Visser, G.J.M.Jassen and P. Pawelczak. Multinode spectrum sensing based on energy detection for dynamic spectrum access[C].//IEEE.67th IEEE Vehicular Technology Conference.2008:1394-1398.
[38]R.S. Blum, S.A. Kassam, H.V. Poor. Distributed detection with multiple sensors I. Advanced topics[J]. Proceedings of the IEEE.1997,85(1):64-79.
[39]Jiang Zhu, Zhengguang Xu,Furong Wang, Benxiong Huang, Bo Zhang. Double threshold energy detection of cooperative spectrum sensing in cognitive radio [C]. //IEEE. Cognitive Radio Oriented Wireless Networks and Communications. 2008:1-5.
[40]O.A. Alghamdi and M.Z.A hmed. New optimization method for cooperative spectrum sensing in cognitive radio spectrum sensing in cognitive radio networks [C].//IEEE. Wireless Advanced (WiAd) 2011.2011:54-59.
[41]李子,蔡跃.Rayleigh衰落信道的仿真模型.解放军理工大学学报.2004.5(2)：1-8.
[42]汪洋,葛临东.多径独立Rayleigh衰落信道仿真模型.信息工程大学学报,2007,8(2)：202-205.
[43]董洁,陈岩.Rayleigh信道下多用户合作能量检测方法的研究.桂林电子科技大学学报,2008,28(5)：392-394..
[44]杜威,宋琦军,肖凯宁,张洪顺.Rice衰落信道的仿真方法研究.重庆邮电大学学报.2007,19(5)：546-550.
[45]王保云,郑宝玉.Nakagami衰落环境下合并接收的性能分析.南京邮电学院学报.2003,23(4)：51-54.