认知无线电中基于能量检测的频谱感知技术研究
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摘要
无线频谱资源具有不可再生性。随着无线通信业务的需求不断增长,频谱资源紧张的问题日益凸显。但是大量的研究表明传统的固定频谱分配策略导致部分频段十分拥挤而另一部分频谱利用不充分。因此,如何解决频谱利用的不均衡性并合理利用宝贵的频谱资源成为未来无线通信领域的重要研究课题。
认知无线电为上述问题的解决提供了有效途径。它通过与其周围电磁环境的交互,动态地改变自身的工作参数,对授权频谱进行二次利用。这一概念的提出突破了传统静态频谱分配策略的局限,可以有效缓解当前频谱资源匮乏与无线业务日益增长之间的矛盾。
频谱感知是实现空闲频谱有效利用的基础与前提。能量检测作为频谱感知技术之一,具有不需要授权用户的先验信息、复杂程度低和容易实现等优点,在相关研究和标准中被广泛采用,因此具有重要的研究价值。
本文对影响能量检测性能的主要因素检测门限模型进行研究,分析了相关研究存在的问题：单门限检测具有判决过程简单易于实现的优点,但抗噪声能力差；自适应单门限检测模型,改善了抗噪声能力,但其算法复杂度较大不易实现；现有的双门限检测方案在一定程度上提高了检测性能,但它是基于固定门限的判决方式,而门限数量的增加使得判决过程中包含更多的状态,进而出现系统稳定性减低、单个信道检测时间过长、频谱利用率下降和抗噪声能力弱等问题。
为解决以上问题,本文综合考虑频谱检测中的性能指标,提出一种基于滞回门限的认知无线电频谱检测方案。所提方案改善了现有方案在应对判决中间状态中的不足,依据用户业务行为的统计规律,通过参照之前的判决结果来选择本次进行判决时使用的门限。仿真验证表明,方案在保证碰撞概率在可接受范围内的前提下,能够减小噪声随机性对检测系统的影响以及频谱感知次数,提高频谱利用率,达到提升频谱检测性能的目的。
Wireless spectrum is not a renewable resource. Therefore with the growing demand of wireless communication services, the strain in spectrum resources becomes increasingly prominent. However, more and more studies and reports have shown that the traditional fixed spectrum allocation policy makes some frequency bands over-utilized while other bands under-utilized. Consequently, rational use of the unbalanced utilized spectrum resource deserves intensive study in the field of wireless communications in the future.
Cognitive radio is a research hotspot in the evolution and development of wireless and mobile communications technology. Cognitive radio can dynamically change its operational parameters and improve the utilization of spectrum resource via interacting with the surrounding electromagnetic environment. Such a technology overcome the limitations of traditional static spectrum strategy and can effectively alleviate the contradiction between the current lack of spectrum resources and the growing wireless business. Spectrum sensing is the foundation of cognitive radio, and energy detection is a favorable spectrum sensing scheme which requires no prior information of the licensed user and has the advantages of low complexity and easy implementation. Energy detection is widely applied in test-beds and standards and thus deserves more concentration and research.
This paper focuses on sensing threshold model, which is the main factor influencing the performance of energy detection. The limitations and shortcomings of current research are analyzed. Single threshold model has simple decision process. Although easy to be implemented, single threshold model suffers from stochastic noise. As an improved model, adaptive threshold is introduced. Such a scheme enjoys better anti-noise capacity, but increases the complexity of the algorithm and the difficulty of implement. Double threshold considerably improves the performance of energy detection, while it brings about a third detection state in which no judgment can be made about the channel, leading to detection blind spot and impaired spectrum utilization.
To solve the problems mentioned above, this paper proposed a hysteresis-threshold scheme for spectrum sensing in cognitive radio based on energy detection. The proposed scheme alternates its sensing threshold according to the previous sensing decision based on the statistics of licensed user, instead of making no decision in the sensing blind spot. Simulation shows that the proposed scheme can reduce the impacted of stochastic noise and the number of spectrum sensing resulting in a improved spectrum utilization with a tolerable increased probability of collision.
认知无线电为上述问题的解决提供了有效途径。它通过与其周围电磁环境的交互,动态地改变自身的工作参数,对授权频谱进行二次利用。这一概念的提出突破了传统静态频谱分配策略的局限,可以有效缓解当前频谱资源匮乏与无线业务日益增长之间的矛盾。
频谱感知是实现空闲频谱有效利用的基础与前提。能量检测作为频谱感知技术之一,具有不需要授权用户的先验信息、复杂程度低和容易实现等优点,在相关研究和标准中被广泛采用,因此具有重要的研究价值。
本文对影响能量检测性能的主要因素检测门限模型进行研究,分析了相关研究存在的问题：单门限检测具有判决过程简单易于实现的优点,但抗噪声能力差；自适应单门限检测模型,改善了抗噪声能力,但其算法复杂度较大不易实现；现有的双门限检测方案在一定程度上提高了检测性能,但它是基于固定门限的判决方式,而门限数量的增加使得判决过程中包含更多的状态,进而出现系统稳定性减低、单个信道检测时间过长、频谱利用率下降和抗噪声能力弱等问题。
为解决以上问题,本文综合考虑频谱检测中的性能指标,提出一种基于滞回门限的认知无线电频谱检测方案。所提方案改善了现有方案在应对判决中间状态中的不足,依据用户业务行为的统计规律,通过参照之前的判决结果来选择本次进行判决时使用的门限。仿真验证表明,方案在保证碰撞概率在可接受范围内的前提下,能够减小噪声随机性对检测系统的影响以及频谱感知次数,提高频谱利用率,达到提升频谱检测性能的目的。
Wireless spectrum is not a renewable resource. Therefore with the growing demand of wireless communication services, the strain in spectrum resources becomes increasingly prominent. However, more and more studies and reports have shown that the traditional fixed spectrum allocation policy makes some frequency bands over-utilized while other bands under-utilized. Consequently, rational use of the unbalanced utilized spectrum resource deserves intensive study in the field of wireless communications in the future.
Cognitive radio is a research hotspot in the evolution and development of wireless and mobile communications technology. Cognitive radio can dynamically change its operational parameters and improve the utilization of spectrum resource via interacting with the surrounding electromagnetic environment. Such a technology overcome the limitations of traditional static spectrum strategy and can effectively alleviate the contradiction between the current lack of spectrum resources and the growing wireless business. Spectrum sensing is the foundation of cognitive radio, and energy detection is a favorable spectrum sensing scheme which requires no prior information of the licensed user and has the advantages of low complexity and easy implementation. Energy detection is widely applied in test-beds and standards and thus deserves more concentration and research.
This paper focuses on sensing threshold model, which is the main factor influencing the performance of energy detection. The limitations and shortcomings of current research are analyzed. Single threshold model has simple decision process. Although easy to be implemented, single threshold model suffers from stochastic noise. As an improved model, adaptive threshold is introduced. Such a scheme enjoys better anti-noise capacity, but increases the complexity of the algorithm and the difficulty of implement. Double threshold considerably improves the performance of energy detection, while it brings about a third detection state in which no judgment can be made about the channel, leading to detection blind spot and impaired spectrum utilization.
To solve the problems mentioned above, this paper proposed a hysteresis-threshold scheme for spectrum sensing in cognitive radio based on energy detection. The proposed scheme alternates its sensing threshold according to the previous sensing decision based on the statistics of licensed user, instead of making no decision in the sensing blind spot. Simulation shows that the proposed scheme can reduce the impacted of stochastic noise and the number of spectrum sensing resulting in a improved spectrum utilization with a tolerable increased probability of collision.
引文
[1]Hoven N. K. On the feasibility of cognitive radio[D]. Berkeley:University of California, 2005.
[2]Mitola J. Ⅲ, Maguire G.Q. Jr. Cognitive radio:making software radios more personal[J]. IEEE Personal Communications,1999, (6):13-18.
[3]Mitola J. Ⅲ. Cognitive radio:an integrated agent architecture for software defined radio[D]. Stockholm, Sweden:Royal Institute of Technology(KTH),2000.
[4]FCC-03-322. Facilitating Opportunities for Flexible, efficient, and Reliable Spectrum Use Employing Cognitive Radio Technologies[R]. ET Docket 03-289, Notice of Inquiry and Proposed,2003.
[5]HaykinS.. Cognitive radio:brain-empowered wireless communications[J]. IEEE Journalon Selected Areas in Communications,2005,23(2):201-220.
[6]IEEEP 1901.2TM/D01, IEEE P1900 Working Group[EB/OL]. http://grouper.ieee.org/groups/1901/index.html,2010.
[7]杨小牛,楼才义,徐建良编著.软件无线电技术与实现[M].北京：电子工业出版社,2004.
[8]Clancy T. C. III.. Dynamic spectrum access in cognitive radio networks[D]. Keith Nolan: Philosophy University of Maryland,2005.
[9]Zhao Q.. Sadler B.M.. A Survey of dynamic spectrum access[J]. IEEE Signal Processing Magazine,2007,24(3):79-89.
[10]Shankar N.S., Cordeiro C., Challapali K.. Spectrum agile radios:utilization and sensing architecture[C]. In:Proceedings of 2005 First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks[C]. Baltimore, USA:2005.160-169.
[11]FCC ET Docket No.02-155. Spectrum Policy Task Force Report[S].2002.
[12]Akyildiz I.F., Lee W.Y., Vuran M.C., et al. NeXtgeneration/dynamic spectrum access cognitive radio wireless networks:asurvey[J]. Computer Networks Journal (Elsevier),2006, 50(13):2127-2159.
[13]ArslanhH. Cognitive Radio, Software Defined Radio, and Adaptive Wireless Systems[M]. Springer,2007:470.
[14]Ekram H., Bhargava V. K., Cognitive Wireless Communication Networks[M]. Springer, 2007:440.
[15]Cordeiro C., Challapali K., Birru D., et al. IEEE 802.22:the first worldwide wireless standard based on cognitive radios[A]. In:Proceedings of 2005 First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks[C]. Baltimore, USA: 2005.328-337.
[16]Stevenson C., Chouinard G., Lei Zhongding, et al. IEEE 802.22:The first cognitive radio wireless regional area network standard[J].IEEE Communications Magazine,2009, 47(1):130-138.
[17]FilinS., Harada H., Murakami H, et al. International standardization of cognitive radio systems[J]. IEEE Communications Magazine,2011,49 (3):82-89.
[18]郭彩丽,张天魁,曾志民等.认知无线电技术的国内外发展和研究现状[J].现代电信科技.2006,(6).
[19]国家自然科学基金网站.http://159.226.244.22/portal/proj_search.asp.
[20]Cabric D., Mishra S. M., Brodersen R. W.. Implementation issues in spectrum Sensing for Cognitive Radios[A]. Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers[C],2004.772-776.
[21]H. Tang, Some physical layer issues of wide-band cognitive radio systems[A]. In: Proceedings of IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks[C]. Baltimore, USA:2005.151-159.
[22]Sahai A., Tandra R., Mishra S. M., et al. Fundamental design tradeoffs in cognitive radio systems[A]. In:Proceedings of International Workshop on Technology and Policy for Accessing Spectrum[C]. Boston, USA:2006.
[23]周贤伟,王建萍,王春江.认知无线电[M].北京：国防工业出版社.2008.1
[24]Haykin S., Thomson D., Reed J.H.. Spectrum sensing for cognitive radio[J]. Proceeding of the IEEE,2009,97(5):849-877.
[25]Urkowitz H., Energy detection of unknown deterministic signals[J].Proceedings of the IEEE, 1967,55(4):523-531.
[26]Choi Hyun-Ho, Jang Kyunghun, Cheong Yoonchae. Adaptive sensing threshold control based on transmission power in cognitive radio systems[A]. In:Proceedings of 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications[C]. Singapore, Singapore:2008.1-6.
[27]Gorcin A., Qaraqe K.A., Celebi H., et al. An adaptive threshold method for spectrum sensing in multi-channel cognitive radio networks [A]. In:Proceedings of EEEE 17th International Conference on Telecommunications. Doha, Qatar:2010.425-429.
[28]JoshiD.R., PopescuD.C., DobreO.A.. Dynamic threshold adaptation for spectrum sensing in cognitive radio systems[A]. In:Proceedings of IEEE Radio and Wireless Symposium [C]. New Orleans, USA:2010.468-471.
[29]WuJinbo, Luo Tao, YueGuangxin. An energy detection algorithm based on double-threshold in CR systems[A]. In:Proceedings of IEEE International Conference on Information Science and Engineering[C]. Nanjing, China:2009.493-496.
[30]ZongBangsheng, Hu Jing, SongTiecheng,. Adaptive spectrum sensing scheme with punishing mechanism in cognitive radio networks[A]. In:Proceedings of IEEE International Conference on Communication Technology. Nanjing, China:2010.1160-1163.
[31]彭木根,王文博.3G无线资源管理与网络规划优化[M].北京：人民邮电出版社.2006.
[32]张长刚,孙保红.CDMA无线网络规划原理与实践[M].北京：人民邮电出版社.2005.
[33]Ghozzi M., Marx F., DohlerM., et al. Cyclostatilonarilty-based test for detection of vacant frequency bands[A]. In:Proceedings of 1st International Conference on Cognitive Radio Oriented Wireless Networks and Communications[C]. Mykonos Island, Greece:2006.1-5.
[34]Wild B., Ramchandran K.. Detecting primary receivers for cognitive radio application[A]. In: Proceedings of 2005 First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks[C]. Baltimore, MD, USA:2005.124-130.
[2]Mitola J. Ⅲ, Maguire G.Q. Jr. Cognitive radio:making software radios more personal[J]. IEEE Personal Communications,1999, (6):13-18.
[3]Mitola J. Ⅲ. Cognitive radio:an integrated agent architecture for software defined radio[D]. Stockholm, Sweden:Royal Institute of Technology(KTH),2000.
[4]FCC-03-322. Facilitating Opportunities for Flexible, efficient, and Reliable Spectrum Use Employing Cognitive Radio Technologies[R]. ET Docket 03-289, Notice of Inquiry and Proposed,2003.
[5]HaykinS.. Cognitive radio:brain-empowered wireless communications[J]. IEEE Journalon Selected Areas in Communications,2005,23(2):201-220.
[6]IEEEP 1901.2TM/D01, IEEE P1900 Working Group[EB/OL]. http://grouper.ieee.org/groups/1901/index.html,2010.
[7]杨小牛,楼才义,徐建良编著.软件无线电技术与实现[M].北京：电子工业出版社,2004.
[8]Clancy T. C. III.. Dynamic spectrum access in cognitive radio networks[D]. Keith Nolan: Philosophy University of Maryland,2005.
[9]Zhao Q.. Sadler B.M.. A Survey of dynamic spectrum access[J]. IEEE Signal Processing Magazine,2007,24(3):79-89.
[10]Shankar N.S., Cordeiro C., Challapali K.. Spectrum agile radios:utilization and sensing architecture[C]. In:Proceedings of 2005 First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks[C]. Baltimore, USA:2005.160-169.
[11]FCC ET Docket No.02-155. Spectrum Policy Task Force Report[S].2002.
[12]Akyildiz I.F., Lee W.Y., Vuran M.C., et al. NeXtgeneration/dynamic spectrum access cognitive radio wireless networks:asurvey[J]. Computer Networks Journal (Elsevier),2006, 50(13):2127-2159.
[13]ArslanhH. Cognitive Radio, Software Defined Radio, and Adaptive Wireless Systems[M]. Springer,2007:470.
[14]Ekram H., Bhargava V. K., Cognitive Wireless Communication Networks[M]. Springer, 2007:440.
[15]Cordeiro C., Challapali K., Birru D., et al. IEEE 802.22:the first worldwide wireless standard based on cognitive radios[A]. In:Proceedings of 2005 First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks[C]. Baltimore, USA: 2005.328-337.
[16]Stevenson C., Chouinard G., Lei Zhongding, et al. IEEE 802.22:The first cognitive radio wireless regional area network standard[J].IEEE Communications Magazine,2009, 47(1):130-138.
[17]FilinS., Harada H., Murakami H, et al. International standardization of cognitive radio systems[J]. IEEE Communications Magazine,2011,49 (3):82-89.
[18]郭彩丽,张天魁,曾志民等.认知无线电技术的国内外发展和研究现状[J].现代电信科技.2006,(6).
[19]国家自然科学基金网站.http://159.226.244.22/portal/proj_search.asp.
[20]Cabric D., Mishra S. M., Brodersen R. W.. Implementation issues in spectrum Sensing for Cognitive Radios[A]. Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers[C],2004.772-776.
[21]H. Tang, Some physical layer issues of wide-band cognitive radio systems[A]. In: Proceedings of IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks[C]. Baltimore, USA:2005.151-159.
[22]Sahai A., Tandra R., Mishra S. M., et al. Fundamental design tradeoffs in cognitive radio systems[A]. In:Proceedings of International Workshop on Technology and Policy for Accessing Spectrum[C]. Boston, USA:2006.
[23]周贤伟,王建萍,王春江.认知无线电[M].北京：国防工业出版社.2008.1
[24]Haykin S., Thomson D., Reed J.H.. Spectrum sensing for cognitive radio[J]. Proceeding of the IEEE,2009,97(5):849-877.
[25]Urkowitz H., Energy detection of unknown deterministic signals[J].Proceedings of the IEEE, 1967,55(4):523-531.
[26]Choi Hyun-Ho, Jang Kyunghun, Cheong Yoonchae. Adaptive sensing threshold control based on transmission power in cognitive radio systems[A]. In:Proceedings of 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications[C]. Singapore, Singapore:2008.1-6.
[27]Gorcin A., Qaraqe K.A., Celebi H., et al. An adaptive threshold method for spectrum sensing in multi-channel cognitive radio networks [A]. In:Proceedings of EEEE 17th International Conference on Telecommunications. Doha, Qatar:2010.425-429.
[28]JoshiD.R., PopescuD.C., DobreO.A.. Dynamic threshold adaptation for spectrum sensing in cognitive radio systems[A]. In:Proceedings of IEEE Radio and Wireless Symposium [C]. New Orleans, USA:2010.468-471.
[29]WuJinbo, Luo Tao, YueGuangxin. An energy detection algorithm based on double-threshold in CR systems[A]. In:Proceedings of IEEE International Conference on Information Science and Engineering[C]. Nanjing, China:2009.493-496.
[30]ZongBangsheng, Hu Jing, SongTiecheng,. Adaptive spectrum sensing scheme with punishing mechanism in cognitive radio networks[A]. In:Proceedings of IEEE International Conference on Communication Technology. Nanjing, China:2010.1160-1163.
[31]彭木根,王文博.3G无线资源管理与网络规划优化[M].北京：人民邮电出版社.2006.
[32]张长刚,孙保红.CDMA无线网络规划原理与实践[M].北京：人民邮电出版社.2005.
[33]Ghozzi M., Marx F., DohlerM., et al. Cyclostatilonarilty-based test for detection of vacant frequency bands[A]. In:Proceedings of 1st International Conference on Cognitive Radio Oriented Wireless Networks and Communications[C]. Mykonos Island, Greece:2006.1-5.
[34]Wild B., Ramchandran K.. Detecting primary receivers for cognitive radio application[A]. In: Proceedings of 2005 First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks[C]. Baltimore, MD, USA:2005.124-130.