基于模糊积分和最优化理论的合作式频谱感知算法研究
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摘要
随着无线通信技术的发展,无线频谱的需求在不断的增加,频谱资源变得越来越紧缺。而在现行的无线频谱管理体制下,大量的已分配频谱却经常未被使用。频谱稀缺与频谱的低利用率之间的矛盾越来越突出,为了解决频谱利用率低的问题,感知无线电技术应运而生。它能够自适应的接入空闲信道而不对主用户造成任何干扰,从而最大限度的提高频谱利用率。
在新世纪优秀人才计划(项目编号：NCET-06-0091)和国家高新技术863项目(频谱资源共享无线通信系统,项目编号：2009AA011802)的支持下对频谱感知技术进行了研究,本文的结构如下所示：
本文首先介绍了本课题的研究背景,然后阐述了感知无线电技术在国内外的研究现状及其关键技术的介绍,指明了本论文的研究方向。然后介绍了现有的感知无线电频谱感知技术。将频谱感知技术主要分为四大类,并对这四类技术的原理和技术背景做了介绍,并得出结论：合作检测已经成为感知无线电频谱感知发展的趋势,本文研究的重点也将围绕合作式频谱检测展开。接下来重点介绍了两种在合作式频谱感知方法中基于不确定性推测的融合策略：证据理论方法和模糊矩阵评价方法。通过对这两种方法的详细介绍以及与传统融合策略的比较,总结了它们的优缺点。紧接着将各个感知用户检测结果的“不确定性”考虑到检测算法中,提出了两种基于模糊积分和最优化理论的频谱感知算法。文中给出了这两种算法的系统模型和算法原理,并且通过仿真分析,比较了所提算法与目前常用的“证据理论”、“与”“或”和“大多数”融合准则的合作式频谱检测方法的检测性能,本文所提的基于模糊积分和最优化理论的频谱感知算法的检测概率、虚警概率和总错误概率性能均优于其他算法,大大提高了整个感知无线电系统的频谱检测的正确性。最后对感知无线电频谱感知技术进行了总结和展望
With the development of wireless communication technology, the need for bandwidth is increasing continuously, and the growing need makes wireless spectrum resources more and more scarce. Within the current spectrum regulatory framework, however, a large number of spectrum resources are often idle. The conflicts between spectrum scarcity and spectrum under-utilization become more obvious, and they are caused by the mismatch between static spectrum planning system and dynamic use of spectrum. In order to solve the conflicts between spectrum scarcity and spectrum under-utilization, cognitive radio (CR) technology was recently proposed. It can improve the spectrum utilization by allowing secondary networks (users) to borrow unused radio spectrum from primary licensed networks (users) or to share the spectrum with the primary networks (users).
Thanks for New Century Excellent Talents in University (NCET) under Grant No and NCET-06-0091 and the National High-tech R&D Program of China (863 program) under Grant No.2009AA011802, these two programs support my research. The content is organized as follows.
This paper introduces the background of the research topic and presents some general information of cognitive radio initially. It also gives out the definition and the function of the CR, as well as the key technologies and the current research situations at domestic and abroad in detail, Through detailed background information, the main research areas of this dissertation is determined. Chapter two describes the existing spectrum sensing cognitive radio technology. Spectrum sensing technology can be divided into four categories, and these four technologies are introduced in detail. According to the introduction, the conclusion can be made that:cooperation detection of the radio spectrum has become trend of cognitive radio development. Chapter three focuses on two of the cooperative spectrum sensing methods based on uncertainty integration strategy:they are the evidence theory and fuzzy matrix evaluation. With a detailed description of these two methods and their comparisons with traditional integration strategies, their advantages and disadvantages are summarized. Through chapter four, uncertainty is taken into account into the detection algorithms by the innovative way. The two spectrum sensing algorithms based on fuzzy integral and optimization theory are introduced in detail. Compared to AND, OR, Majority and evidence theory fusion strategies implementing in cooperative spectrum sensing scheme, the proposed algorithms has better performance. In the end, spectrum sensing in CR are summarized and the prospects for the research are speculated.
在新世纪优秀人才计划(项目编号：NCET-06-0091)和国家高新技术863项目(频谱资源共享无线通信系统,项目编号：2009AA011802)的支持下对频谱感知技术进行了研究,本文的结构如下所示：
本文首先介绍了本课题的研究背景,然后阐述了感知无线电技术在国内外的研究现状及其关键技术的介绍,指明了本论文的研究方向。然后介绍了现有的感知无线电频谱感知技术。将频谱感知技术主要分为四大类,并对这四类技术的原理和技术背景做了介绍,并得出结论：合作检测已经成为感知无线电频谱感知发展的趋势,本文研究的重点也将围绕合作式频谱检测展开。接下来重点介绍了两种在合作式频谱感知方法中基于不确定性推测的融合策略：证据理论方法和模糊矩阵评价方法。通过对这两种方法的详细介绍以及与传统融合策略的比较,总结了它们的优缺点。紧接着将各个感知用户检测结果的“不确定性”考虑到检测算法中,提出了两种基于模糊积分和最优化理论的频谱感知算法。文中给出了这两种算法的系统模型和算法原理,并且通过仿真分析,比较了所提算法与目前常用的“证据理论”、“与”“或”和“大多数”融合准则的合作式频谱检测方法的检测性能,本文所提的基于模糊积分和最优化理论的频谱感知算法的检测概率、虚警概率和总错误概率性能均优于其他算法,大大提高了整个感知无线电系统的频谱检测的正确性。最后对感知无线电频谱感知技术进行了总结和展望
With the development of wireless communication technology, the need for bandwidth is increasing continuously, and the growing need makes wireless spectrum resources more and more scarce. Within the current spectrum regulatory framework, however, a large number of spectrum resources are often idle. The conflicts between spectrum scarcity and spectrum under-utilization become more obvious, and they are caused by the mismatch between static spectrum planning system and dynamic use of spectrum. In order to solve the conflicts between spectrum scarcity and spectrum under-utilization, cognitive radio (CR) technology was recently proposed. It can improve the spectrum utilization by allowing secondary networks (users) to borrow unused radio spectrum from primary licensed networks (users) or to share the spectrum with the primary networks (users).
Thanks for New Century Excellent Talents in University (NCET) under Grant No and NCET-06-0091 and the National High-tech R&D Program of China (863 program) under Grant No.2009AA011802, these two programs support my research. The content is organized as follows.
This paper introduces the background of the research topic and presents some general information of cognitive radio initially. It also gives out the definition and the function of the CR, as well as the key technologies and the current research situations at domestic and abroad in detail, Through detailed background information, the main research areas of this dissertation is determined. Chapter two describes the existing spectrum sensing cognitive radio technology. Spectrum sensing technology can be divided into four categories, and these four technologies are introduced in detail. According to the introduction, the conclusion can be made that:cooperation detection of the radio spectrum has become trend of cognitive radio development. Chapter three focuses on two of the cooperative spectrum sensing methods based on uncertainty integration strategy:they are the evidence theory and fuzzy matrix evaluation. With a detailed description of these two methods and their comparisons with traditional integration strategies, their advantages and disadvantages are summarized. Through chapter four, uncertainty is taken into account into the detection algorithms by the innovative way. The two spectrum sensing algorithms based on fuzzy integral and optimization theory are introduced in detail. Compared to AND, OR, Majority and evidence theory fusion strategies implementing in cooperative spectrum sensing scheme, the proposed algorithms has better performance. In the end, spectrum sensing in CR are summarized and the prospects for the research are speculated.
引文
[1]FCC, ET Docket No 02-135 Spectrum Poicy Take Force (SPTF) Report, Nov.2002.
[2]A. Ghasemi, E.S Sousa, "Sensing in Cognitive Radio Networks:Requirements, Challenges and Design Trade-offs," IEEE Communications Magazine, April 2008: pp.32-39.
[3]N.K. Hoven, " On the feasibility of cognitive radio," Master of Science, University of California, Berkeley, Spring 2005.
[4]J. Mitola, Cognitive radio:making software radios more personal, in IEEE Personal Communications,1999,6(4).
[5]FCC. ET Docket No 03-222 Notice of proposed rule making and order, December, 2003.
[6]S. Haykin, Cognitive radio:brain-empowered wireless communications, in IEEE Journal on Selected Areas in Communications,2005,23(2):128-138.
[7]IEEE802 LAN/MAN Standards Committee 802.22 WG [EB/OL], http://www. ieee802. org/22/.
[8]IEEE 802.16's License-Exempt (LE) Task Group [EB/OL]. http://www. ieee802. org/16/le/.
[9]IEEE P1900 Working Group [EB/OL].
[10]IEEE Std 802.11h-2003 Part 11. Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications Amendment 5:Spectrum and Transmit Power Management Extensions in the 5 GHz band in Europe [S].2003.
[11]IEEE P802.11-Task Group Y-Meeting Update:Status of project IEEE 802.11y [EB/OL]. http://grouper.ieee.org/groups/802/11/Reports/tgy_update.html.
[12]ITU-R Report 2063, "The Impact of Software Defined Radio on IMT-2000, the Future Development of IMT-2000 and Systems Beyond IMT-2000."
[13]ITU-R Report M.2064, "Software-Defined Radio in the Land Mobile Service."
[14]S. M. Kay, Fundamentals of Statistical Signal Processing:Detection Theory. Englewood Cliffs, NJ:Prentice-Hall,1998, vol.2.
[15]E.S.Sousa, Spectrum sensing in cognitive radio networks:requirements, challenges and design trade-offs, in IEEE Communications Magazine,2008, pp:33.
[16]H. Urkowitz, "Energy detection of unknown deterministic signals," Proceeding of the IEEE, Apr.1967,55(4).
[17]F. Digham, M. Alouini, and M. Simon, "On the energy detection of unknown signals over fading channels,"IEEE International Conference on Communications,2003. ICC'03, vol.5,2003.
[18]V. I. Kostylev, "Energy detection of a signal with random amplitude," in Proc. IEEE Int. Conf. Commun., New York, Apr.28-May 2,2002, pp.1606-1610.
[19]曹志刚,钱亚生,《现代通信原理》,清华大学出版社,1992年8月,第1版
[20]H.-S. Chen, W. Gao, and D. G Daut, "Signature based spectrum sensing algorithms for IEEE 802.22 WRAN," in Proc. IEEE Int. Conf. Communications (ICC), Jun.2007.
[21]W.A. Gardner, "Signal Interception:A Unifying Theoretical Framework for Future Detection," IEEE Trans. on Communications,1998.
[22]W.A. Gardner, "Measurement of Spectral Correlation," IEEE Trans. on Signal Processing, Vol. ASSP-34, No.5, Oct.1986.
[23]J. Goerlich, D. Bruchner, and A. Richter, "Signal Analysis Using Spectral Correlation Measurement," IEEE IMTC,1998.
[24]Ye, J Grosspietsch,G Memik, "Spectrum Sensing Using Cyclostationary Spectrum Density for Cognitive Radios,"IEEE Workshop on Signal Processing Systems, pp.1-6,2007.
[25]S.Y Xu, Z.J. Zhao, J.N. Shang,"Spectrum Sensing Based on Cyclostationarity," 2008 Workshop on Power Electronics and Intelligent Transportation System.
[26]A. Sahai, N. Hoven, and R. Tandra, "Some fundamental limits on cognitive radio," in Proc. Allerton Conf. on Commununictions, control, and computing, Monticello, Oct. 2004. V. I. Kostylev, "Energy detection of a signal with random amplitude," in Proc. IEEE Int. Conf. Commun., New York, Apr.28-May 2,2002,pp.1606-1610.
[27]D. Cabric, S. M. Mishra, and R. W. Brodersen, "Implementation issues in spectrum sensing for cognitive radios," in Proc. Asilomar Conf. on Signals, Systems, and Computers, Nov.7-10,2004, vol.1, pp.772-776.
[28]S. Mishra, A. Sahai, and R. Brodersen, "Cooperative sensing among cognitive radios," in Proc. of the IEEE International Conference on Communications (ICC),2006.
[29]Amir Ghasemi and Elvino S. Sousa, "Asymptotic Performance of Collaborative Spectrum Sensing under Correlated Log-Normal Shadowing,"IEEE Communications Letters, VOL.11, NO.1, JANUARY 2007
[30]C. Sun, W. Zhang, and K. Letaief, "Cooperative spectrum sensing for cognitive radios under bandwidth constraints," in Proc. IEEE WCNC,2007, pp.1-5.
[31]W. Zhang, R. Mallik, and K. Letaief, "Cooperative spectrum sensing optimization in cognitive radio networks," in IEEE International Conference on Communications, 2008. ICC'08,2008, pp.3411-3415.
[32]E. Visotsky et al., "On collaborative detection of TV transmissions insupport of dynamic spetrum sharing," in Proc. IEEE 1st Symposium onDynamic Spectrum Access Networks (DySPAN'05).
[33]Chunhua Sun, Wei Zhang and Letaief, K.B., "Cooperative Spectrum Sensing for Cognitive Radios under Bandwidth Constraints", in Wireless Communications and Networking Conference,2007.WCNC 2007. IEEE,11-15 March 2007 Page(s):1-5.
[34]A. Ghasemi and E. Sousa, "Impact of User Collaboration on the performance of Sensing-Based Opportunistic Spectrum Access", in Proc. IEEE VTC Fall'06, pp. 1278-1283, Sep.2006. H.
[35]G. Ganesan and Y. G. Li, "Cooperative spectrum sensing in cognitive radio networks," in Proc. IEEE Symp. New Frontiers in Dynamic Spectrum Access Networks (DySPAN'05), Baltimore, USA, Nov.8-11,2005, pp.137-143.
[36]A. Ghasemi and E. S. Sousa, "Collaborative spectrum sensing for opportunistic access in fading environments," in Proc. IEEE Symp. New Frontiers in Dynamic Spectrum Access Networks (DySPAN'05), Baltimore, USA, Nov.8-11,2005, pp. 131-136.
[37]E. Peh and Y.-C. Liang, "Optimization for cooperative sensing in cognitiveradio networks," in Proc. IEEE Int. Wireless Commun. Networking Conf., Hong Kong, Mar. 11-15,2007, pp.27-32.
[38]M. Gandetto and C. Regazzoni, "Spectrum sensing:a distributed approach for cognitive terminals," IEEE J. Select. Areas Commun., vol.25, no.3, pp.546-557, Apr. 2007.
[39]C. Sun, W. Zhang, and K. B. Letaief, "Cluster-based cooperative spectrum sensing for cognitive radio systems," in Proc. IEEE Int. Conf. Commun., Glasgow, Scotland, UK, June 24-28,2007, pp.2511-2515.
[40]X.G.H,Ning.Han,G.B.Zheng,S.H.Sohn and J.Kim, "Weighted-Collaborative Spectrum Sensing in Cognitive Radio," Communications and Networking in China, 2007. CHINACOM '07. Second International Conference on,Aug.2007
[41]P. K. Varshney, "Distributed Detection and Data Fusion, Springer-Verlag, "New York,1997.
[42]Jun Zhao, Haito Zheng, Guang-Hua Yang, "Distributed coordination in dynamic spectrum allocation networks", New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005.2005 First IEEE International Symposium on 8-11 Nov.2005 Page(s):259-268.
[43]P. Qihang, Z. Kun, W. Jun, and L. Shaoqian, "A Distributed Spectrum Sensing Scheme Based on Credibility and Evidence Theory in Cognitive Radio Context," in 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications,2006, pp.1-5.
[44]W. Yang, Y. Cai, Y. Xu, and N. PLAUST, "A fuzzy collaborative spectrum sensing scheme in cognitive radio," in Intelligent Signal Processing and Communication Systems,2007. ISPACS 2007. International Symposium on,2007, pp.566-569.
[45]M. Grabisch, M. Sugeno, and T. Murofushi, Fuzzy measures and integrals:theory and applications. Springer-Verlag New York, Inc. Secaucus, NJ, USA,2000.
[46]Liu Weidong, Lv Tiejun, A Novel Cooperative Spectrum Sensing Scheme Based on Fuzzy Integral Theory in Cognitive Radio Networks, in in Wireless Communications, Networking and Mobile Computing,2009. WiCom '09,2009, pp:1-4.
[2]A. Ghasemi, E.S Sousa, "Sensing in Cognitive Radio Networks:Requirements, Challenges and Design Trade-offs," IEEE Communications Magazine, April 2008: pp.32-39.
[3]N.K. Hoven, " On the feasibility of cognitive radio," Master of Science, University of California, Berkeley, Spring 2005.
[4]J. Mitola, Cognitive radio:making software radios more personal, in IEEE Personal Communications,1999,6(4).
[5]FCC. ET Docket No 03-222 Notice of proposed rule making and order, December, 2003.
[6]S. Haykin, Cognitive radio:brain-empowered wireless communications, in IEEE Journal on Selected Areas in Communications,2005,23(2):128-138.
[7]IEEE802 LAN/MAN Standards Committee 802.22 WG [EB/OL], http://www. ieee802. org/22/.
[8]IEEE 802.16's License-Exempt (LE) Task Group [EB/OL]. http://www. ieee802. org/16/le/.
[9]IEEE P1900 Working Group [EB/OL].
[10]IEEE Std 802.11h-2003 Part 11. Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications Amendment 5:Spectrum and Transmit Power Management Extensions in the 5 GHz band in Europe [S].2003.
[11]IEEE P802.11-Task Group Y-Meeting Update:Status of project IEEE 802.11y [EB/OL]. http://grouper.ieee.org/groups/802/11/Reports/tgy_update.html.
[12]ITU-R Report 2063, "The Impact of Software Defined Radio on IMT-2000, the Future Development of IMT-2000 and Systems Beyond IMT-2000."
[13]ITU-R Report M.2064, "Software-Defined Radio in the Land Mobile Service."
[14]S. M. Kay, Fundamentals of Statistical Signal Processing:Detection Theory. Englewood Cliffs, NJ:Prentice-Hall,1998, vol.2.
[15]E.S.Sousa, Spectrum sensing in cognitive radio networks:requirements, challenges and design trade-offs, in IEEE Communications Magazine,2008, pp:33.
[16]H. Urkowitz, "Energy detection of unknown deterministic signals," Proceeding of the IEEE, Apr.1967,55(4).
[17]F. Digham, M. Alouini, and M. Simon, "On the energy detection of unknown signals over fading channels,"IEEE International Conference on Communications,2003. ICC'03, vol.5,2003.
[18]V. I. Kostylev, "Energy detection of a signal with random amplitude," in Proc. IEEE Int. Conf. Commun., New York, Apr.28-May 2,2002, pp.1606-1610.
[19]曹志刚,钱亚生,《现代通信原理》,清华大学出版社,1992年8月,第1版
[20]H.-S. Chen, W. Gao, and D. G Daut, "Signature based spectrum sensing algorithms for IEEE 802.22 WRAN," in Proc. IEEE Int. Conf. Communications (ICC), Jun.2007.
[21]W.A. Gardner, "Signal Interception:A Unifying Theoretical Framework for Future Detection," IEEE Trans. on Communications,1998.
[22]W.A. Gardner, "Measurement of Spectral Correlation," IEEE Trans. on Signal Processing, Vol. ASSP-34, No.5, Oct.1986.
[23]J. Goerlich, D. Bruchner, and A. Richter, "Signal Analysis Using Spectral Correlation Measurement," IEEE IMTC,1998.
[24]Ye, J Grosspietsch,G Memik, "Spectrum Sensing Using Cyclostationary Spectrum Density for Cognitive Radios,"IEEE Workshop on Signal Processing Systems, pp.1-6,2007.
[25]S.Y Xu, Z.J. Zhao, J.N. Shang,"Spectrum Sensing Based on Cyclostationarity," 2008 Workshop on Power Electronics and Intelligent Transportation System.
[26]A. Sahai, N. Hoven, and R. Tandra, "Some fundamental limits on cognitive radio," in Proc. Allerton Conf. on Commununictions, control, and computing, Monticello, Oct. 2004. V. I. Kostylev, "Energy detection of a signal with random amplitude," in Proc. IEEE Int. Conf. Commun., New York, Apr.28-May 2,2002,pp.1606-1610.
[27]D. Cabric, S. M. Mishra, and R. W. Brodersen, "Implementation issues in spectrum sensing for cognitive radios," in Proc. Asilomar Conf. on Signals, Systems, and Computers, Nov.7-10,2004, vol.1, pp.772-776.
[28]S. Mishra, A. Sahai, and R. Brodersen, "Cooperative sensing among cognitive radios," in Proc. of the IEEE International Conference on Communications (ICC),2006.
[29]Amir Ghasemi and Elvino S. Sousa, "Asymptotic Performance of Collaborative Spectrum Sensing under Correlated Log-Normal Shadowing,"IEEE Communications Letters, VOL.11, NO.1, JANUARY 2007
[30]C. Sun, W. Zhang, and K. Letaief, "Cooperative spectrum sensing for cognitive radios under bandwidth constraints," in Proc. IEEE WCNC,2007, pp.1-5.
[31]W. Zhang, R. Mallik, and K. Letaief, "Cooperative spectrum sensing optimization in cognitive radio networks," in IEEE International Conference on Communications, 2008. ICC'08,2008, pp.3411-3415.
[32]E. Visotsky et al., "On collaborative detection of TV transmissions insupport of dynamic spetrum sharing," in Proc. IEEE 1st Symposium onDynamic Spectrum Access Networks (DySPAN'05).
[33]Chunhua Sun, Wei Zhang and Letaief, K.B., "Cooperative Spectrum Sensing for Cognitive Radios under Bandwidth Constraints", in Wireless Communications and Networking Conference,2007.WCNC 2007. IEEE,11-15 March 2007 Page(s):1-5.
[34]A. Ghasemi and E. Sousa, "Impact of User Collaboration on the performance of Sensing-Based Opportunistic Spectrum Access", in Proc. IEEE VTC Fall'06, pp. 1278-1283, Sep.2006. H.
[35]G. Ganesan and Y. G. Li, "Cooperative spectrum sensing in cognitive radio networks," in Proc. IEEE Symp. New Frontiers in Dynamic Spectrum Access Networks (DySPAN'05), Baltimore, USA, Nov.8-11,2005, pp.137-143.
[36]A. Ghasemi and E. S. Sousa, "Collaborative spectrum sensing for opportunistic access in fading environments," in Proc. IEEE Symp. New Frontiers in Dynamic Spectrum Access Networks (DySPAN'05), Baltimore, USA, Nov.8-11,2005, pp. 131-136.
[37]E. Peh and Y.-C. Liang, "Optimization for cooperative sensing in cognitiveradio networks," in Proc. IEEE Int. Wireless Commun. Networking Conf., Hong Kong, Mar. 11-15,2007, pp.27-32.
[38]M. Gandetto and C. Regazzoni, "Spectrum sensing:a distributed approach for cognitive terminals," IEEE J. Select. Areas Commun., vol.25, no.3, pp.546-557, Apr. 2007.
[39]C. Sun, W. Zhang, and K. B. Letaief, "Cluster-based cooperative spectrum sensing for cognitive radio systems," in Proc. IEEE Int. Conf. Commun., Glasgow, Scotland, UK, June 24-28,2007, pp.2511-2515.
[40]X.G.H,Ning.Han,G.B.Zheng,S.H.Sohn and J.Kim, "Weighted-Collaborative Spectrum Sensing in Cognitive Radio," Communications and Networking in China, 2007. CHINACOM '07. Second International Conference on,Aug.2007
[41]P. K. Varshney, "Distributed Detection and Data Fusion, Springer-Verlag, "New York,1997.
[42]Jun Zhao, Haito Zheng, Guang-Hua Yang, "Distributed coordination in dynamic spectrum allocation networks", New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005.2005 First IEEE International Symposium on 8-11 Nov.2005 Page(s):259-268.
[43]P. Qihang, Z. Kun, W. Jun, and L. Shaoqian, "A Distributed Spectrum Sensing Scheme Based on Credibility and Evidence Theory in Cognitive Radio Context," in 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications,2006, pp.1-5.
[44]W. Yang, Y. Cai, Y. Xu, and N. PLAUST, "A fuzzy collaborative spectrum sensing scheme in cognitive radio," in Intelligent Signal Processing and Communication Systems,2007. ISPACS 2007. International Symposium on,2007, pp.566-569.
[45]M. Grabisch, M. Sugeno, and T. Murofushi, Fuzzy measures and integrals:theory and applications. Springer-Verlag New York, Inc. Secaucus, NJ, USA,2000.
[46]Liu Weidong, Lv Tiejun, A Novel Cooperative Spectrum Sensing Scheme Based on Fuzzy Integral Theory in Cognitive Radio Networks, in in Wireless Communications, Networking and Mobile Computing,2009. WiCom '09,2009, pp:1-4.