认知无线电中的协作频谱感知技术研究
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摘要
认知无线电是一种解决频谱稀缺的有效途径,作为下一代网络发展中的关键技术正受到越来越多的关注,而频谱感知作为认知无线电网络中的重要技术近年来也成为了研究的热点。协作频谱感知是在单用户频谱感知技术上发展起来的,通过利用认知无线电用户的分集作用提高感知的准确度和灵敏度。本文在总结了现有各种协作频谱感知方法的基础上,着重研究了以下问题:
首先,重点研究了采用双门限能量检测的协作频谱感知,分析了一种“β-比”融合准则,以提高系统感知准确度。理论推导并仿真了感知信道(sensing channel)为AWGN信道或Rayleigh衰落信道,汇报信道(reporting channel)理想或非理想时的系统性能参数,并与采用“与”规则和“或”规则融合时的情况做了比较,得出结论:“β-比”融合准则在提高系统感知准确度和降低传输开销方面都具有较明显的优势。
其次,本文还针对协作频谱感知中存在的异步问题,构建了一种基于异步分布式融合的协作频谱感知模型,推导了此模型在似然比准则下的最优融合方案,并分析了一种不需要主用户先验信息的次优方案——最大后验概率(MAP)估计-K秩规则融合方案。分别对采用这两种方案时的系统性能进行了理论分析和仿真,仿真结果显示两种方案都能有效提高频谱感知的可靠性。
Cognitive radio (CR), an innovative technology to mitigate the spectrum scarcity problem, is being paid on increasingly attention as a key technology in the next-generation wireless network. And spectrum sensing, one of the most important issues in CR networks, has become a hot research topic in recent years. Cooperative spectrum sensing can improve the inference accuracy and sensitivity by using diversity of CR users. This thesis summarizes existing cooperative spectrum sensing schemes, and then focuses on the following two issues:
First, and then cooperative spectrum sensing using double threshold energy detection is investigated. A fusion rule called‘β-ratio’rule is analyzed for improving the accuracy of sensing. The performance parameters of the sensing system whose sensing channel is AWGN channel or Rayleigh fading channel, and reporting channel is perfect or imperfect are derived and then simulated, which are compared with those of a system based on‘and’fusion rule or‘or’fusion rule. The conclusion is that‘β-ratio’rule has quite obvious superiority both on improving sensing accuracy and reducing transmission overheads.
Second, a cooperative spectrum sensing model is proposed based on asynchronous distributed fusion. An optimal fusion rule is derived, and a suboptimal scheme, maximum posteriori probability (MAP) estimate-K-rank fusion scheme is analyzed, which does not require prior knowledge of primary user. The probabilities of system by using these two schemes are theoretically analyzed and then simulated respectively. Simulation results show that both of them could improve spectrum sensing reliability effectively.
首先,重点研究了采用双门限能量检测的协作频谱感知,分析了一种“β-比”融合准则,以提高系统感知准确度。理论推导并仿真了感知信道(sensing channel)为AWGN信道或Rayleigh衰落信道,汇报信道(reporting channel)理想或非理想时的系统性能参数,并与采用“与”规则和“或”规则融合时的情况做了比较,得出结论:“β-比”融合准则在提高系统感知准确度和降低传输开销方面都具有较明显的优势。
其次,本文还针对协作频谱感知中存在的异步问题,构建了一种基于异步分布式融合的协作频谱感知模型,推导了此模型在似然比准则下的最优融合方案,并分析了一种不需要主用户先验信息的次优方案——最大后验概率(MAP)估计-K秩规则融合方案。分别对采用这两种方案时的系统性能进行了理论分析和仿真,仿真结果显示两种方案都能有效提高频谱感知的可靠性。
Cognitive radio (CR), an innovative technology to mitigate the spectrum scarcity problem, is being paid on increasingly attention as a key technology in the next-generation wireless network. And spectrum sensing, one of the most important issues in CR networks, has become a hot research topic in recent years. Cooperative spectrum sensing can improve the inference accuracy and sensitivity by using diversity of CR users. This thesis summarizes existing cooperative spectrum sensing schemes, and then focuses on the following two issues:
First, and then cooperative spectrum sensing using double threshold energy detection is investigated. A fusion rule called‘β-ratio’rule is analyzed for improving the accuracy of sensing. The performance parameters of the sensing system whose sensing channel is AWGN channel or Rayleigh fading channel, and reporting channel is perfect or imperfect are derived and then simulated, which are compared with those of a system based on‘and’fusion rule or‘or’fusion rule. The conclusion is that‘β-ratio’rule has quite obvious superiority both on improving sensing accuracy and reducing transmission overheads.
Second, a cooperative spectrum sensing model is proposed based on asynchronous distributed fusion. An optimal fusion rule is derived, and a suboptimal scheme, maximum posteriori probability (MAP) estimate-K-rank fusion scheme is analyzed, which does not require prior knowledge of primary user. The probabilities of system by using these two schemes are theoretically analyzed and then simulated respectively. Simulation results show that both of them could improve spectrum sensing reliability effectively.
引文
[1] W. Krenik, A. Batra. Cognitive radio techniques for wide area networks. Design Automation Conference, California,USA. June 2005:409-412.
[2] R. W. Brodersen, A . Wolisz, D. Cabric, S. M. Mishra, D.Willkomm. CORVUS: a cognitive radio approach for usage of virtual unlicensed spectrum. BWRC White paper, 2004.
[3] FCC, ET Docket No 03-222 Notice of proposed rule making and order, Dec. 2003.
[4] Mitola J. Cognitive radio: An integrated agent architecture of software defined radio. Doctor of Technology, Royal Inst. Technol. (KTH), Stockholm, Sweden, 2000.
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[6] Mitola J. Cognitive Radio for flexible mobile multimedia communications. Mobile Multimedia Communications, 1999. (MoMuC '99) 1999 IEEE International Workshop on, Nov. 1999: 15-17.
[7]周小飞,认知无线电原理及应用.北京:北京邮电大学出版社, 2007.
[8] S. Haykin, Cognitive radio: brain-empowered wireless communications, IEEE journal on Selected Areas in Communications, 2005, 23(2): 201-220,.
[9] I. F. Akylidiz, W. Y. Lee, M. C. Vuran, and S. Mohanty, NeXt generation/dynamic spectrum access/ cognitive radio wireless networks: A survey, Computer Networks, 2006, 50: 2127-2159,.
[10] K. Hamdi and K. B. Letaief, Cooperative communications for cognitive radio networks, in The 8th Annual Postgraduate Symposium, The Convergence of Telecommunications, Networking and Broadcasting, Liverpool John Moores University, June 2007.
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[12] Visotsky, S. Kuffner, and R. Peterson, On collaborative detection of TV transmissions in support of dynamic spectrum sensing, in IEEE Symposium DySPAN, Baltimore, Nov 2005.
[13] A. Ghasemi and E. S. Sousa, Collaborative spectrum sensing for opportunistic access in fading environments, in IEEE Symposium DySPAN, Baltimore, Nov 2005.
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[16] F. F. Digham, M. S. Alouini, and M. K. Simon, On the energy detection of unknown signals over fading channels, in Proc. IEEE Int. Conf. on Commun., May 2003, 5: 3575-3579.
[17] G. Ganesan and Y. G. Li, Cooperative spectrum sensing in cognitive radio–part I: Two User Networks, IEEE Transactions on Wireless Communications, 2007, 6(6): 2204– 2213.
[18] G. Ganesan and Y. G. Li, Cooperative spectrum sensing in cognitive radio–part II: multiuser networks, IEEE Transactions on Wireless Communications, 2007 , 6(6): 2214 - 2222.
[19] Jun Ma and Ye Li, Soft combination and detection for cooperative spectrum sensing in cognitive radio networks, IEEE Transactions on Wireless Communications, Nov. 2008,7(11): 4502-4507.
[20] C. Sun, W. Zhang, and K. B. Letaief, Cooperative spectrum sensing for cognitive radios under bandwidth constraints, Proc. IEEE Int. Wireless Commun. And Networking Conf. (Hong Kong), Mar. 2007.
[21] C. Lee, W. Wolf, Multiple access-inspired cooperative spectrum sensing for cognitive radio, in IEEE Military Communications Conference, Orlando, FL, Oct. 2007.
[22] T. C. Aysal, S. Kandeepan, and R. Piesiewicz, Cooperative spectrum sensing over imperfect channels, in Proc of BWA Workshop at the IEEE Conf on GLOBECOM, Dec. 2008.
[23] T. C. Aysal, S. Kandeepan, and R. Piesiewicz, Cooperative spectrum sensing with noisy hard decision transmissions, in IEEE Conf ICC, Dresden, ,Jun. 2009.
[24] S. Kandeepan, A. B. Rahim, T. C. Aysal and R. Piesiewicz, Time divisional and time-frequency divisional cooperative spectrum sensing. 4th International Conference on CROWNCOM, 2009.
[25] J.G. Proakis, Digital Communications, 4th ed. McGraw-Hill, 2001.
[26] R. Tandra and A. Sahai, Fundamental limits on detection in low SNR under noise uncertainty, in Proc. International Conference on Wireless Networks, Communications and Mobile Computing, Jun. 2005: 464-469.
[27] D. Cabric, S. M. Mishra and R. W. Brodersen, Implementation issues in spectrum sensing for cognitive radios, in Proc. Asilomar Conference on Signals, Systems, and Computers, Nov. 2004: 772-776.
[28] A. Sahai, N. Hoven, R. Tandra, Some fundamental limits in cognitive radio, Allerton Conf. on Communications, Control and Computing 2004,Oct. 2004.
[29] R. Chen, J. Park and K. Bian. Robust distributed spectrum sensing in cognitive radio networks. Technical Report TR-ECE-06-07, 2006.
[30]谭学治,姜靖,孙洪剑.认知无线电的频谱感知技术研究.通信技术. 2007(3):61-63.
[31]吕雄.认知无线电频谱检测技术浅析.中国水运.2008(11):145-147.
[32]彭少谦.认知无线电中频谱感知技术研究.电子科技大学,2007.
[33]江莹,杨震.认知无线电的几种频谱感知方法研究.科技资讯.2007(10):6-7.
[34] B. Wild, K. Ramchandran. Detecting primary receivers for cognitive radio applications. in: Proceedings of 2005 First IEEE International Symposium, MD, USA. Piscataway, NJ, USA, IEEE Computer Society 2004: 124-130.
[35] E. Hossain, V. Bhargava. Cognitive wireless networks. New York: Springer, 2007.
[36] P. J. Kolodzy. Interference temperature: a metric for dynamic spectrum utilization. International Journal of Network Management, 2006, (16): 103-113.
[37]邓韦.认知无线电中频谱感知技术的研究. Science& Technology Information, 2008, (32): 101-102.
[38] T. Weiss, J. Hillenbrand, an F. Jondral, A diversity approach for the detection of idle spectral resources in spectrum pooling systems, The 48th International Scientific Colloquium, 2003 :37-38.
[39] W. Wang, et al., On the distributed cooperative spectrum sensing for cognitive radio, International Symposium on Communications and Information Technologies(ISCIT’07), Oct. 2007: 1496-1501.
[40] A. K Kattepur, A. T. Hoang , Y. Liang , et al. Data and Decision Fusion for Distributed Spectrum Sensing in Cognitive Radio Networks[C]∥Processing of 2007 6th International Conference on InformationCommunications& Signal Piscataway: IEEE, 2007: 1-5.
[41] S. M. Kay,Fundamentals of Statistical Signal Processing: Detection Theory, 1st ed. NJ: Prentice-Hall, 1998: 60-93.
[42] Z. Quan, S. Cui and A. H. Sayed. An optimal strategy for cooperative spectrum sensing in cognitive radio networks, IEEE Global Telecommunications Conference(GLOBLECOM’07), Nov. 2007: 2947-1951.
[43] A. Fehske, J. Caeddert, and J. H. Reed, A new approach to signal classification using spectral correlation and neural neutral networks, IEEE DySPAN 2005, Nov. 2005: 131-136.
[44] A. Goldsmith, Wireless Communications, Cambridge University Press, 2004.
[45] M. Zou, C. Zhao, B. Shen and K. Kwak, Cooperative spectrum sensing using DF cooperative diversity protocol in cognitive radio, IEEE ISCIT. 2008: 604-608.
[46] H. Urkowitz. Energy detection of unknown deterministic signals, Proc. IEEE. 1967, 55(4): 523–531.
[47]杨露菁,余华.多源信息融合理论与应用.北京:北京邮电大学出版社, 2006.
[48] P. Varshney. Distributed Detection and Data Fusion. New York: Springer Verlag, 1996.
[49] J. G. Proakis. Digital Communications (4th ed). Beijing: Publishing House of Electronics Industry, 2006.
[50]盛骤,谢式千,潘承毅.概率论与数理统计.北京:高等教育出版社, 2001.
[2] R. W. Brodersen, A . Wolisz, D. Cabric, S. M. Mishra, D.Willkomm. CORVUS: a cognitive radio approach for usage of virtual unlicensed spectrum. BWRC White paper, 2004.
[3] FCC, ET Docket No 03-222 Notice of proposed rule making and order, Dec. 2003.
[4] Mitola J. Cognitive radio: An integrated agent architecture of software defined radio. Doctor of Technology, Royal Inst. Technol. (KTH), Stockholm, Sweden, 2000.
[5] Mitola J, Maguire G. Jr. . Cognitive Radio: Making software radios more personal. IEEE Personal Communications Magazine, 1999, 6(4): 13-18.
[6] Mitola J. Cognitive Radio for flexible mobile multimedia communications. Mobile Multimedia Communications, 1999. (MoMuC '99) 1999 IEEE International Workshop on, Nov. 1999: 15-17.
[7]周小飞,认知无线电原理及应用.北京:北京邮电大学出版社, 2007.
[8] S. Haykin, Cognitive radio: brain-empowered wireless communications, IEEE journal on Selected Areas in Communications, 2005, 23(2): 201-220,.
[9] I. F. Akylidiz, W. Y. Lee, M. C. Vuran, and S. Mohanty, NeXt generation/dynamic spectrum access/ cognitive radio wireless networks: A survey, Computer Networks, 2006, 50: 2127-2159,.
[10] K. Hamdi and K. B. Letaief, Cooperative communications for cognitive radio networks, in The 8th Annual Postgraduate Symposium, The Convergence of Telecommunications, Networking and Broadcasting, Liverpool John Moores University, June 2007.
[11] S. M. Mishra, A. Sahai, and R. Brodersen, Cooperative sensing among cognitive radios, in IEEE Conf ICC, Istanbul, June 2006.
[12] Visotsky, S. Kuffner, and R. Peterson, On collaborative detection of TV transmissions in support of dynamic spectrum sensing, in IEEE Symposium DySPAN, Baltimore, Nov 2005.
[13] A. Ghasemi and E. S. Sousa, Collaborative spectrum sensing for opportunistic access in fading environments, in IEEE Symposium DySPAN, Baltimore, Nov 2005.
[14] Z. Quan, S. Cui,and A. H. Sayed, Optimal linear cooperation for spectrum sensing in cognitive radio networks, IEEE Journal on Selected Areas in Signal Processing, 2008, 2(1).
[15] Z. Quan, S. Cui, A. H. Sayed, and V. H. Poor, Wideband spectrum sensing in cognitive radio networks,in IEEE International Conference on Communications, Beijing, China, May 2008.
[16] F. F. Digham, M. S. Alouini, and M. K. Simon, On the energy detection of unknown signals over fading channels, in Proc. IEEE Int. Conf. on Commun., May 2003, 5: 3575-3579.
[17] G. Ganesan and Y. G. Li, Cooperative spectrum sensing in cognitive radio–part I: Two User Networks, IEEE Transactions on Wireless Communications, 2007, 6(6): 2204– 2213.
[18] G. Ganesan and Y. G. Li, Cooperative spectrum sensing in cognitive radio–part II: multiuser networks, IEEE Transactions on Wireless Communications, 2007 , 6(6): 2214 - 2222.
[19] Jun Ma and Ye Li, Soft combination and detection for cooperative spectrum sensing in cognitive radio networks, IEEE Transactions on Wireless Communications, Nov. 2008,7(11): 4502-4507.
[20] C. Sun, W. Zhang, and K. B. Letaief, Cooperative spectrum sensing for cognitive radios under bandwidth constraints, Proc. IEEE Int. Wireless Commun. And Networking Conf. (Hong Kong), Mar. 2007.
[21] C. Lee, W. Wolf, Multiple access-inspired cooperative spectrum sensing for cognitive radio, in IEEE Military Communications Conference, Orlando, FL, Oct. 2007.
[22] T. C. Aysal, S. Kandeepan, and R. Piesiewicz, Cooperative spectrum sensing over imperfect channels, in Proc of BWA Workshop at the IEEE Conf on GLOBECOM, Dec. 2008.
[23] T. C. Aysal, S. Kandeepan, and R. Piesiewicz, Cooperative spectrum sensing with noisy hard decision transmissions, in IEEE Conf ICC, Dresden, ,Jun. 2009.
[24] S. Kandeepan, A. B. Rahim, T. C. Aysal and R. Piesiewicz, Time divisional and time-frequency divisional cooperative spectrum sensing. 4th International Conference on CROWNCOM, 2009.
[25] J.G. Proakis, Digital Communications, 4th ed. McGraw-Hill, 2001.
[26] R. Tandra and A. Sahai, Fundamental limits on detection in low SNR under noise uncertainty, in Proc. International Conference on Wireless Networks, Communications and Mobile Computing, Jun. 2005: 464-469.
[27] D. Cabric, S. M. Mishra and R. W. Brodersen, Implementation issues in spectrum sensing for cognitive radios, in Proc. Asilomar Conference on Signals, Systems, and Computers, Nov. 2004: 772-776.
[28] A. Sahai, N. Hoven, R. Tandra, Some fundamental limits in cognitive radio, Allerton Conf. on Communications, Control and Computing 2004,Oct. 2004.
[29] R. Chen, J. Park and K. Bian. Robust distributed spectrum sensing in cognitive radio networks. Technical Report TR-ECE-06-07, 2006.
[30]谭学治,姜靖,孙洪剑.认知无线电的频谱感知技术研究.通信技术. 2007(3):61-63.
[31]吕雄.认知无线电频谱检测技术浅析.中国水运.2008(11):145-147.
[32]彭少谦.认知无线电中频谱感知技术研究.电子科技大学,2007.
[33]江莹,杨震.认知无线电的几种频谱感知方法研究.科技资讯.2007(10):6-7.
[34] B. Wild, K. Ramchandran. Detecting primary receivers for cognitive radio applications. in: Proceedings of 2005 First IEEE International Symposium, MD, USA. Piscataway, NJ, USA, IEEE Computer Society 2004: 124-130.
[35] E. Hossain, V. Bhargava. Cognitive wireless networks. New York: Springer, 2007.
[36] P. J. Kolodzy. Interference temperature: a metric for dynamic spectrum utilization. International Journal of Network Management, 2006, (16): 103-113.
[37]邓韦.认知无线电中频谱感知技术的研究. Science& Technology Information, 2008, (32): 101-102.
[38] T. Weiss, J. Hillenbrand, an F. Jondral, A diversity approach for the detection of idle spectral resources in spectrum pooling systems, The 48th International Scientific Colloquium, 2003 :37-38.
[39] W. Wang, et al., On the distributed cooperative spectrum sensing for cognitive radio, International Symposium on Communications and Information Technologies(ISCIT’07), Oct. 2007: 1496-1501.
[40] A. K Kattepur, A. T. Hoang , Y. Liang , et al. Data and Decision Fusion for Distributed Spectrum Sensing in Cognitive Radio Networks[C]∥Processing of 2007 6th International Conference on InformationCommunications& Signal Piscataway: IEEE, 2007: 1-5.
[41] S. M. Kay,Fundamentals of Statistical Signal Processing: Detection Theory, 1st ed. NJ: Prentice-Hall, 1998: 60-93.
[42] Z. Quan, S. Cui and A. H. Sayed. An optimal strategy for cooperative spectrum sensing in cognitive radio networks, IEEE Global Telecommunications Conference(GLOBLECOM’07), Nov. 2007: 2947-1951.
[43] A. Fehske, J. Caeddert, and J. H. Reed, A new approach to signal classification using spectral correlation and neural neutral networks, IEEE DySPAN 2005, Nov. 2005: 131-136.
[44] A. Goldsmith, Wireless Communications, Cambridge University Press, 2004.
[45] M. Zou, C. Zhao, B. Shen and K. Kwak, Cooperative spectrum sensing using DF cooperative diversity protocol in cognitive radio, IEEE ISCIT. 2008: 604-608.
[46] H. Urkowitz. Energy detection of unknown deterministic signals, Proc. IEEE. 1967, 55(4): 523–531.
[47]杨露菁,余华.多源信息融合理论与应用.北京:北京邮电大学出版社, 2006.
[48] P. Varshney. Distributed Detection and Data Fusion. New York: Springer Verlag, 1996.
[49] J. G. Proakis. Digital Communications (4th ed). Beijing: Publishing House of Electronics Industry, 2006.
[50]盛骤,谢式千,潘承毅.概率论与数理统计.北京:高等教育出版社, 2001.