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博碩士論文 etd-0701109-144206 詳細資訊
Title page for etd-0701109-144206
論文名稱
Title
使用結合能量和循環性穩態檢測器的分散式偵測法於感知無線電中的功率頻譜偵測之應用
A Distributed Detection Scheme by Combining Energy Detectors and Cyclostationarity-Based Detectors for Power Spectrum Sensing in Cognitive Radio
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
29
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2009-06-05
繳交日期
Date of Submission
2009-07-01
關鍵字
Keywords
感知網路、融合中心、頻譜偵測
cognitive, fusion center, spectrum sensing
統計
Statistics
本論文已被瀏覽 5739 次,被下載 2354
The thesis/dissertation has been browsed 5739 times, has been downloaded 2354 times.
中文摘要
在本論文中,我們考慮頻譜感知網路的問題。我們提出一個具有強健性的決策融
合法則,這個法則可以在干擾存在時依然運行良好。明確地說,我們提出了將能
量檢測器和循環性穩態檢測器決策結果利用融合中心融合的頻譜偵測法則。這個
提出的融合法則和其它使用同一類檢測器的決策法則在融合中心融合的功率頻
譜偵測技術有著很大的不同。我們提出的結合架構同時具有能量檢測器和循環性
穩態檢測器的優點。將這篇論文中提出的頻譜偵測架構和其他使用同一種類檢測
器的頻譜偵測架構比較後,結果顯示本論文提出的方法更能抵抗可能存在著的干
擾。
Abstract
In this thesis, the problem of spectrum sensing in cognitive radio communication networks
is considered. This thesis has developed a robust decision fusion scheme that can perform
well when the interference caused by other PUs is present. Specifically, the proposed detection
scheme is based on fusing the local decisions from energy detectors (EDs) and cyclostationarity-
based detectors (CDs). Our proposed fusion scheme is different from other power spectrum
sensing technology being developed so far in that other fusion technology are based on fusing
the local decisions from the same type of detectors. Our proposed fusion scheme can take the
advantage of both EDs and CDs. We compare the proposed scheme with the schemes fusing
the same type of detectors, and the results confirm that the proposed scheme is more robust
against the possible interference.
目次 Table of Contents
1 Introduction 1
1.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Spectrum Sensing Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.3 Research Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.4 Thesis Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.5 Thesis Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2 Spectrum sensing methods for cognitive radio 5
2.1 Energy Detector Based Sensing . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1.1 Energy Detection Characterization . . . . . . . . . . . . . . . . . . . . . 5
2.1.2 Approximation of Gaussian distribution for large N . . . . . . . . . . . . 6
2.2 Cyclostationarity-Based Sensing . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3 Decision Fusion Using ED and CD for Power Spectrum Sensing 12
3.1 Network operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
3.2 Decision fusion with ED and CD . . . . . . . . . . . . . . . . . . . . . . . . . . 12
3.2.1 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
4 Conclusion 20
參考文獻 References
[1] H. Sadeghi and P. Azmi, “A novel primary user detection method for multiple-antenna
cognitive radio,” Proceedings of 2008 IST 2008 International Symposium on Telecommu-
nications, pp. 188-192, Aug. 2008.
[2] D. Cabric, S. M. Mishra, and R. W. Brodersen, “Implementation Issues in Spectrum
Sensing for Cognitive Radios,” Proceedings of the 38h Annual Asilomar Conference on
Signals, Systems and Computers, Nov. 2004.
[3] K. Sridhara, A. Chandra, and P. S. M. Tripathi, “Spectrum Challenges and Solutions by
Cognitive Radio: An Overview,” Wireless Personal Communications, vol. 45, pp. 281-291,
Feb. 2008.
[4] I. Mitora, J. Maguire, and Q. Gerald, “Cognitive radio: making software radios more
personal,” IEEE Personal Communications Magazine, vol. 6, no. 4, pp. 13-18, Aug. 1999.
[5] Federal Communications Commission, “Notice of proposed rule making and order: Facil-
itating opportunities for flexible, efficient, and reliable spectrum use employing cognitive
radio technologies,” ET Docket no. 03-108, Feb. 2005.
[6] T. Yucek and H. Arslan, “A survey of spectrum sensing algorithms for cognitive radio
applications,” IEEE Communications Surveys & Tutorials, vol. 11, no. 1, first quarter
2009.
[7] H. Urkowitz, “Energy detection of unknown deterministic signals,” Proceedings of the
IEEE, vol. 55, no. 4, pp. 523-531, Apr. 1967.
[8] F. F. Digham, M. S. Alouini, and M. K. Simon, “On the Energy Detection of Unknown
Signals Over Fading Channels,” IEEE Transactions on Communications, vol. 55, no. 1,
pp. 21-24, Jan. 2007.
[9] Z. Ye, J. Grosspietsch, and G. Memik, “Spectrum Sensing Using Cyclostationary Spec-
trum Density for Cognitive Radios,” Proceedings of the 2007 IEEE Workshop on signal
Processing Systems, pp. 1-6, Oct. 2007.
[10] W. A. Gardner, “Signal interception: a unifying theoretical framework for feature detec-
tion,” IEEE Transactions on Communications, vol. 36, no. 8, pp. 897-906, Aug. 1988.
[11] A. V. Dandawat and G. B. Giannakis, “Statistical test for presence of cyclostationarity,”
IEEE Transactions on Signal Processing, vol. 42, no. 9, pp. 2355-2369, Sep. 1994.
[12] Q. Peng, K. Zeng, and S. Li, “A Distributed Spectrum Sensing Scheme Based on Credi-
bility and Evidence Theory in Cognitive Radio Context,” Proceedings of 2006 IEEE 17th
International Symposium Personal, Indoor and Mobile Radio Communications, pp. 1-5,
2006.
[13] C. Danijela, T. Artem, and W. B. Robert, “Experimental study of spectrum sensing based
on energy detection and network cooperation,” Proceedings of the first international work-
shop on Technology and policy for accessing spectrum, vol. 222, no. 12, 2006.
[14] H. S. Chen, W. Gao, and D. G. Daut, “Spectrum Sensing Using Cyclostationary Properties
and Application to IEEE 802.22 WRAN,” Proceedings of IEEE GLOBECOM 2007, 2007.
[15] D. Cabric, A. Tkachenko, and R. Brodersen, “Spectrum Sensing measurements of pilot,
energy, and collaborative detection,” Proceedings IEEE Military Communications Confer-
ence, pp. 1-7, Oct. 2006.
[16] A. H. Nuttall, “Some integrals involving the QM function,” IEEE Transactions on Infor-
mation Theory, vol. 21, no. 1, pp. 95-99, Jan. 1975.
[17] Y. Lin and H. Chen, “Subsection-average cyclostationary feature detection in cognitive
radio,” 2008 Int. Conference on Neural Networks and Processing, pp. 604-608, Jun. 2008.
[18] M. Ghozzi, M. Francois, D. Mischa, and J. Palicot, “Cyclostatilonarilty-Based Test for
Detection of Vacant Frequency Bands,” 2006 1st International Conference on Cognitive
Radio Oriented Wireless Networks and Communications, pp. 1-5, Jun. 2006.
[19] P. K. Varshney, Distributed Detection and Data Fusion. New York: Springer, 1997.
[20] G. Ganesan and Y. (Geoffrey) Li “Cooperative Spectrum Sensing in Cognitive Radio, Part
I: Two User Networks,” IEEE Transactions on wireless communications, vol. 6, no. 6, pp.
2204-2213, Jun. 2007.
[21] G. Ganesan and Y. (Geoffrey) Li “Cooperative Spectrum Sensing in Cognitive Radio, Part
II: Multiuser Networks,” IEEE Transactions on wireless communications, vol. 6, no. 6, pp.
2214-2222, Jun. 2007.
[22] H. Cram′er, Mathematical methods of statistics. USA: Princeton University Press, 1999.
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