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研究生:李孟哲
研究生(外文):Lee, Mong-Zhe
論文名稱:在感知無線電網路中使用權重式匯整規則做合作式頻譜感測
論文名稱(外文):Cooperative Spectrum Sensing Using a Weighted Fusion Rule for Cognitive Radio Networks
指導教授:李程輝
指導教授(外文):Lee, Tsern-Huei
學位類別:碩士
校院名稱:國立交通大學
系所名稱:電信工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2011
畢業學年度:99
語文別:英文
論文頁數:28
中文關鍵詞:感知無線電網路頻譜感測權重駭客
外文關鍵詞:CR networkspectrum sensingweighthacker
相關次數:
  • 被引用被引用:0
  • 點閱點閱:182
  • 評分評分:
  • 下載下載:10
  • 收藏至我的研究室書目清單書目收藏:0
  在感知網路中,每個感知使用者和主要使用者距離不盡相同,可能受到訊號干擾及衰減影響其感測能力,而硬體故障、駭客攻擊,也會導致錯誤的判定。合作式頻譜感測是一種能讓失敗偵測機率及錯誤預警機率降低的辦法,因此匯整規則就顯得相當重要,好的匯整規則足以因應感知網路的各種環境,讓判定錯誤率降到極低。現存一些匯整規則,譬如OR規則、AND規則、多數決規則,它們的錯誤率仍非令人滿意,因此權重式匯整規則因應而生,給予信賴度較高的感知使用者較高的權重,即使於不穩定的網路環境,仍有較正確的判定機率。因此在這篇學位論文裡,我們提出一種新的權重式匯整規則,有別於之前提出的匯整規則,更能在未知多變的網路環境,使得誤判率下降,進而讓感知使用者在不影響主要使用者的前提下,得到更高的吞吐量。
In cognitive radio (CR) networks, because the distance of every CR user and the primary user is different, a signal may have interference and attenuation that affect the sensing ability of CR users. A CR user in mal-function or being hacked also results in wrong decision. Cooperative spectrum sensing is a way to decrease the probability of miss detection and the probability of false alarm. Therefore, the fusion rule is remarkably important. A good fusion rule is suitable for various circumstances because it can decrease significantly error probability. The error rate of existing data fusion techniques, such as OR rule, AND rule, and Majority rule, are still not satisfactory. Consequently, a weighted fusion rule is proposed so that reliable CR users are given higher weights. It still makes better decision under unstable networks. Hence in this thesis, we propose a weighted fusion rule that differs from previous weighted fusion rule. It can decrease the probability of wrong decision in unknown and changing networks. Furthermore, CR networks have higher throughput under the promise of avoiding interference to the primary user.
摘要 ………………………………………………………………… i
Abstract …………………………………………………………… ii
誌謝 ………………………………………………………………… iii
Contents …………………………………………………………… iv
List of Tables …………………………………………………… v
List of Figures ………………………………………………… vi
Notation …………………………………………………………… vii
Chapter 1 Introduction ………………………………………… 1
Chapter 2 Background …………………………………………… 3
2.1 Local Spectrum Sensing ……………………………… 3
2.2 Cooperative Spectrum Sensing ……………………… 5
2.3 Existing Data Fusion Techniques ………………… 6
2.4 Throughput ……………………………………………… 7
Chapter 3 Related Works ……………………………………… 10
3.1 Weighted Fusion Rule ………………………………… 10
3.2 SPRT and WSPRT ………………………………………… 12
Chapter 4 Proposed Weighted Fusion Rule ………………… 14
Chapter 5 Simulation Results ………………………………… 19
Chapter 6 Conclusion …………………………………………… 27
Reference ………………………………………………………… 28

[1] Ghasemi, E. S. Sousa,“Spectrum sensing in cognitive radio
networks: requirements, challenges and design trade-offs,”
IEEE Communications Magazine, vol. 46, no. 4, pp. 32-39, Apr.2008
[2] J. Mitola, G. Q. Maguire, “Cognitive radio: making software
radios more personal,” IEEE Personal Communication, vol.6,
pp.13-18, Aug. 1999.
[3] F. Akyildiz, W. Y. Lee, M. C. Vuran, S. Mohanty, “Next
generation/dynamic spectrum access/cognitive radio wireless
networks: A survey,” Computer Networks, vol. 50, no. 13, pp.
2127-2159, Sep. 2006.
[4] W. Zhang, R. K. Mallik, K. B. Letaief, ”Cooperative spectrum
sensing optimization in cognitive radio networks,” in Proc.
IEEE ICC’08, pp. 3411 – 3415, May 2008.
[5] F. F. Digham, M. S. Alouini, M. K. Simon, “On the energy
detection of unknown signals over fading channels,” in Proc.
IEEE ICC’03, pp. 3575 – 3579, vol. 5, May 2003.
[6] Y. C. Liang, Y. Zeng, C.Y. Peh, A. T. Hoang, “Sensing-
throughput tradeoff for cognitive radio networks,” in IEEE
Trans. on Wireless Communications, vol. 7, no.4, Apr. 2008.
[7] L. Zhengyi, L. Lin, and Z. Chi, “Fast detection method in
cooperative cognitive radio networks,” International Journal of
Digital Multimedia, 2010.
[8] J. Ma, G. Zhao, Y. Li, “Soft combination and detection for
cooperative spectrum sensing in cognitive radio networks,” in
IEEE Trans. on Wireless Communications, vol. 7, no.11, November
2008.
[9] R. Chen, J. M. Park, and K. Bian, “Robust Distributed Spectrum
Sensing in Cognitive Radio Networks,” IEEE INFOCOM, 2008.


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