用於感知無線電之能量頻譜感測技術

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：73

、訪客IP：3.17.110.119

姓名

邱瑜琪(Yu-Chi Chiu) 查詢紙本館藏

畢業系所

通訊工程學系

論文名稱

用於感知無線電之能量頻譜感測技術
(Energy Detection Techniques Based Spectrum Sensing for Cognitive Radios)

相關論文

★ 運用SIFT特徵進行光學影像目標識別	★ 語音關鍵詞辨識擷取系統
★ 適用於筆記型電腦之WiMAX天線研究	★ 應用於凱氏天線X頻段之低雜訊放大器設計
★ 適用於802.11a/b/g WLAN USB dongle曲折型單極天線設計改良	★ 應用於行動裝置上的雙頻(GPS/BT)天線
★ SDH設備單體潛伏性障礙效能分析與維運技術	★ 無風扇嵌入式觸控液晶平板系統小型化之設計
★ 自動化RFID海關通關系統設計	★ 發展軟體演算實現線性調頻連續波雷達測距系統之設計
★ 近場通訊之智慧倉儲管理	★ 在Android 平台上實現NFC 室內定位
★ Android應用程式開發之電子化設備巡檢	★ 鏈路預算估測預期台灣衛星通訊的發展
★ 在中上衰落通道中分集結合技術之二階統計特性	★ 先進長程演進系統中載波聚合技術的初始同步

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

隨著無線通訊技術的快速成長，傳輸頻帶的需求也日益增加。根據量測，大部分的頻帶在特定時間裡都是沒有使用的。為了提升頻譜的使用效率，感知無線電的概念被提出，如何在不干擾主要使用者的前提下偵測到未使用的頻帶，使次要使用者充分利用頻段，已經成為一個重要的研究議題。
　　快速且準確的頻譜偵測是實現感知無線電網路的基本要求。在本文中，我們在不需要偵測通道的資訊，也不限制偵測的訊號種類的前提下，根據能量偵測的方法分析研究了幾種同時偵測多條頻帶的快速頻譜偵測演算法。接著本篇論文中提出一利用最大正差值(maximum and positive peak algorithm, MPP) 檢測的演算法，在犧牲些微效能的情況下，可節省大量的偵測時間。根據實驗模擬結果，我們提出的演算法，其效能與快速偵測的優點皆能符合實現感知無線電網路的基本需求。

摘要(英)

With fast growing of the wireless communication technology, radio wave is an important resource in transmitting signal. However, according to several measurements, large amounts of spectrum are unused at the particular moment. Due to the electromagnetic radio spectrum is a natural resource, the appropriate spectrum usage is an important issue. For the great utilization of spectrum, how to find a spectrum hole to use has becoming an interesting issue in cognitive radios.
To implement any cognitive radios (CR) network, a fundamental functional requirement is the availability of a multitude of fast and accurate spectrum sensing technique. Various fast spectrum sensing algorithms which require no information about the sensed channel and the primary signal structure in multiple-channel scenarios would be investigated. In this study, a fast censoring multi-tone energy detection algorithm called maximum and positive peak algorithm (MPP) is proposed. The performance of proposed algorithm is compared with several censoring algorithms by computer simulations and their computational complexities. Numerical results show that the proposed algorithm does provide satisfactory performance instantaneously.

關鍵字(中)

★ 多通道能量偵測
★ 固定誤警率
★ 頻譜感測

關鍵字(英)

★ spectrum sensing
★ multi-tone energy detector
★ censoring
★ constant false alarm rate

論文目次

ABSTRACT ......................................................................................... ii
Contents ............................................................................................... iii
List of Figures ..................................................................................... iv
List of Tables ....................................................................................... v
Chapter 1 Introduction .................................................................... 1
Chapter 2 Spectrum Sensing Algorithm ........................................ 3
2.1 Neyman Pearson Criterion............................................................................. 3
2.2 Energy detector .............................................................................................. 5
2.3 Signal of digital television ............................................................................. 6
2.4 SUI channel model ...................................................................................... 10
Chapter 3 Energy Detector ........................................................... 16
3.1 System model of multi-tone detector .......................................................... 16
3.2 The cell-averaging (CA) algorithm ............................................................. 21
3.3 Censoring ..................................................................................................... 23
3.3.1 The consecutive mean excision algorithm ................................... 23
3.3.2 The forward consecutive mean excision algorithm ...................... 24
3.4 Iterative detector .......................................................................................... 25
3.4.1 CA detector with CA censoring .................................................... 25
3.4.2 CA detector with BCME censoring .............................................. 28
3.4.3 CA detector with FCME censoring .............................................. 30
3.5 The maximum positive peak algorithm ....................................................... 32
3.5.1 CA detector with MPP censoring ................................................. 34
Chapter 4 Simulation Results .......................................................... 36
Chapter 5 Conclusion ....................................................................... 42
Bibliography ...................................................................................... 43

參考文獻

[1] Joseph Mitola III and Gerald Q. Maguire, Jr, “Cognitive Radio: Making software more
personal,” Personal Communications, IEEE, 6:13-18, Aug. 1999.
[2] Steven M. Kay, “Fundamentals of Statistical Signal Processing Volume II Detection
Theory,” vol. II, 1998, Prentice Hall. pp. 24-65.
[3] Harry Urkowitz, “Energy detection of unknown deterministic signals,” Proceedings of the
IEEE, vol 55, No.4, April 1967
[4] Hyoung-Nam Kim, Yong-Tae Lee, and Seung Won Kim, “Mathematical modeling of
VSB-based digital television system,” ETRI Journal, Vol.25, No.1, pp.9-18, Feb. 2003
[5] “ATSC Recommended Practice A/54A: Guide to the Use of the ATSC Digital Television
Standard,” Dec. 2003
[6] “Channel model for fixed wireless applications,” IEEE 802.16.3c-01/29r4, July 2001.
[7] Steve Shellhammer, Victor Tawil, Gerald Chouinard, Max Muterspaugh, Monisha Ghosh,
“Spectrum Sensing Simulation Model,” IEEE 802.22-06/0028r5 Mar. 2006.
[8] Steve Shellhammer and Gerald Chouinard, “Spectrum Sensing Requirements Summary,”
IEEE 802.22-06/0089r5, July 2006.
[9] Jonne J, Johanna V, Markku J Harri S, “Spectrum sensing with forward methods,” IEEE
Military Communications Conference, Oct. 2006.
[10] J. Lehtomaki, M. Juntti, H. Sarrnisarri, “CFAR strategies for channelized radiometer,”
IEEE signal processing Lett., vol 12, no.1, pp.13-16, Jan. 2005.
[11] H. Saarnisaari, P. Henttu, and M.Juntti, “Iterative multidimensional impulse detectors
based on the classical diagnostic methods,” IEEE Trans. Commun., vol. 53, no. 3, pp.
395-398, Mar. 2005.
[12] Janne Lehtomaki, “Analysis of energy based signal detection,” Ph.D. dissertation,
Faculity of Technology, University of Oulu, Finland, Dec. 2005. [Online]. Available:
44
http://herkules.oulu.fi/isbn9514279255/
[13] Harri Saarnisaari, Pertti Henttu, “Impulse detection and rejection methods for radio
systems,” in Proc. IEEE Military Commun. Conf., vol. 2, Oct. 2003, pp. 1126-1131.
[14] P. Henttu and S. Aromaa, “Consecutive mean excision algorithm,” in Proc. IEEE Int.
Symp. Spread Spectrum Techniques, Applicat., Prague, Czech Republic, 2002, pp.
45-454.
[15] Jia-Chin Lin, “A modified sequential acquisition scheme in direct-sequence
spread-spectrum communications over a fading channel,” IEICE Trans. Commun., vol.
E83-B, no. 10, pp. 2442-2446, Oct. 2000.

指導教授

林嘉慶(Jia-Chin Lin)

審核日期

2010-7-21

推文