請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/23332
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 陳少傑(Sao-Jie Chen) | |
dc.contributor.author | Min-Jung Fan-Chiang | en |
dc.contributor.author | 范姜敏容 | zh_TW |
dc.date.accessioned | 2021-06-08T04:59:19Z | - |
dc.date.copyright | 2010-08-20 | |
dc.date.issued | 2010 | |
dc.date.submitted | 2010-08-18 | |
dc.identifier.citation | [1] J. Z. Sun, J. Sauvola, and D. Howie, “Features in Future: 4G Visions from a Technical Perspective,” in Proc. IEEE Global Telecommunications Conference (GLOBECOM ‘01), San Antonio, TX, Nov. 2001, pp. 3533-3537.
[2] Federal Communications Commission (FCC), Spectrum Policy Task Force, ET Docket no. 02-135, Nov. 15, 2002. [3] J. Mitola III and G. Q. Maguire, Jr., “Cognitive Radio: Making Software Radios more Personal,” IEEE Personal Communications, vol. 6, no. 4, pp. 13-18, Aug. 1999. [4] J. Mitola, “Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio,” PhD Dissertation, Royal Institute of Technology (KTH), Sweden, 2000. [5] S. Haykin, “Cognitive Radio: Brain-Empowered Wireless Communications,” IEEE Journal on Selected Areas in Communications, vol. 23, no. 2, pp. 201-220, Feb. 2005. [6] J. Mitola III, 'Software Radio Architecture: A Mathematical Perspective,' IEEE Journal on Selective Areas in Communications, vol. 17, no. 4, pp. 514-538, Apr. 1999. [7] W. Tuttlebee, Software Defined Radio, Enabling Technologies. John Wiley & Sons, Ltd., 1 edition, 2002. [8] International Standard ISO/IEC 8802-11:1999, Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications, IEEE, New York, 1999. [9] International Standard ISO/IEC 8802-11:1999/Amd 1:2000(E) and IEEE Std 802.11a-1999, “Amendment 1: High-Speed Physical Layer in the 5 GHz Band,” in Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications, IEEE, New York, 2000. [10] IEEE Std 802.11b-1999/Cor 1-2001, “Amendment 2: Higher-Speed Physical Layer (PHY) Extension in the 2.4 GHz band—Corrigendum 1,” in Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications, IEEE, New York, 2001. [11] IEEE Standard 802.11g-2003, “Amendment 4: Further Higher Data Rate Extension in the 2.4 GHz Band,” in Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications, IEEE, New York, 2003. [12] IEEE Standard 802.11n-2009, “Amendment 5: Enhancements for Higher Throughput,” in Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications, IEEE, New York, 2009. [13] IEEE Standard 802.16-2004, Part16: Air Interface for Fixed Broadband Wireless Access Systems, IEEE, New York, 2004. [14] IEEE Standard 802.16e-2005, “Amendment for Physical and Medium Access Control Layers for Combined Fxed and Mobile Operation in Licensed Band,” in Part16: Air Interface for Fixed and Mobile Broadband Wireless Access Systems , IEEE, New York, 2005. [15] D. Cabric, S. M. Mishra, R.B. Brodersen, “Implementation Issues in Spectrum Sensing for Cognitive Radios,” in Proc. 38th Annual Asilomar Conference on Signals, Systems and Computers, November 2004. [16] W.A. Gardner, “Signal Interception: A Unifying Theoretical Framework for Feature Detection,” IEEE Trans. on Communications, vol. 36, no. 8, pp. 897-906 August 1988. [17] Texas Instruments, TMS320C6000 CPU and Instruction Set, Literature Number SPRU189F, Oct.2000. [18] Texas Instruments, TMS320C6000 DSP Cache User’s Guide, Literature Number SPRU656A, May 2003. [19] Texas Instruments, Code Composer Studio User’s Guide, Literature Number SPRU328B, Feb. 2000. [20] Texas Instruments, TMS320C6000 Code Composer Studio v3.0 Getting Started Guide, Literature Number SPRU509E, Sep. 2004. [21] Texas Instruments, TMS320C6000 Programmer’s Guide, Literature Number SPRU198G, Oct.2002. [22] Texas Instruments, Signal Processing Examples Using TMS320C64x Digital Signal Processing Library (DSPLIB), Literature Number SPRA884A, Sep.2003. [23] M. Oerder, and H. Meyr, “Digital Filter and Square Timing Recovery,” IEEE Trans. Communications, vol. 36, no. 5, pp. 605-612, May 1988. [24] J. J. van de Beek, M. Sandell, and P. O. Borjesson, “ML Estimation of Timing and Frequency Offset in OFDM Systems,” IEEE Trans. Signal Processing, vol. 45, no. 7, pp. 1800-1805, July 1997. [25] W. Gardner, “Signal Interception: A Unifying Theoretical Framework for Feature Detection,” IEEE Trans. Communications, vol. 36, no. 8, pp. 897–906, Aug. 1988. [26] B. Sadler and A. Dandawate, “Nonparametric Estimation of the Cyclic Cross Spectrum,” IEEE Trans. Information Theory, vol. 44, no. 1, pp. 351–358, Jan. 1998. [27] P. D. Sutton, K. E. Nolan, and L. E. Doyle “Cyclostationary Signatures in Practical Cognitive Radio Applications,” IEEE Journal on Selected Areas in Communications, vol. 26, no. 1, pp. 13-24, Jan. 2008. [28] Texas Instruments, TMS320C64x DSP Library Programmer’s Reference, Literature Number SPRU565B, Oct.2003. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/23332 | - |
dc.description.abstract | 為了徹底使用無線電資源進而增加頻譜使用效率,感知無線電需要偵測環境以及辨識訊號來源,如此次要通訊系統使用者得以和主要通訊系統使用者共存,因此頻譜偵測和感知在感知無線電中扮演著重要的角色。在本篇論文中,我們針對現存多個通訊系統做頻譜偵測的動作,相較於先前技術的單一系統偵測技術,多系統共存將會是未來通訊系統的趨勢而其在頻譜偵測的困難度也更值得進一步探討。當欲偵測頻段的主要使用者不限於一個系統時,頻譜偵測機制將必須有能力分辨訊號是屬於何種系統。因為在不同頻段下有不同的系統共存情形,所以我們也分別選擇不同的技術來做頻譜偵測,其中包含了量測接收訊號強度、偵測正交多工分頻存取訊號的循環性,以及利用譜相關函數得知訊號經由調變而產生的週期性機率特性。軟體定義無線電的可調性被認為適合實現多系統無線電,所以本文選擇將整個頻譜偵測程序用軟體實現,並進一步在數位訊號處理器平台做程式之優化。最後可以得到此多系統頻譜偵測在實際的數位訊號處理器平台上的運算時間。 | zh_TW |
dc.description.abstract | In order to fully exploit wireless radio resource and then increase spectrum efficiency, cognitive radios for future wireless communication systems shall sense wireless environments and identify interference so that the secondary system(s) may coexist with primary communication systems. As a result, sensing and cognition play a major functionality in cognitive radios. In this Thesis, we aimed at the spectrum sensing mechanism under several existing or developing communication systems. Compare to previous technique in single system spectrum sensing, multiple systems coexist will be the future trends in communication systems and the difficulty and complexity on multi-standard spectrum sensing is more worthy of further exploration. The spectrum sensing mechanism is able to detect signals belong to which system, when there are more than one primary users. Depending on different system coexistence situations, we choose different techniques to detect the primary users, which include measurement received signal strength indicator (RSSI), cyclic prefix detection, and spectral correlation function (SCF). Since the flexibility of software defined radio is considered suitable to achieve multi-system radio, we develop our spectrum sensing mechanism in software on an existing digital signal processor platform and perform optimization on the program. | en |
dc.description.provenance | Made available in DSpace on 2021-06-08T04:59:19Z (GMT). No. of bitstreams: 1 ntu-99-R97943127-1.pdf: 1580505 bytes, checksum: c5b11a815b03ad4927684ed3ca7daa9e (MD5) Previous issue date: 2010 | en |
dc.description.tableofcontents | ABSTRACT i
LIST OF FIGURES vii LIST OF TABLES ix CHAPTER 1 INTRODUCTION 1 1.1 Cognitive Radios and Spectrum Sensing 1 1.2 Software Defined Radio 3 1.3 DSP Implementation 4 1.4 Thesis Organization 5 CHAPTER 2 SYSTEM OVERVIEW 7 2.1 Primary Systems 7 2.1.1 802.11b 7 2.1.2 802.11a 10 2.1.3 802.11g 14 2.1.4 802.11n 15 2.1.5 802.16-2004 15 2.1.6 802.16e-2005 16 2.2 CR Systems 17 2.3 Previous Techniques of Spectrum Sensing 18 2.3.1 Energy Detection 19 2.3.2 Matched Filter 21 2.3.3 Cyclostationary Detection 22 2.4 Motivation 24 CHAPTER 3 DSP IMPLEMETATION 25 3.1 Introduction to TMS320C6416 DSP 25 3.1.1 TMS320C6416 Features and Architecture 25 3.1.2 Central Processing Unit 27 3.1.3 Memory Architecture 33 3.2 TI’s Code Development Environment 34 3.3 Code Development Flow 36 3.4 Acceleration Rules 38 3.4.1 Fixed–Point Coding 38 3.4.2 Packet Data Processing 38 3.4.3 Register and Memory Arrangement 39 3.4.4 Loop Unrolling 40 3.4.5 Compiler Optimization Options 41 3.4.6 Software Pipelining 42 3.4.7 Macros and Intrinsic Functions 43 CHAPTER 4 SYSTEM FRAMEWORK 45 4.1 Operate Spectrum and Channels 45 4.2 Signal Characters of Primary Users 46 4.2.1 Cyclic Prefixes in OFDM-based Systems 46 4.2.2 Probability Property 48 4.3 Spectrum Sensing Scenario 48 4.3.1 Received Signal Strength Indicator 50 4.3.2 Cyclic Prefix Detection 50 4.3.3 Spectral Correlation Function Detection 52 CHAPTER 5 DSP SOFTWARE IMPLEMENTATION 55 5.1 Execution Cycle of the Original Programs 55 5.2 Efficiency Enhancement 57 5.2.1 Fixed-Point Coding and Data Flow Bandwidth 57 5.2.2 TI DSP Library Functions 58 5.2.3 Software Pipelining 59 5.3 System Performance 60 5.3.1 RSSI Detector Optimization 60 5.3.2 CP Detector Optimization 61 5.3.3 SCF Detector Optimization 65 5.3.4 Overall Performance 66 CHAPTER 6 CONCLUSION 69 REFERENCE 71 | |
dc.language.iso | en | |
dc.title | 多系統感知無線頻譜偵測技術之數位訊號處理器實現 | zh_TW |
dc.title | DSP Software Implementation of Multi-standard Spectrum Sensing for Cognitive Radio | en |
dc.type | Thesis | |
dc.date.schoolyear | 98-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 曹恆偉(Hen-Wai Tsao),闕志達(Tzi-Dar Chiueh),熊博安(Pao-Ann Hsiung) | |
dc.subject.keyword | 頻譜偵測,感知無線電,軟體定義無線電,數位訊號處理器, | zh_TW |
dc.subject.keyword | Spectrum Sensing,Cognitive Radio,Software Defined Radio,Digital Signal Processor, | en |
dc.relation.page | 73 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2010-08-19 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電子工程學研究所 | zh_TW |
顯示於系所單位: | 電子工程學研究所 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-99-1.pdf 目前未授權公開取用 | 1.54 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。