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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 張進福 | |
| dc.contributor.author | Chin-Fu Ho | en |
| dc.contributor.author | 何錦富 | zh_TW |
| dc.date.accessioned | 2021-06-13T16:39:23Z | - |
| dc.date.available | 2005-07-11 | |
| dc.date.copyright | 2005-07-11 | |
| dc.date.issued | 2005 | |
| dc.date.submitted | 2005-07-04 | |
| dc.identifier.citation | [1] Michael Chryssomallis, “Smart Antennas,” IEEE Antennas and Propagation
Magazine, Vol. 42, No. 3, June 2000. [2] J. C. Liberti JR. and T. S. Rappaport, “Smart Antennas for Wireless Communications : IS-95 and Third Generation CDMA Applications,” Prentice Hall PTR, New Jersey, 1999. [3] J. Irvine, J. -P. Couvy, F. Graziosi, J. Laurila, G. Mossakowski, and P. Robin, “System architecture for the MOSTRAIN project (mobile services for high speed trains),” Vehicular Technology Conference, IEEE 47th Volume 3, pp. 1917-1921 vol.3, 1997. [4] http://www.thsrc.com.tw/ [5] S. Haykin, “Adaptive Filter Ttheory,” 4th edition, Prentice-Hall, Englewood cliffs, NJ, 2002. [6] J. G. McWhirter, and T. J. Shepherd, “Systolic array processor for MVDR beamforming,” Radar and Signal Processing, IEE Proceedings Volume 136, Issue 2, pp. 75-80, 1989. [7] Theodore S. Rappaport, “Wireless Communications: Principles & Practice”, 2nd edition, Prentice Hall, 2002. [8] 3GPP TR 25.943 V4.1.0, ETSI TR 125 943 V5.1.0, 2002. [9] Harry L. Van Trees, “Optimum Array Processing, Part IV of Detection, Estimation, and Modulation Theory,” John Wiley & Sons, 2002. [10] J. J. Shynk, “Frequency-domain and multirate adaptive filtering,” Signal Processing Magazine, IEEE Volume 9, Issue 1, pp. 14-37, 1992. [11] Hiroshi Harada, and Ramjee Prasad, “Simulation and Software Radio for Mobile Communications,” Artech House, 2002. [12] R. O. Schmidt, “Multiple Emitter Location and Signal Parameter Estimation,” IEEE Transactions on Antennas and Propagation, Vol. AP-34, No. 3, pp. 276-80, Mar. 1986. [13] S. U. Pillai, and B. H. Kwon, “Forward / Backward Spatial Smoothing Techniques for Coherent Signal Identification, ” IEEE Transactions on ASSP, Vol. 37, No. 1, pp. 8-15, Jan. 1989. [14] T. J. Shan, M. Wax, and T. Kailath, “On spatial smoothing for direction-of- arrival estimation of coherent signals,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-33, no. 4, pp. 806-811, Aug. 1985. [15] Keh-Chiarng Huarng, and Chien-Chung Yeh, “A unitary transformation method for angle-of-arrival estimation Signal Processing,” IEEE Transactions on Volume 39, Issue 4, pp. 975-977, 1991. [16] K. Minseok, K. Ichige, and H. Arai, “Implementation of FPGA based fast DOA estimator using unitary MUSIC algorithm,” Vehicular Technology Conference, pp. 213-217 Vol.1, 2003. [17] M. Pesavento, A. B. Gershman, and M. Haardt, “Unitary root-MUSIC with a real-valued eigendecomposition : a theoretical and experimental performance study,” IEEE Transactions on Signal Processing, Volume 48, Issue 5, pp. 1306-1314, 2002. [18] R. Roy, A. Paulraj and T. Kailath, “Direction-of-arrival estimation by subspace rotation method - ESPRIT,” IEEE Proc. ICASSP, pp. 2495-2498, 1986. [19] R. Roy and T. Kailath, “ESPRIT- Estimation of Signal Parameters via Rotational Invariance Techniques,” IEEE Transactions on Acoustics, speech, and Signal Processing, Vol. ASSP-37, pp. 984-995, July 1989. [20] M. Haardt, and J. A. Nossek, “Unitary ESPRIT : how to obtain increased estimation accuracy with a reduced computational burden,” Signal Processing, IEEE Transactions on Volume 43, Issue 5, pp. 1232-1242, 1995. [21] M. Haardt, M. E. Ali-Hackl, “Unitary ESPRIT: how to exploit additional information inherent in the relational invariance structure,” IEEE International Conference on Acoustics, Speech, and Signal Processing, Volume iv, pp. IV/229 - IV/232, 1994. [22] A. T. Denidni, and G. Y. Delisle, “An adaptive array for multipath effect reduction,”Antennas and Propagation Society International Symposium, pp. 1003-1006 vol.2, 1992. [23] Kaizhi Huang, Jing Wang, Guoan Chen, and Youzheng Wang, “Smart antenna and spatial diversity-combining,” VTC Spring 2002 IEEE 55th Volume 1, pp. 340-344, 2002. [24] Y. Ogawa, Y. Tanabe, T. Nishimura, and T. Ohgane, “Basestation adaptive antennas for a high-speed FDD / TDMA system,” ICC 2001 IEEE International Conference on Volume 8, pp. 2558-2562, 2001. [25] Kaizhi Huang, Jing Wang, Guoan Chen, and Youzheng Wang, “Smart antenna and spatial diversity-combining,” Vehicular Technology Conference, IEEE 55th Volume 1, pp. 340-344, May 2002. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/38618 | - |
| dc.description.abstract | 高速鐵路系統近年來由於高速度、高乘載以及安全性高等因素，未來可期望成為主要的大眾運輸交通工具。而可適性波束成型(Adaptive beamforming)技術有擴充系統容量及消除干擾信號等優點，勢必會成為通訊系統中重要的一環，因此探討可適性波束成型系統在高速鐵路環境下所面臨到的問題以及解決方法是一個非常重要的課題。首先假設高速鐵路系統已知信號來源方向(DOA)，利用此已知信號方向我們先架構運用QR-RLS演算法的可適性波束成型器，套用在高速鐵路環境中由模擬結果可知波束在干擾信號方向會有零陷點的偏移以及凹陷程度不夠等問題，因此我們建構了時域寬頻可適性波束成型器以及頻域寬頻可適性波束成型器來補償上述波束方面的問題。最後為了高速鐵路通訊系統的強健性及完備性，我們做了信號方位估測，估測信號來的方向以形成波束消除干擾信號，運用MUSIC演算法做高解析度的信號估測以及ESPRIT演算法來降低估測的計算複雜度以及記憶體儲存空間，同時運用Forward / Backward Spatial Smoothing以及Unitary Transform等方法來降低信號間的同調(Coherent)效應，以增加信號方位估測的準確度以及估測振幅響應。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2021-06-13T16:39:23Z (GMT). No. of bitstreams: 1 ntu-94-R92942039-1.pdf: 1519574 bytes, checksum: 91e6ecaadc5bbc362247e9d9b07ec5cd (MD5) Previous issue date: 2005 | en |
| dc.description.tableofcontents | 第一章 緒論........................................................1
1.1 智慧型天線系統簡介........................................................1 1.1.1 智慧型天線系統優點........................................................2 1.1.2 智慧型天線系統分類........................................................7 1.2 高速鐵路的無線通訊系統架構描述........................................................8 1.2.1 高速鐵路的場景描述........................................................8 1.2.2 高速鐵路的無線通訊系統架構........................................................9 1.2.3 高速鐵路的無線通訊系統探討.......................................................11 1.2.4 台灣高速鐵路現況.......................................................14 1.3 論文架構.......................................................14 第二章 可適性波束成型在高速鐵路環境下的表現.......................................................17 2.1 研究動機.......................................................17 2.2 天線陣列基本架構及數學模型.......................................................18 2.2.1 MVDR波束成型器的數學架構.......................................................20 2.2.2 MVDR波束成型器運用QR-RLS演算法.......................................................23 2.3 多重路徑衰減通道的架構及數學模型.......................................................25 2.3.1 都普勒效應及信號衰減分布.......................................................28 2.3.2 多重路徑衰減傳輸環境的數學模型.......................................................31 2.3.3 COST 259通道模型.......................................................33 2.4可適性波束成型在高速鐵路環境下的模擬實驗及討論.......................................................35 2.4.1 都普勒效應對可適性波束成型的影響之分析.......................................................35 2.4.2 可適性波束成型在高速鐵路環境下的表現.......................................................39 2.5 結論.......................................................44 第三章 寬頻可適性波束成型在高速鐵路環境下的表現.......................................................46 3.1 研究動機.......................................................46 3.2 時域寬頻可適性波束成型.......................................................47 3.2.1 運用LMS演算法的時域寬頻可適性波束成型器.......................................................49 3.2.2 運用QR-RLS演算法的時域寬頻可適性波束成型器.......................................................54 3.3 頻域寬頻可適性波束成型.......................................................58 3.3.1 運用Block LMS演算法的頻域寬頻可適性波束成型器.......................................................60 3.3.2 運用DCT-LMS演算法的頻域寬頻可適性波束成型器.......................................................63 3.4 結論.......................................................67 第四章 在高速鐵路環境中的方位估測技術.......................................................68 4.1 研究動機.......................................................68 4.2 運用MUSIC演算法估測信號方位.......................................................70 4.2.1 MUSIC加上前後向空間平滑演算法.......................................................74 4.2.2 Unitary MUSIC演算法.......................................................79 4.3 運用ESPRIT演算法估測信號方位.......................................................82 4.3.1 ESPRIT加上前後向空間平滑演算法.......................................................86 4.3.2 Unitary ESPRIT演算法.......................................................88 4.4 結論.......................................................89 第五章 總結與未來展望.......................................................91 5.1 總結.......................................................91 5.2 未來展望.......................................................92 參考文獻.......................................................95 | |
| dc.language.iso | zh-TW | |
| dc.title | 在高速鐵路環境下可適性波束成型技術之研究 | zh_TW |
| dc.title | A study on Adaptive Beamforming Techniques in High-Speed Train Environment | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 93-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 洪志偉,魏學文 | |
| dc.subject.keyword | 高速鐵路,可適性波束成型, | zh_TW |
| dc.subject.keyword | High-Speed Train,Adaptive Beamforming, | en |
| dc.relation.page | 98 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2005-07-05 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
| 顯示於系所單位： | 電信工程學研究所 | |
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|---|---|---|---|
| ntu-94-1.pdf 目前未授權公開取用 | 1.48 MB | Adobe PDF |
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