系統識別號 | U0002-2906201012125200 |
---|---|
DOI | 10.6846/TKU.2010.01077 |
論文名稱(中文) | 應用最佳化法則降低都會區無線通訊傳輸信號之信號衰減 |
論文名稱(英文) | Path Loss Reduction in An Urban Area by Applying Optimization Method |
第三語言論文名稱 | |
校院名稱 | 淡江大學 |
系所名稱(中文) | 電機工程學系碩士班 |
系所名稱(英文) | Department of Electrical and Computer Engineering |
外國學位學校名稱 | |
外國學位學院名稱 | |
外國學位研究所名稱 | |
學年度 | 98 |
學期 | 2 |
出版年 | 99 |
研究生(中文) | 張家偉 |
研究生(英文) | Chai –Wei Chang |
學號 | 697440914 |
學位類別 | 碩士 |
語言別 | 繁體中文 |
第二語言別 | |
口試日期 | 2010-06-07 |
論文頁數 | 83頁 |
口試委員 |
指導教授
-
丘建青
委員 - 方文賢 委員 - 林丁丙 委員 - 陳建宏 委員 - 李慶烈 |
關鍵字(中) |
戶外無線通訊 訊號衰減 基因演算法 群聚粒子演算法 動態差異演算法 |
關鍵字(英) |
SBR/Image-method outdoor environments antenna patterns path loss genetic algorithm particle swarm optimization algorithm dynamic differential evolution algorithm. |
第三語言關鍵字 | |
學科別分類 | |
中文摘要 |
在本論文中所呈現的是戶外無線通訊系統的通道特性分析。然而在戶外的環境中,有許多阻擋物會干擾和減弱接收訊號的功率,例如車輛樹木和建築物。所以我們的目的是要分析與了解戶外無線通訊系統的通道特性。 我們考慮了三種不同的天線形式來評估戶外環境中的路徑損失。而且藉由使用遺傳基因演算法,群聚粒子演算法,動態差異演算法三種演算法,來改善陣列天線的天線場型使得無線通訊訊號傳輸具有良好的指向性並減少環境的多路徑干擾產生的路徑損失。 在本文中,吾人利用遺傳基因演算法,群聚粒子演算法與動態差異演算法來把具有指向性的天線陣列加入戶外環境裡,用射線彈跳-影像法(SRB-image method)來模擬傳播通道,進而分別分析三種演算法如何改良天線場型,使得所需區域的路徑損失(Path Loss)下降更多,並減少基地台上的功率浪費,並比較三種演算法在不同形狀的天線陣列中的各項優缺點。 第二章是模擬戶外環境的描述及建立,如射線彈跳-影像法技術(SBR-image method )、路徑損失(Path Loss)的觀念等等。第三章描述天線陣列的觀念,如分集技術、天線陣列技術、天線陣列模擬操作等等。第四章中,介紹遺傳基因演算法則、群聚粒子演算法則以及動態差異演算法則三種不同演算法的設定與特性,第五章則是描述以上三種演算法則來產生天線陣列場型所減少環境中多路徑干擾造成的接收點收到訊號之路徑損失,最後第六章則比較上述三種演算法產生天線場之結論。 |
英文摘要 |
In this paper, we use the SBR/Image method to compute the path loss for different outdoor environments in the commercial area of Taipei. Three types of antenna arrays such as L shape, Y shape, and circular shape arrays are used in the base station and their corresponding path loss on several routes in the outdoor environment are calculated. Moreover, three algorithms are employed to optimize the excitation voltages and phases for antenna arrays to form proper antenna patterns. The performance in reduction of path loss by the optimization algorithm is investigated for these antenna arrays. The particle swarm optimization algorithm and dynamic differential evolution algorithm have more advantages than genetic algorithm. By the obtained antenna patterns, we can know the route with the lowest path loss; meanwhile, transmission power using this route in the base station can be reduced. The dynamic differential evolution algorithm has better optimization result than genetic algorithm in LOS case. But the particle swarm optimization has better optimization result in NLOS case. The investigated results can help communication engineers improve their planning and design of outdoor communication system. |
第三語言摘要 | |
論文目次 |
中文摘要.....................................................I 英文摘要 ....................................................II 第一章 概論 1 第二章環境建構與通道模型 6 2.1 無線電波傳播的通道分析 6 2.2 無線電波傳播的多重路徑與信號衰減 7 2.3 射線彈跳-追蹤法 10 第三章 天線工程理論與演算法法則....................... 14 3.1天線陣列技術........................................14 3.2分集技術............................................22 第四章改良式基因法則、動態差異型演化法與改良式粒子群聚法.....29 4.1基因演算法則........................................29 4.2 粒子群聚最佳化法...................................37 4.3差異型演化法........................................41 4.4動態差異型演化法....................................43 第五章 天線與環境的模擬與分析..........................54 5.1模擬環境與相關參數設定簡介..........................54 5.2 天線陣列形狀的模擬.................................54 5.3 戶外環境的模擬 .....................................61 5.4模擬環境與天線陣列的分析(LOS).......................63 5.4.1 GA-LOS...........................................64 5.4.2 PSO-LOS..........................................66 5.4.3 DDE-LOS..........................................69 5.5模擬環境與天線陣列的分析(NLOS)......................70 5.5.1 GA-NLOS..........................................72 5.5.2 PSO-NLOS.........................................74 5.5.3 DDE-NLOS.........................................76 第六章 結論............................................79 參考文獻...............................................81 圖2-1傳播模型的簡單幾何學.................................................13 圖2-2 二維射線圖..........................................................14 圖2-3 二進位反射/穿透樹狀圖...............................................15 圖3-1 均勻線性陣列天線之幾何排列架構與相對的激發相位......................25 圖3-1a 線性陣列場型(X-Y平面).............................................26 圖3-1b 線性陣列場型(Y-Z平面).............................................26 圖3-5 天線的極化分極......................................................27 圖3-6 天線的角度分集......................................................28 圖4-1 基因法則流程圖......................................................32 圖4-2 ?子群聚法流程圖....................................................38 圖4-3 粒子群聚法中於二維目標函數等位線圖..................................39 圖4-4 二維問題中,三種不同邊界條件示意圖..................................42 圖4-5 差異型演化法流程圖..................................................44 圖4-6 差異型進化法中突變方法一的示意圖....................................46 圖4-7 差異型進化法中突變方法二的示意圖....................................47 圖4-8 差異型進化法中突變方法三的示意圖....................................47 圖4-9 差異型進化法中交配向量結構示意圖....................................50 圖4-10 差異型進化法中的交配向量於一個二維目標函數等位線圖描述的示意圖.....50 圖4-11 動態差異型型演化策略法流程圖.......................................53 圖5-1 圓型陣列天線空間幾何排列............................................56 圖5-2 圓型天線陣列場型(X-Y平面)..........................................56 圖5-3 圓型天線陣列場型(Y-Z平面)..........................................57 圖5-4 L型陣列天線空間幾何排列.............................................57 圖5-5 L型天線陣列場型(X-Y平面)...........................................58 圖5-6 L型天線陣列場型(Y-Z平面)...........................................58 圖5-7 Y型陣列天線空間幾何排列.............................................59 圖5-8 Y型天線陣列場型(X-Y平面)...........................................59 圖5-9 Y型天線陣列場型(Y-Z平面)..........................60 圖5-10 多重街道圖...................................62 圖5-11 三種演算法與未加演算法比較圖(LOS) ..............63 圖5-12 遺傳基因演算法應用於L型天線陣列輻射場...............64 圖5-13 遺傳基因演算法應用於Y型天線陣列輻射場...............64 圖5-14 遺傳基因演算法應用於circular型天線陣列輻射場.......65 圖5-15群聚粒子演算法應用於L型天線陣列輻射場.............66 圖5-16群聚粒子演算法應用於Y型天線陣列輻射場............66 圖5-17 群聚粒子演算法應用於circular型天線陣列輻射場....67 圖5-18動態差異演算法應用於L型天線陣列輻射場............68 圖5-19動態差異演算法應用於Y型天線陣列輻射場............68 圖5-20動態差異演算法應用於circular型天線陣列輻射場.....69 圖5-21 三種演算法與未加演算法比較圖(NLOS)......................71 圖5-22 遺傳基因演算法應用於L型天線陣列輻射場......72 圖5-23 遺傳基因演算法應用於Y型天線陣列輻射場.......72 圖5-24 遺傳基因演算法應用於circular型天線陣列輻射場....73 圖5-25 群聚粒子演算法應用於L型天線陣列輻射場............74 圖5-26 群聚粒子演算法應用於Y型天線陣列輻射場.............74 圖5-27 群聚粒子演算法應用於circular型天線陣列輻射場......75 圖5-28 動態差異演算法應用於L型天線陣列輻射場..............76 圖5-29 動態差異演算法應用於Y型天線陣列輻射場.............76 圖5-30 動態差異演算法應用於circular型天線陣列輻射場......77 圖5-31演算法應用於天線陣列以降低傳輸之訊號衰減..........78 |
參考文獻 |
[1] Paier, Alexander; Zemen, Thomas; Bernado, Laura. “Non-WSSUS vehicular channel characterization in highway and urban scenarios at 5.2GHz using the local scattering function”, Smart Antennas, 2008. WSA 2008. International ITG Workshop on. Publication Year: 2008 , Page(s): 9 - 15 [2] TGa modelling group, Andreas F. Molisch (Chiarman) “IEEE 802.15.4a channel model-final report ”, IEEE 802.15 wireless personal area network, 15 Sept. 2004. [3] Theodore S.Rappaport, Wireless Communications: NJ, Principles and Practice, Prentice Hall, 1996. [4] Ling Cen; Zhu Liang Yu; Ser, W.;“Antenna array synthesis in presence of mutual coupling effect for low cost implementation “Integrated Circuits, ISIC '09. Proceedings of the 2009 12th International Symposium on. Publication Year: 2009 , Page(s): 360 - 363 [5] Polpasee, M.; Homsup, N.; Virunha, P. “Optimize Directivity Pattern for Arrays by Using Genetic Algorithms Based on Planar Fractal Arrays” Communications and Information Technologies, 2006. ISCIT '06. International Symposium on. Publication Year: 2006 , Page(s): 28 – 31 [6] Ting-Chieh Tu and Chieh-Ching Chiu. “Path Loss Reduction in an Urban Area by Genetic Algorithms” [7] Chi-Hsien Sun. Chien-Ching Chiu. Wei Chien. and Hua-Pin Chen “Characteristic Studies of Time Domain Scattering for 2-D Homogeneous Dielectric Cylinder by Applying Optimization Methods” [8] ” IEEE, Antenna and Propagation Magazine, Vol. 42, NO. 3, June 2000, pp.12 – 20. [9] A. Carlisle and G. Dozier, “An off-the-shelf PSO,” Proc. of the Workshop on Particle Swarm Optimization, Indianapolis, April 2001. T. Huang and A. S. Mohan, “A hybrid boundary condition for robust particle swarm optimization,” IEEE Antennas and Wireless Propagation Letters, vol. 4, pp. 112-117, 2005. [10] Elliott, R. S. Antenna theory and design, Prentice-Hall, 1981. A. Qing, “Dynamic differential evolution strategy and applications in electromagnetic inverse scattering problems,” IEEE Transactions on Geoscience and Remote Sensing, vol 44, issue 1, pp.116 - 125, Jan. 2006. [11] R. Nabar, H. Bölcskei, V. Erceg, D. Gesbert and A. Paulraj, “Performance of multi-antenna signaling strategies in the presence of polarization diversity” in IEEE Transactions on signal processing, vol.50, no.10, October 2002, pp. 2553-2562. [12] S. Y. Tan and H. S. Tan, “ A Theory for Propagation Path-Loss Characteristics in a City-Street Grid”, IEEE Transactions on Electromagnetic Compatibility, Vol. 37, No.3, Aug. 1995, pp.333-342. [13] Erricolo D. Uslenghi, P.L.E., “Propagation path loss-a comparison between ray-tracing approach and empirical models”, IEEE Transactions on Antennas and Propagation, Volume 50, Issue 5, May 2002, pp.766 – 768. [14] Sakawa, K., Masui, H., Ishii, M., Shimizu, H., Kobayashi, T., “Microwave path-loss characteristics in an urban area with base station antenna on top of a tall building”, 2002 International Zurich Seminar on Broadband Communications, Feb. 2002, pp.19-21. [15] Yonezawa, K., Maeyama, T., Iwai, H.; Harada, H., “Path loss measurement in 5 GHz macro cellular systems and consideration of extending existing path loss prediction methods”, Wireless Communications and Networking Conference, 2004. WCNC. 2004 IEEE Volume 1, March 2004 , pp.21-25 [16] G.. E. Corazza, V. Degli-Esposti, M. Frullone, G. Riva, “A Characterization of Indoor Space and Frequency Diversity by Ray-Tracing Modeling”, IEEE Journal on Selected Area in Communication, Vol. 14, NO.3, April 1996, pp.411-419. [17] Zhijun Zhang, Yun, Z., Iskander, M.F. ,“New computationally efficient 2.5D and 3D ray tracing algorithms for modeling propagation environments”, IEEE Antennas and Propagation Society International Symposium, Vol.1, July 2001, pp:460 – 463. [18] Tobin, M.L., Richie, J.E.,“A 2-D ray tracing model for the characterization of spatial and time-domain properties of the indoor propagation channel”, IEEE Antennas and Propagation Society International Symposium, Vol. 4, June 1995, pp:1948 – 1951 [19] Seong-Cheol Kim; Guarino, B.J., Jr, “Radio propagation measurements and prediction using three-dimensional ray tracing in urban environments at 908 MHz and 1.9 GHz”, IEEE Transactions on Vehicular Technology, Vol. 48, Issue 3, May 1999, pp:931 – 946. [20] Julio Cesar R. Dal Bello, Gla’ucio L. Siqeira, ”Theoretical Analysis and Measurement Results of Vegetation Effects on Path Loss for Mobile Cellular Communication Systems”, IEEE Transactions on Vehicular Technology, Vol. 49, No. 4, July 2000, pp. 1285 – 1293. [21] Saleh AAM, Valenzuela RA., “A statistical model for indoor multipath propagation”, IEEE Journal on Selected Areas in Communication, Vol. 5, 1987, pp.128 – 137. [22] S. C. Jan and S. K. Jeng, "A novel propagation modeling for microcellular communications in urban environments" in IEEE Transactions on Vehicular Technology., vol. 46, no. 4, 1997, pp. 1021-1026. [23] L.M. Correia, Wireless Flexible Personalised Communication. 605 Third Avenue, NY: John Wiley, 2001. [24] P.C.F. Eggers, I.Z. Kovács, and K. Olesen, “Penetration effects on XPD with GSM 1800 handset antennas, relevant for BS polarization diversity for indoor coverage” in IEEE VTC’98, Ottawa Ont. Canada, May 1998 |
論文全文使用權限 |
如有問題,歡迎洽詢!
圖書館數位資訊組 (02)2621-5656 轉 2487 或 來信