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Student Number 955303006
Author Wei-ting Shen(沈威廷)
Author's Email Address No Public.
Statistics This thesis had been viewed 538 times. Download 280 times.
Department Executive Master of Communication Engineering
Year 2011
Semester 1
Degree Ph.D.
Type of Document Doctoral Dissertation
Language zh-TW.Big5 Chinese
Title Improved Particle Swarm Optimization Algorithm Applied to the Base Station Placement Planning of WCDMA Network
Date of Defense 2012-01-09
Page Count 48
Keyword
  • 內部碰撞法
  • 基站位置
  • 外部擴散法
  • 指定基站位置
  • 權重
  • 粒子群優化演算法
  • 覆蓋率
  • Abstract In a new generation of WCDMA base stations is smaller, powerful in performance. So, In spite of many construction of base stations, the locations of the base station may not be adequate. That’s why the signal coverage is low. Excessive number of base stations means much money is to be wasted. This thesis is about optimization for WCDMA base station location.
    How to choose a suitable tool for optimization to be used ? Generally in the construction of WCDMA base stations, it may not be easy to know where the best base station location is. But in our research we found that particle swarm algorithm (PSO) is an excellent algorithm. This thesis proposes a new external diffusion and internal collision method. Our results showed indeed that it improved the signal overlapping problem of local optimization.
    Finally, the construction of base stations should be evaluated by considering the base station location. And by the designated base station location should verify the coverage obtained by using the particle swarm algorithm (PSO) algorithm.
    Keywords: WCDMA, particle swarm algorithm (PSO), weigh, base station location, coverage, external diffusion, internal collision, designated the base station location.
    Table of Content 摘  要i
    Abstractii
    誌  謝iii
    目  錄iv
    圖 目 錄 List of Figuresv
    表 目 錄 List of Tablesvi
    第一章 緒 論1
    1-1 研究背景與動機1
    1-2 研究的方向與內容2
    1-3論文架構4
    第二章 WCDMA網絡與基站選址規劃5
    2-1 概述5
    2-2 基站選址規劃5
    2-3 網絡覆蓋和容量分析7
    第三章 群體智能粒子群優化演算法9
    3-1 群體智能簡述9
    3-2 常用近代優化演算法及研究進展9
    3-3 粒子群優化演算法的原理概述11
    3-4 粒子群優化演算法的數學簡述12
    第四章 改良式粒子群優化演算法17
    4-1 慣性權重粒子群優化演算法17
    4-2 外部擴散粒子群優化演算法23
    4-3 內部碰撞粒子群優化演算法26
    4-4 『指定座標』粒子群演算法31
    第五章 進行程式模擬實驗驗證33
    5-1 問題定義與參數設定34
    5-2 隨機選取產生的初始解35
    5-3 定義適應值(Fitness value)函數36
    5-4 進行V向量的更新39
    5-5 檢查是否達到停止條件39
    5-6 參數選擇與實測結果40
    5-7 指定座標模擬40
    5-8改良式粒子群優化演算法實測結果41
    第六章 結論……………………………………………………………………………46
    參 考 文 獻……………………………………………………………………………47
    Reference [1]  吳秋玲 ,遺傳算法及其在CDMA基站優化選址中的應用,河海大學碩士學位論文, pp. 40-50, 2006年3月1日。
    [2]  蔡裕仁 ,粒子群優化演算法應用於企業更新數據網路採購之優化,國立中央大學通訊工程學系碩士論文, pp. 4-14 , 2011年7月15日 。
    [3]  朱源 ,新型高精度PSO算法及其應用,華南理工大學碩士學位論文,2008年11月25日。
    [4]  丁遠 ,CDMA網絡基站的參數規劃和優化,廣東大學碩士學位論文,2009年5月25日。
    [5]  唐輝 ,WCDMA網絡覆蓋預測分析與應用,南京郵電大學碩士學位論文,2004年5月
    1日。
    [6]  李銘 ,基于WCDMA下基站優化選址的研究,廣東工業大學碩士學位論文,2009年5月
    1日。
    [7]  康雪姣 ,CDMA無線網絡規劃與設計,蘭州大學碩士學位論文, 2009年6月1日。
    [8]  范思源 ,無線網絡规劃中基站選址的解决方案華南理工大學碩士學位論文,2006年
    11月27日。
    [9]  陳聖彦 , 基于改進PSO算法的動態神經網絡研究, 江南大學碩士學位論文,2009年
    5月1日。
    [10]Antonio I. S. Nascimento, Carmelo J. A. Bastos Filho, "A Particle Swarm Optimization based approach for the maximum coverage problem in cellular base stations positioning", Hybrid Intelligent Systems (HIS), 10th , pp. 91-96,23-25 Aug.2010..
    [11]M. A. S. Choudhry, M. Zubair, and I. M. Qureshi, "MUD for WCDMA using modified PSO algorithm", Wireless Communications and Signal Processing (WCSP) ", pp. 1-4, 21-23 Oct,2010.
    [12]M. A. S. Chaudhry, M. Zubair, and I. M. Qureshi,"Particle swarm optimization based MUD for overloaded MC-CDMA system", Wireless Communications, Networking and Information Security (WCNIS), pp. 1-5,25-27 June 2010.
    [13]A. A. El-Saleh, M. Ismail, R. Viknesh, C. C. Mark, and M. L. Chan, "Particle swarm optimization for mobile network design", IEICE Electronics Express, vol. 6, pp. 1219-1225, 17 August 2009.
    [14]D. Tsilimantos, D. Kaklamani, and G. Tsoulos, "Particle swarm optimization for UMTS WCDMA network planning", Wireless Pervasive Computing, ISWPC, pp. 283-287, 7-9 May 2008.
    [15]W. T. Li, X. W. Shi, L. Xu, and Y. Q. Hei, "Improved GA and PSO culled hybrid algorithm for antenna array pattern synthesis", Progress in Electromagnetics Research, vol. 80, pp. 461-476,2008.
    [16]T. P. Hong and G. N. Shiu (2007), "Allocating multiple base stations under general power consumption by the particle swarm optimization",Swarm Intelligence Symposium, pp. 23-28,1-5 April 2007.
    [17]H. M. Elkamchouchi, H. M. Elragal, and M. A. Makar, "Power control in CDMA system using particle swarm optimization", Radio Science Conference, pp, 1-8, 13-15 March 2007.
    [18]T. M. Chan, S. Kwong, and K. F. Man, "Resource management in wideband CDMA systems using gnetic algorithms", Applied Artificial Intelligence, vol. 19, pp. 1-41,23 Feb 2007.
    [19]Y. Zhang, C. Ji, P. Yuan, M. Li, C. Wang, and G. Wang, "Particle swarm optimization for base station placement in mobile communication",Networking, Sensing and Control, pp. 428-432,21-23 March 2004.
    Advisor
  • Chia-lu Ho(賀嘉律)
  • Files
  • 955303006.pdf
  • approve immediately
    Date of Submission 2012-01-17

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