在新的通訊技術不斷的開發與研究下，也開啟新的WCDMA基站的問世。新一代的基站具有體積小，強大功率效能，更低耗能消耗，系統可靠性提升，成本下降等能力。如此，基站的使用的容量將提升一倍增加。縱然使用容量獲得提升，但是網絡的部署建設，若是選擇不適合的基站位址，則信號覆蓋率偏低；或是基站設立數量過多，則造成成本浪費，原本的改善方案將因此徒勞無功。本論文正是由此出發，針對WCDMA基站選址優化這問題進行研究。 使用優化的工具眾多，可是如何挑選適合的工具？一般在建設WCDMA基站時，是無法得知何處是最佳的基站位置。在研究過程中，發現粒子群演算法(PSO)具有相當優異的特性。 在實驗研究過程中，發現使用粒子群演算法(PSO)加上Weight(權重) ，可以讓每代的粒子容易獲得較沒有加上Weight(權重)的PSO獲得更佳解。本論文實驗中，新增了 ｢外部擴散法｣與｢內部碰撞法｣，經實驗後，確實也快速改善訊號重疊局部優化的問題。 最後提出，對於建設基站的工程師所評估後，所假設的基站位置，也可經｢指定基站位置｣來驗證覆蓋率，並且透過粒子群演算法(PSO)尋得最佳覆蓋率的基站位置，以進行後期改善工程。 關鍵字：WCDMA，PSO，P_BEST，G_BEST，Weigh，基站位置，覆蓋率，權重，外部擴散法，內部碰撞法，指定基站位置，粒子群優化演算法。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.
