粒子群演算法基於考量人口密度之基地台佈建; Particle Swarm Optimization Algorithm Applied to Base Station Construction Based on Population Density

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Title:	粒子群演算法基於考量人口密度之基地台佈建;Particle Swarm Optimization Algorithm Applied to Base Station Construction Based on Population Density
Authors:	黃偉哲;Huang,Wei-che
Contributors:	通訊工程學系在職專班
Keywords:	PSO;粒子群演算法;人口密度;基地台佈建
Date:	2013-07-30
Issue Date:	2013-08-22 12:07:08 (UTC+8)
Publisher:	國立中央大學
Abstract:	行動通訊在短短的數年內，技術進步迅速，已經可讓人們達到行動上網，甚至是高畫質影音的網路速度。因此行動通訊的使用人口呈現大幅增加，造就了人手一機的情況。用戶量暴增，導致人口密度高的地區，容易造成網路塞車，連線不易。若再加上基地台的佈建位置不佳，訊號覆蓋率變差，或是基地台佈建數量過多，則會造成營運成本增加，本論文便是針對上述問題進行探討及研究。在研究過程中，發現粒子群演算法具備有算法簡單僅需較少的參數設定、容易實現最佳化、快速收斂的特性、搜尋速度快等優點，所以本篇論文是藉由粒子群最佳化演算法之特性，套用在行動通訊基地台的選址優化，並加以考量人口密度因素，以獲得最佳的覆蓋率，可作為電信營運商於規劃基地台位置時的參考依據。 Mobile communication has great progress in just a few years. People can access the internet by mobile and the speed of internet can support high-definition video. Therefore, the user of mobile communication have Increased significantly. Surge of users, it will cause network congestion in areas of high population density, and then the connection is not easy. When the location of base station disposes at bad locations, the signal coverage is poor. Or an excessive number of base station constructions will result in increases in operating costs. This thesis will study in accordance with the above issues. In my research, I found the particle swarm algorithm have the advantages, such as simple algorithms, fewer parameter settings, easy to optimize, fast convergence and fast search speed. So this thesis is applied for base station optimization, and considered population density factors to get the best coverage of base stations. This theory can be used in telecom operators in planning base station positions.
Appears in Collections:	[Executive Master of Communication Engineering] Electronic Thesis & Dissertation

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