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研究生:林昌均
研究生(外文):Chang-Chun Lin
論文名稱:室內環境無線接取佈建軟體之開發
論文名稱(外文):Software Development of Wireless Access Planning for Indoor Environment
指導教授:林信標林信標引用關係
口試委員:柯正義鄭獻勳丘建青林丁丙
口試日期:2007-06-18
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:電腦與通訊研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:中文
論文頁數:65
中文關鍵詞:基因演算法線性迴歸分析無線接取點
外文關鍵詞:Genetic AlgorithmsLinear Regression AnalysisAccess Point
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無線通迅網路在近年來之應用範圍已逐漸普及,而室內環境之相關應用也逐漸被重視,特別是人口密集度高的商業大樓裡,在成本及效率的考量下,如何於室內環境規劃網路已是一個重要之議題。在本論文中,吾人以實驗室已開發之軟體平台,延續發展其它相關應用,包括以實測資料為基礎之傳播模型模擬、室內無線網路接取點佈建及蜂巢式行動通信系統(Global System for Mobile, GSM)系統室內纜線配置機制,使其形成室內網路整合平台。
由於電波傳播模型於無線網路中扮演極為重要之角色,其準確度是設計者所關切之問題,吾人先利用基因演算法(Genetic Algorithms, GA)得到發射端位置,並將發射端擺放於實際環境中量測,使用線性迴歸分析法找出模型路徑損失及相關參數之關係,並透過實測資料來驗證於此迴歸模型下模擬之場強值是否與實測吻合。再利用GA搭配迴歸模型或內定傳播模型來完成無線區域網路(Wireless Area Network, WLAN) 之優化,其中,考慮的參數包括無線擷取點(Access Point, AP)數量、涵蓋率及訊號強度等。而亦可利用GA來達成無線感測網路(Wireless Sensor Network, WSN)之優化,其參數考慮多了感測器(Sensor Node)連結度。
要於大樓高樓層維持GSM網路之信號強度,其方法為佈建室內天線於各樓層中,並透過功分器、管道間及室外基站形成小型網路。傳統佈建方式為網路設計者依靠其經驗或直覺來決定天線位置,往往造成某些角落或區域信號強度不足之現象,因此,本軟體提供設計者繪製大樓平面圖,搭配接取點及電波傳播模型來模擬訊號強度,得知樓層平面之場強分佈情況,最後,透過各種統計分析,清楚地得知無線網路資訊。而天線之有效幅射功率(Effective Radiated Power, ERP)是由室外基站扣除纜線及功分器損失所得,因此,本軟體提供設計者手動繪製室內纜線、管道間及功分器或自動配線功能,透過軟體模擬室內天線之ERP值,使得配線更為簡單及省時。
The application of wireless communication networks has already been popularized in recent years. The relevant application in indoor environment has been noticed gradually, especially in business building of high population density. How to deploy the network which considered the cost and efficiency has become an important issue in indoor environment. In this thesis, I use platform built by lab to develop other relevant applications, including simulation of propagation models based on measurement data, the deployment of wireless access point in indoor environment, the design rules of indoor cable of GSM system. The integrated platform of network in indoor environment is formed.
Because the wave propagation model is an important role in wireless network, the degree of accuracy is concerned by designer. Genetic algorithm was used to evaluate the location of AP and set it in practical environment, then the signal strength was measured in this environment. Using linear regression analysis rules to find relationship between path loss and parameters. The measurement data was used to verify the simulated signal strength by using regression model is the same. Then using genetic algorithms rules complete optimal wireless area network with regression propagation model or default propagation model. The considerable parameters include the number of AP、the percentage of coverage and signals strength etc.. The software also can use GA rules to complete optimal wireless sensor network which consider parameter include the copulation of sensor node more.
In order to maintain the signal strength of GSM system in high-story building. The way is to deploy the distributing antennas in different floor-story and form a small network by splitters、pipelines and outdoor base station. Traditionally, system designer usually determine the deployment of the antennas by their experience or intuition but causes weak at signal strength in some corner of region. Therefore, the software can use the placement of antennas and propagation models to simulate signal strength based on the layout of the building. Finally, the variety of statistical analysis were use to know the information of wireless network clearly. Cable loss and splitter loss from outdoor base station affect the ERP value of antennas, therefore, the software provide users to draw indoor cable、pipeline and splitter or to deploy cable line automatically. It can reduce complexity and time which use software platform to simulate the ERP of indoor antennas.
中文摘要 i
英文摘要 iii
誌謝 v
目錄 vi
圖目錄 vii
表目錄 xi
第一章 緒論 1
1.1. 前言 1
1.2. 研究動機與目的 2
1.3. 論文架構 3
第二章 室內無線接取點佈建軟體平台介紹. 4
2.1. 主要視窗介面 4
2.2. 編輯選單 5
2.3. 繪圖選單 5
2.4. 地圖選單 6
2.5. 模擬選單 8
2.6. 高頻元件及其它元件 12
2.7. 資料庫選單 14
2.8. 詢問選單 15
第三章 以實測資料為基礎之室內傳播模型. 20
3.1. 室內傳播模型 20
3.2. 線性迴歸分析法 20
3.3. 實測資料分析 21
3.3.1. 迴歸方程式 22
3.3.2. 以實測資料為基礎之室內傳播模型 23
3.3.3. 以實測資料為基礎之室內傳播模型驗證 26
第四章 室內無線網路優化佈建. 32
4.1. 無線網路場強模擬 32
4.2. 基因演算法之介紹 35
4.3. 使用基因演算法之室內無線網路配置 38
4.3.1. 無線區域網路系統優化配置 39
4.3.2. 無線感測網路優化配置 43
第五章 GSM系統室內配線之優化. 45
5.1. 有效幅射功率 45
5.2. 室內配線之優化 50
第六章 結論 62
參考文獻 64
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