淡江大學機構典藏:Item 987654321/35781
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/35781


    Title: 利用基因法則最佳化室內天線位置之分析
    Other Titles: Optimal antenna location in indoor environment using genetic algorithm
    Authors: 陳彥甫;Chen, Yen-fu
    Contributors: 淡江大學電機工程學系碩士班
    丘建青;Chiu, Chien-ching
    Keywords: 超寬頻;基因法則;位元錯誤率;失效率;Ultra-wide band;Genetic Algorithm;Bit error rate;Outage probability
    Date: 2008
    Issue Date: 2010-01-11 07:08:45 (UTC+8)
    Abstract: 由於無線電波在室內環境中容易受到遮蔽物的影響，例如:牆壁、天花板以及傢俱等，造成無線電波經由多重反射、繞射等路徑而到達接收天線，此一現象稱之為多路徑效應(multi-path effect)。由於此效應造成的符際間干擾(InterSymbol Inference, ISI) ，導致通訊位元錯誤率(Bit Error Rate, BER)及失效率(outage probability)增加，亦即通話品質變差。射線彈跳追蹤法可以模擬複雜環境、預測無線通訊傳輸時的特性以及減少工作時間與成本。為了得知其脈衝響應(impulse responses)，本文利用射線彈跳追蹤法(Shooting and Bouncing Ray/image techniques, SBR/Image techniques)和快速反傅立葉轉換(Inverse Fast Fourier Transform, IFFT)技術計算其脈衝響應。使用二進制的脈波振幅調變(Binary Pulse Amplitude Modulation, BPAM)方法，進而計算超寬頻通訊系統的位元錯誤率。本篇論文裡，吾人分別針對四種狀況，並且利用基因法則最佳化室內的發射天線位置，之後探討其在超寬頻(Ultra-Wide Band, UWB) 通訊上對位元錯誤率的影響。
    這四種不同的狀況分別為: 1. 發射器在室內自由移動、每個接收器以0.3公尺間隔均勻分佈固定在桌上(例如:手機對電腦) 2. 發射器在桌上自由移動、每個接收器以0.3公尺間隔均勻分佈固定在桌上(例如:電腦對電腦) 3. 發射器在室內自由移動、每個接收器以0.75公尺間隔均勻分佈在室內環境(例如:手機對手機) 4. 發射器在桌上自由移動、每個接收器以0.75公尺間隔均勻分佈在室內環境(例如:電腦對手機) 。最後數值結果顯示使用基因法則最佳化室內的發射天線位置確實可以降低環境失效率。
    A novel optimization procedure for the location of the transmitter in ultra-wideband (UWB) wireless communication systems is presented. The impulse responses of different transceiver locations are computed by shooting and bouncing ray/image (SBR/Image) techniques and inverse fast Fourier transform (IFFT). By using the impulse responses of these multi-path channels, the bit error rate (BER) performance for binary pulse amplitude modulation (BPAM) impulse radio UWB communication system are calculated. Based on the BER performance, the outage probability for any given location of the transmitter can be computed. The optimal antenna location for minimizing the outage probability is searched by genetic algorithm (GA). There are four different transceiver locations considered in the simulation. These four cases are (i) the transmitter is mobile in the whole indoor environment and the receivers are located on the tables with intervals distribution (ii) the transmitter is mobile but only set on the tables and the receivers are located on the tables with uniform distribution (iii) the transmitter is mobile and the receivers are uniform intervals distribution in the whole indoor environment (iv) the transmitter is mobile but only set on the tables and the receivers are uniform distribution in the whole indoor environment. Numerical results have shown that our proposed method is effect to find the optimal location for transmitting antenna to reduce BER and outage probability.
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Thesis

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