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研究生: 紀丞懋
Chi, Cheng-Mao
論文名稱: 正交分頻多工點對點分散式通訊系統吞吐量最佳化研究
Study of throughput optimization for OFDM based D2D distributed communication system
指導教授: 郭文光
Kuo, Wen-Kuang
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 電腦與通信工程研究所
Institute of Computer & Communication Engineering
論文出版年: 2019
畢業學年度: 107
語文別: 中文
論文頁數: 44
中文關鍵詞: 拉格朗日乘數法梯度下降法非線性規劃最佳化
外文關鍵詞: Lagrange multiplier method, optimization, gradient descent, MINLP
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  • 近年來,手機平板的無線行動裝置與多媒體系統普及化下,對於網路的要求日益增加,使得無線通訊系統體資料傳輸量呈現爆炸成長,然而基地台數量卻沒有有效的成長,使得基地台承受更大負擔,因此Device to Device(D2D)通訊傳輸技術越來越受到討論,由於不須基地台轉送直接進行通訊技術,可有效增加總體傳輸量,並減輕基地台的負擔。本論文將探討分散式架構下的Ad-hoc D2D資料傳輸率的最佳化與分析,在SINR限制、功率上下限、單一資料傳輸率下限,主要使用的求解方式有Lagrange multiplier method(拉格朗日乘數法)以及梯度下降法(gradient descent)。

    In recently, with the popularity of wireless devices and multimedia systems for mobiles and tablets, the demand for networks is increasing, which has caused the data transmission of wireless communication systems to explode rapidly. However, the number of base stations has not been effectively grown, which makes base stations more burdened. Therefore, Device to Device (D2D) communication transmission technology is more and more discussed. Because of D2D communication, devices directly transfer with others without using the base staion, the overall transmission amount can be effectively increased, and the burden on the base station can be reduced. This paper will explore the optimization and analysis of Ad-hoc D2D data transmission rate based the distributed architecture. In the SINR limit, the limits of the upper and lower power, and the lower limit of single data transmission rate. Finally, the main solution is Lagrange multiplier method and gradient descent.

    摘要 I Abstract II 致謝 V 目錄 VI 表目錄 VIII 圖目錄 IX 第一章 緒論 1 1.1 研究動機 1 1.2 論文內容簡介 1 第二章 網路架構 2 2.1 第五代行動通訊技術 2 2.2 裝置間(D2D)通訊 6 2.3 OFDMA 12 2.4 數學模型 14 2.4.1 符號 14 2.4.2 決策目標 15 2.4.3 系統連線限制 15 2.4.4 功率限制 16 2.4.5 品質限制 16 2.4.6 混合整數非線性規劃模型 18 第三章 模型簡化 19 3.1 等價化簡 19 3.2 非凸函數轉凸函數 20 3.3 Relax Binary Variable 21 3.4 模型簡化總結 22 第四章 非線性規劃與求解過程解法 23 4.1 拉格朗日乘數法 23 4.2 梯度下降法 25 4.3 演算法設計 26 第五章 模擬結果 33 5.1 參數設定 33 5.2 數據呈現 34 第六章 結論 42 參考文獻 43

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