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研究生: 蔡德生
Tsai, Te-Sheng
論文名稱: D2D通訊於LTE蜂巢式網路中使用粒子群最佳化演算法之位置推薦
Particle swarm optimization algorithm based location recommendation for D2D Underlying Cellular Networks
指導教授: 王嘉斌
Wang, Chia-Pin
學位類別: 碩士
Master
系所名稱: 電機工程學系
Department of Electrical Engineering
論文出版年: 2017
畢業學年度: 106
語文別: 中文
論文頁數: 65
中文關鍵詞: 設備與設備之通訊長期演進技術資源分配位置推薦干擾抑制
英文關鍵詞: Device-to-Device (D2D) communications, 3GPP Long Term Evolution (LTE), Resource Allocation, Location Recommendation, interference mitigation
DOI URL: https://doi.org/10.6345/NTNU202201888
論文種類: 學術論文
相關次數: 點閱:114下載:18
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  • 在此篇論文中,我們提出了D2D (Device-to-Device, D2D) 通訊於LTE蜂巢式網路中使用粒子群最佳化演算法之位置推薦。我們所提出的方法是讓D2D使用者移動到我們所推薦的位置以達到更好的系統容量以及資源利用率,利用我們設計的成本函數來決定我們的資源分配機制,避免與相鄰的大型蜂窩式網路基地台或其他的D2D用戶產生干擾並且平衡MUE (Marcocell User Equipment, MUE)用戶及D2D用戶的體驗品質(Quality of Experience, QoE),希望兩者都可以達到最佳的體驗效果。
    最後經由模擬結果證明,粒子群演算法不同的迭代結果與傳統暴力法的位置推薦方法比較之後,我們的方法可以有效的降低位置推薦所產生的推薦成本及時間。

    In this paper, we present a Particle swarm optimization algorithm based location recommendation for Device-to-Device (D2D) Underlying Cellular Networks. The proposed scheme enables D2D users to transmit to the best position we recommended for better system capacity and resource reuse utilization ratio. Moreover, with our cost function to decide how to distribute resource, the interference between neighboring Cellular Networks base station and D2D users could be avoided. Also, it can balance Quality of Experience(QoE) between MUE (Marcocell User Equipment, MUE) users and D2D users, hoping for the best user experience on both side. As simulation results shows, PSO LR scheme with different iterations effectively reduce both the cost and time of location recommendation in comparison with brute-force LR scheme.

    中文摘要 i 英文摘要 ii 誌謝 iii 目錄 iv 圖目錄 vi 表目錄 viii 第一章  緒論 1 1.1 研究動機與背景 1 1.2 研究目的 4 1.3 其他相關研究 6 1.4 論文架構 7 第二章  相關知識介紹 8 2.1 LTE長期演進技術無線網路系統概述 8 2.2 IoT介紹 15 2.3 IoT之D2D應用 16 第三章  本論文提出之演算法 18 3.1 研究作法之動機 18 3.1.1 網路模型之建立 19 3.2 基於粒子群最佳化之位置推薦方法設計 23 3.2.1 粒子族群最佳化演算法 24 3.2.2 基於粒子群最佳化之位置推薦方法 25 第四章  數值分析與模擬結果 32 4.1 模擬環境與參數設定 32 4.2 模擬結果與討論 33 第五章  結論 62 參考文獻 64

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