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研究生： 張祐嘉
Chang, You-Jia
論文名稱： 在5G網路中，利用模糊理論實現可適應環境之換手演算法
Environment-Sensitive Handover Algorithm Using Fuzzy Logic in 5G Networks
指導教授： 蔡明哲
Tsai, Ming-Jer
口試委員: 郭桐惟
Kuo, Tung-Wei
郭建志
Kuo, Jian-Jhih
學位類別： 碩士
Master
系所名稱： 電機資訊學院 - 資訊工程學系
Computer Science
論文出版年： 2020
畢業學年度： 108
語文別： 英文
論文頁數： 49
中文關鍵詞： 第五代行動通訊技術 、毫米波 、換手 、模糊理論
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    • 在5G網路中，為了使用到更大的頻寬，使用到了毫米波的技術。但由於毫米波訊號衰退較快的特性，使得使用毫米波傳輸的基地臺覆蓋範圍較小，導致了使用者裝置頻繁換手的問題變得更加嚴重。此外，對電信商來說，在短時間內就佈完所有毫米波基地臺的負擔太大。因此使用者裝置就必定會面對新的問題：在不同的環境中必須使用不同換手方針。為了解決此問題，在本篇論文中，一開始我們會從環境中蒐集與換手相關的資訊，接著再利用這些資料針對每個環境都設計出一套模糊控制系統。模擬的結果顯示，本篇提出的換手方法，在換手的次數以及斷線率上都可以贏過現存最新的方法，並且在效能上可以近似依據未來路徑決定是否換手的最佳方法。

    Millimeter-wave (mmWave) is proposed for 5G to provide high throughput up to multiple gigabits per second. However, the small coverage of base stations using mmWave leads the frequent handover problem to a more severe issue. Also, it is quite a burden for mobile operators to deploy mmWave base stations in every region in a short time. Therefore, user equipment using 5G faces a new issue: the necessity of adjusting the handover decision policy in different environments. To this purpose, in this thesis, we construct the specific fuzzy logic for each environment using the data collected from the environment. Simulation results show that in terms of the number of handovers and the number of connection failures, the proposed algorithm outperforms the state-of-the-art methods and approximates the optimal solution based on the future location information in all environments defined in the latest 3GPP specification.

    摘要 i Abstract ii Acknowledgements iii Contents iv List of Figures vi List of Tables viii Abbreviations ix 1 Introduction 1 2 Related Works 6 3 Handover Procedure 8 4 Fuzzy Logic 12 5 Algorithm 18 5.1 Idea of the Proposed Algorithm 18 5.2 Algorithm 20 5.2.1 Data Collection 20 5.2.2 Fuzzy Logic Construction 23 6 Simulation 29 6.1 Scenarios 29 6.2 Performance Metrics 31 6.3 Competitive Methods 32 6.4 Simulation Results 33 6.5 Evaluation 34 7 Conclusion 41 Bibliography 42 Appendices 44 A Simulation Details 44 A.1 Mobility 44 A.2 Handover 45 A.3 Performance Metrics 48

    [1] “Radio resource control (RRC) protocol specification,” 3GPP TS 38.331 (Release 16), 2020.
    [2] J. Bai, S. Yeh, F. Xue, and S. Talwar, “Route-Aware Handover Enhancement for Drones in Cellular Networks,” in IEEE GLOBECOM, 2019.
    [3] K. C. Silva, Z. Becvar, E. H. S. Cardoso, and C. R. L. Francês, “Self-tuning handover algorithm based on fuzzy logic in mobile networks with dense small cells,” in IEEE WCNC, 2018.
    [4] K. Da Costa Silva, Z. Becvar, and C. R. L. Frances, “Adaptive hysteresis margin based on fuzzy logic for handover in mobile networks with dense small cells,” IEEE Access, 2018.
    [5] “NR and NG-RAN overall description,” 3GPP TS 38.300 (Release 16), 2020.
    [6] “Study on scenarios and requirements for next generation access technologies,” 3GPP TR 38.913 (Release 16), 2020.
    [7] “Study on channel model for frequencies from 0.5 to 100 GHz,” 3GPP TR 38.901 (Release 16), 2019.
    [8] “Mobility enhancements in heterogeneous networks,” 3GPP TR 36.839 (Release 11), 2012.

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