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研究生： 賴文裕
Lai, Wen-Yu
論文名稱： 以NOMA為基礎之異質性無線網路中以用戶滿意度最大化為目標之移動性管理與資源管理之探討
On Mobility Management and Resource Management for User Satisfaction Maximization in NOMA-based Heterogeneous Wireless Networks
指導教授： 許靜芳
Hsu, Ching-Fang
學位類別： 碩士
Master
系所名稱： 電機資訊學院 - 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年： 2024
畢業學年度： 112
語文別： 英文
論文頁數： 112
中文關鍵詞： 可見光通訊 、射頻網路 、混合網路 、負載平衡 、切換代價 、非正交多重接取 、功率分配
外文關鍵詞： Light Fidelity, Wireless Fidelity, Hybrid Networks, Load Balancing, Handover Overhead, Non-Orthogonal Multiple Access, Power Allocation
相關次數： 點閱：128  下載：0 
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    • 隨著行動通訊設備的普及與傳輸技術的進步，對於射頻網路的負載逐漸提升。可見光通訊(Li-Fi)做為一種正在興起的技術，常被視為能與無線網路(WI-FI)互補的方案，補充面臨短缺的射頻頻譜。Li-Fi 具有更寬敞且不受控管的頻寬、更高的傳輸速度以及由光無法穿透不透明物體而得到的保密性，但也因此頻段特性導致傳輸距離受到限制，覆蓋範圍相比Wi-Fi更小。
    為了進一步系統效能，研究人員利用頻段不相同的特性將兩者結合並得出混合式 Li-Fi 與 Wi-Fi 網路，目標是讓系統能同時享有Li-Fi 的高效傳輸速率與Wi-Fi的大範圍無間段傳輸。在用戶具有移動性的架構中，不同系統的結合會伴隨以下幾個問題，如無線存取點選擇與負載平衡等等，如何替用戶做出合適的選擇會是一個重要的問題，若用戶被分配到負載量大的存取點中，則可能令系統因資源不足而導致效能下降。
    非正交多重接取(NOMA)作為多重接取的新興技術透過讓用戶使用相同頻段而提升傳輸效率，近年被大量學者進行研究，本論文旨在將此技術引入混合式 Li-Fi 與 Wi-Fi 網路中，透過觀察無線存取點附載量的評估調整對移動性管理與資源管理進而最大化用戶滿意度。

    With the growing number of mobile communication devices and advancements in transmission technology, the loading of radio frequency networks has been increasing. Light Fidelity (Li-Fi), an emerging technology, is often seen as a complementary solution to Wireless Fidelity (Wi-Fi), supplementing the increasingly scarce radio frequency spectrum. Li-Fi offers broader and free-license bandwidth, higher transmission speeds, and enhanced security due to light's inability to penetrate opaque objects. However, Li-Fi also faces limitations in transmission distance due to its frequency band characteristics, resulting in a smaller coverage area compared to Wi-Fi.
    To enhance system performance, researchers have combined the distinct characteristics of both technologies, creating a hybrid Li-Fi and Wi-Fi network. The goal is to achieve the high transmission rates of Li-Fi while maintaining the broad, seamless coverage of Wi-Fi. In user mobility scenarios, combining different systems introduces several challenges, such as access point selection (APS) and load balancing (LB). Making appropriate choices for users is important, as assigning users to heavily loaded access points could lead to performance degradation due to insufficient resources.
    Non-Orthogonal Multiple Access (NOMA), an emerging multiple access technology, improves transmission efficiency by allowing users to share the same frequency bandwidth. This technology has garnered significant research interest in recent years. This thesis aims to introduce NOMA into hybrid Li-Fi and Wi-Fi networks, observing system load and adjusting mobility and resource management to maximize user satisfaction.

    摘要 I Abstract II 致謝 IV Contents V List of Figures VIII List of Tables X Chapter 1 Introduction 1 Chapter 2 Background 3 2.1 The Concept of VLC Technology 3 2.2 Multiplexing on VLC Architectures 3 2.3 Multiple Access on VLC Architectures 5 2.4 Hybrid Li-Fi Wi-Fi Networks 6 Chapter 3 Related Work 8 3.1 Access Point Selection and Handover Decision (HD) 8 3.2 Power Allocation (PA) 12 3.3 Grouping 13 Chapter 4 System Models 15 4.1 Li-Fi Channel Model 15 4.1.1 Li-Fi Channel Gain 16 4.1.2 Li-Fi Channel SINR in LACO-OFDM based NOMA Structure 16 4.2 Wi-Fi Channel Model 19 4.2.1 Wi-Fi Channel Gain 19 4.2.2 Wi-Fi Channel SNR 20 4.3 Random Waypoint Model (RWP) 20 Chapter 5 Proposed Schemes 22 5.1 Motivation 22 5.2 Notation 23 5.3 Problem Formulation 26 5.4 Overall Framework 27 5.5 Modulation Mode Determination in an Environment with Grouping 28 5.6 Timer Setting 31 5.7 Proposed LB Algorithm 31 5.7.1 Handover Decision Algorithm 34 5.7.2 System Load-Aware Access Points Selection 35 5.7.3 Rate-Guaranteed Required Resource Calculation Algorithm 37 5.7.4 Resource Allocation Algorithm 38 5.7.5 Minimal Rate Gap Priority Resource Allocation Algorithm 42 5.8 Time Complexity Analysis 44 Chapter 6 Performance Evaluation 47 6.1 Parameter Setting 47 6.2 Performance Metrics 49 6.3 Numerical Results 51 6.3.1 The Impact of the Number of UEs to Satisfaction Level 52 6.3.2 The Impact of the Number of UEs to Fairness of Ωavg 54 6.3.3 The Impact of the Number of UEs to Throughput 56 6.3.4 The Impact of the Number of UEs to Outage Probability 58 6.3.5 The Impact of the Number of UEs to Handover Rate 59 6.3.6 The Impact of the Number of UEs to Average Power Consumption 61 6.3.7 The Impact of Guaranteed Data Rate in HDL 64 6.3.8 The Impact of the Number of Groups 70 Chapter 7 Conclusion 73 References 74 Appendix A 79

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