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研究生： 薛又方
Hsueh, Yu-Fang
論文名稱： 使用鏈路聚合框架之異質性Li-Fi與Wi-Fi無線網路中負載平衡機制之探討
On Load Balancing in Heterogeneous Li-Fi and Wi-Fi Networks Using a Link Aggregation Framework
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： 2023
畢業學年度： 111
語文別： 英文
論文頁數： 71
中文關鍵詞： 可見光通訊 、射頻網路 、額外負擔 、負載平衡 、使用者滿意度 、使用者移動性 、鏈路聚合
外文關鍵詞： Light Fidelity (Li-Fi), Wireless Fidelity (Wi-Fi), overhead, load balancing, user satisfaction, user mobility, link aggregation
相關次數： 點閱：122  下載：4 
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    • 隨著室內無線通訊設備的增加，射頻波段的頻譜資源變得有限，作為一種新興技術，可見光網路（Li-Fi）在解決射頻網路（Wi-Fi）的頻譜短缺問題方面受到廣泛研究。可見光具有比射頻波段更寬的頻寬，並且不受頻譜監管限制。然而，由於可見光無法穿透不透明物體的特性，Li-Fi易受到障礙物的影響，其覆蓋範圍和Wi-Fi相比也較小，但意味著Li-Fi提供了更高的安全性。為了充分利用Li-Fi和Wi-Fi的優勢，混合式Li-Fi與Wi-Fi網路的概念應運而生，讓使用者可以同時享受高傳輸速率的Li-Fi和廣覆蓋範圍的Wi-Fi。此外，由於可見光和射頻波段不重疊，使用者還可以同時從Li-Fi和Wi-Fi接收資料，從而營造出更優越的無線網路環境。
    在混合式無線網路中，負載平衡是一個重要且值得關注的議題，需要在網路效能和資源利用之間找到平衡點。然而，目前的研究主要著重於最大化網路吞吐量，且未能全面考慮到所有混合式網路中的相關議題。本論文旨在提出一種著重於使用者滿意度的動態資源配置演算法，以最大化使用者滿意度並同時滿足個別使用者的特定需求。此演算法綜合考量使用者的體驗和需求，並根據此資源配置優化整個無線網路系統的性能。

    Considering the increasing deployment of indoor wireless communication devices, the limited availability of spectrum resources in the radio frequency (RF) band has become a prominent concern. To address this issue, visible light communication (VLC), also known as Li-Fi, has garnered significant research attention. By utilizing the wider bandwidth of the visible light spectrum, Li-Fi offers a potential solution to spectrum scarcity problems encountered in RF-based Wi-Fi networks. However, Li-Fi’s coverage area is constrained due to the inability of visible light to penetrate opaque objects. Nonetheless, this limitation brings about enhanced security advantages. To leverage the strengths of both Li-Fi and Wi-Fi, the concept of hybrid Li-Fi and Wi-Fi networks (HLWNets) has emerged, enabling users to benefit simultaneously from the high transmission rates provided by Li-Fi and the wide coverage offered by Wi-Fi. Furthermore, since the visible light and RF bands do not overlap, users can receive data concurrently from both Li-Fi and Wi-Fi, creating a superior wireless network environment.
    In HLWNets, Load balancing (LB) plays a critical role in achieving optimal network performance and efficient resource utilization. However, existing research predominantly focuses on maximizing network throughput, overlooking a comprehensive consideration of all pertinent aspects in HLWNets. This thesis aims to propose a dynamic resource allocation algorithm that prioritizes user satisfaction, with the goal of maximizing user satisfaction while effectively meeting the specific requirements of individual users. By comprehensively considering user experience and needs, this algorithm aims to optimize the overall performance of HLWNets.

    摘要 II Abstract IV 致謝 VI Contents VII List of Figures X List of Tables XI Chapter 1 Introduction 1 Chapter 2 Background 4 2.1 Concepts of Li-Fi and LA-HLWNets 4 2.2 Common Challenges in LA-HLWNets 5 Chapter 3 Related Work 8 3.1 Experimental works on LA-HLWNets 8 3.2 Methods of Access Point Selection 9 3.2.1 Optimization-Based Methods 9 3.2.2 Ruled-Based Methods 10 3.2.3 Learning-Based Methods 11 3.3 Methods of Resource Allocation 11 3.3.1 Evenly Shared Strategy 12 3.3.2 Other Strategy 12 Chapter 4 System Models 14 4.1 Li-Fi Channel Model 14 4.1.1 Li-Fi Channel Gain 14 4.1.2 Li-Fi Signal-to-Interference-Plus-Noise Ratio 15 4.1.3 Li-Fi Link Data Rate 16 4.2 Wi-Fi Channel Model 16 4.2.1 Wi-Fi Channel Gain 16 4.2.2 Wi-Fi Signal-to-Noise Ratio 17 4.2.3 Wi-Fi Link Data Rate 17 4.3 Orientation-based RWP Mobility Model 17 4.4 System Overhead 18 4.4.1 Handover Overhead 19 4.4.2 LA Overhead 20 Chapter 5 Proposed Schemes 21 5.1 Motivation 21 5.2 Notation 22 5.3 Problem Formulation 23 5.4 Overall Framework and Pre-Calculation Stage 26 5.5 Proposed LB algorithm 27 5.5.1 Access Point Selection (APS) algorithm 29 5.5.2 Resource Allocation (RA) Algorithm 31 5.5.3 Reconfigure APS (RAPS) Algorithm 33 5.6 Time Complexity Analysis 36 Chapter 6 Performance Evaluation 39 6.1 Parameter Setting 39 6.2 Performance Metrics 41 6.3 Simulation Results 42 6.3.1 Effect of the Number of Users 43 6.3.2 Effects of Speed Threshold mathbit{Vthre} with fixed user type 49 6.3.3 Effects of Speed Threshold mathbit{Vthre} with fixed number of users 52 6.3.4 Effect of mathbit{delta} 55 6.3.5 Effect of Weight Configurations 58 6.3.6 Effect of User’s Free Movement In and Out of Rooms 60 Chapter 7 Conclusion 66 References 68

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