臺灣博碩士論文加值系統

隨著 5G 移動通信系統的出現，在中低頻段獲得額外資源變得越
來越困難。為了進一步提高數據速率，毫米波技術逐漸受到關注，同
時它也被視為 5G/B5G 通信系統的重要組成部分。然而，由於毫米波
的傳播特性，毫米波通信的系統性能高度依賴於用戶關聯。為了替每
個用戶找到合適的基站並最大化系統吞吐量，我們制定並解決了用戶
關聯問題。具體而言，本文研究了包含多個基站和多個用戶的毫米
波 MIMO 無線網絡中的下行數據傳輸。我們發現用戶關聯問題是一
個非凸的優化問題，並提出了基於距離選擇的演算法以及最佳速率
配對（BRP）演算法，以獲得具有低計算複雜度的適當解決方案。此
外，我們對所提出的演算法與文獻中的一些用戶關聯算法進行了分析
和比較。模擬結果表明，BRP 演算法無論是在總和速率和計算複雜
度方面，均優於那些基準算法。

As 5G mobile communication systems emerge, it becomes more and more difficult to obtain additional resources in low and medium frequency bands. In order to further improve the data rate, millimeter wave technology has gradually attracted attention and has been regarded as an important component for 5G/B5G communication systems. However, due to the propagation characteristics of millimeter waves, the system performance of millimeter wave communications is highly dependent on user association. To find an adequate base station for each user and maximize the system throughput, we formulate and solve a user association problem. Specifically, we study downlink data transmission in a millimeter wave MIMO wireless network that contains multiple base stations and multiple users in this thesis. We find that the user association problem is a non-convex optimization problem and propose the distance-based selection algorithm and the best rate pairing (BRP) algorithm for obtaining an appropriate solution with low computational complexity. In addition, we analyze and compare the proposed algorithm with a number of user association algorithms in the literature. Simulation results show that the BRP algorithm outperforms those benchmark algorithms in terms of sum rate and computational complexity.

Contents
Chinese Abstract i
English Abstract ii
Acknowledgements iii
Contents iv
List of Tables vi
List of Figures viii
1 Introduction 1
2 Related Work 4
3 System Model and Problem Formulation 7
3.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3.2 Problem formulation . . . . . . . . . . . . . . . . . . . . . . . . 13
4 Proposed User Association Algorithm 15
4.1 Distance-based selection algorithm . . . . . . . . . . . . . . . . 16
4.2 Best rate pairing user association algorithm . . . . . . . . . . . 18
4.3 Modified BRP algorithm . . . . . . . . . . . . . . . . . . . . . . 21
4.4 Complexity analysis of BRP algorithm . . . . . . . . . . . . . . 22
5 Simulation Setup and Results 24
5.1 Simulation setup . . . . . . . . . . . . . . . . . . . . . . . . . . 25
5.2 Performance evaluation of simulation results . . . . . . . . . . 30
6 Conclusion 45
Bibliographies 47

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