混合波束成形的波束分配演算法 用於下行鏈路 MIMO LEO 衛星通訊

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陳茗薇(Ming-Wei Chen) 查詢紙本館藏

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論文名稱

混合波束成形的波束分配演算法用於下行鏈路 MIMO LEO 衛星通訊
(Beam Allocation Algorithms with Hybrid Beamforming for Downlink MIMO LEO Satellite Communications)

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至系統瀏覽論文 (2027-1-5以後開放)

摘要(中)

在第六代行動通訊( 6G )，行動通訊與各種近端傳輸技術、低軌道衛星通訊系統以及包括毫米波在內等創新通信技術等將融合為一體，逐步實現不管是何時何地皆可以無縫式接收及覆蓋。然而，低軌道衛星通訊系統在第六代（6G）行動通訊中是一項新興的候選技術。
本文中，我們提出大規模多輸入多輸出（MIMO）低地球軌道（LEO）衛星通訊（SATCOM）基於全連接架構的混合波束成形。假設已知通道狀態資訊（CSI），我們可以透過已知的通道狀態資訊，設計混合發射器及混合接收器。先前有學者針對類比端進行波束設計，建立編碼簿，以波束形成增益 (Beamforming Gain) 達到最大為出發點，配置波束，指向訊號方向。前面學者所提的配置波束方法，複雜度較高。本文主要提出低複雜波束配置演算法，以達到最高傳送資料速率為出發點，配置波束。最後，選擇接下來要服務的使用者，是以SINR的大小做挑選，以確保本文提出的演算法選出的使用者與前面學者所提出之結果不會相差甚遠。這代表接下來須服務的使用者是有良好的通道，可以帶來較佳的通訊環境。總結，在本文所提出的演算法，與先前學者所提出的方法挑選接下來要服務的使用者的結果並沒有相差甚遠，且降低複雜度。

摘要(英)

The sixth generation of mobile communications (6G) will integrate mobile communications with Near Field Communication (NFC), the Low Earth Orbit (LEO) satellite communications systems (SATCOM), and innovative communications technologies including millimeter waves, and gradually achieve seamless reception and coverage no matter when and where. LEO satellite communication systems are increasingly considered as a potential technology for the sixth generation (6G) of mobile communications.
In the paper, we introduced a hybrid beamforming approach based on a fully connected architecture for massive Multiple-Input Multiple-Output (MIMO) Low Earth Orbit (LEO) satellite communications. Assuming that the channel state information (CSI) is known, we can design hybrid precoders and combiners based on the known channel status information. Previously, some scholars conducted analog beamformer design, making a beamforming codebook, based on the maximum beamforming gain to allocate analog beamformer and point the signal direction. The beam allocation algorithm proposed by previous scholars, but the complexity is high. This article mainly proposed a low-complexity beam allocation algorithm, based on achieving the highest transmission data rate, proposing an algorithm to allocate beamformer, and finally selecting the users to be served next based on the Signal to Interference plus Noise Ratio (SINR), to ensure that there will not a big gap between our algorithm and previous algorithm of results. This means that the users to be served next have a better channel, which can bring about a better communication environment. The proposed algorithm is not far different from the algorithm proposed by scholars in selecting the users to be served next, it reduces the complexity.

關鍵字(中)

★ 編碼簿
★ 波束配置
★ 衛星通訊系統
★ 大規模多輸入多輸出
★ 混合波束成形
★ 多使用者

關鍵字(英)

★ Codebook
★ Beam allocation
★ Satellite Communication
★ Massive MIMO
★ Hybrid Beamforming
★ Multi-user

論文目次

Content
論文摘要 ......ii
Abstract ......iv
致謝 .....vi
Contents ......vii
List of Figures ......viii
List of Tables ......ix
Chapter 1. Introduction ......1
1.1. Satellite Communication ......1
1.2. Massive MIMO ......3
1.3. Structure of Hybrid Beamforming ......4
1.4 Beamforming Codebook ......5
1.5. Contribution ......6
1.6. Organization ......7
1.7. Abbreviations ......8
1.8. Notation ......9
Chapter 2. System Model ......11
2.1. Hybrid Precoding and Combining ......11
2.2. Beamforming Codebook Structure ......13
2.3. Channel Model ......16
Chapter 3. Proposed Hybrid Beamforming ......21
2.3.1 Codebook-based Analog beamforming Design ......22
2.3.2 Coordinated Block Diagonalization for Digital Beamforming ...... 27
Chapter 4. Low-complexity beam allocation (LBA) Algorithm and User Selection ......32
Chapter 5. Computational Complexity and Simulation Results ......41
Chapter 6. Conclusion ......50
References ......51

List of Figures
Figure 1. Satellite communication system architecture ......2
Figure 2. Comparison of traditional MIMO(Left) and Massive MIMO(Right). ......3
Figure 3. Comparison of fully digital beamforming structure (Left) and hybrid beamforming structure (Right). ......5
Figure 4. Mapping strategies for analog precoder Fully-connected (Left) Partially-connected (Right). ......5
Figure 5. Illustration of downlink u-th user satellite communication systems (SATCOM) system with hybrid beamforming architectures. ......11
Figure 6. The beam allocation in the LEO satellite massive MIMO communication system. ......21
Figure 7. Algorithm of the brute-force search. ......23
Figure 8. Comparing the channel capacity (bits/s/Hz) of Random beam allocation and Brute-force search. ......45
Figure 9. Comparing the channel capacity (bits/s/Hz) of three different combinations of the desired beam patterns. ......45
Figure 10. Selected users are identical probability between two algorithms ......47
Figure 11. Channel Capacity (bits/s/Hz) comparing between two algorithms. ......48
Figure 12. Channel Capacity (bits/s/Hz) comparing between Low-complexity beam allocation algorithms and three different combinations of the desired beam patterns. ......48

List of Tables
Table 1. List of abbreviations used in the thesis. ......8
Table 2. List of Parameters. ......9
Table 3. Table of Complexity. ......44

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指導教授

陳永芳(Yung-Fang Chen)

審核日期

2024-1-9

推文