低軌道衛星通訊之下鏈混合預編碼設計及效能模擬

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姓名

徐啓豪(Chi-Hao Hsu) 查詢紙本館藏

畢業系所

通訊工程學系

論文名稱

低軌道衛星通訊之下鏈混合預編碼設計及效能模擬
(Hybrid Precoding Design and Performance Simulation for Downlink Low Earth Orbit Satellite Communications)

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摘要(中)

在後5G 及6G 無線通訊中，非地面網路通訊變得非常重要，傳統的地面通訊網路
為二維度的通訊網路，其中會遇到許多無法避開的問題，像是都市地區嚴重的環境干
擾以及遮蔽眾多，而非都市地區地面網路的部屬和維護成本相當高，而衛星網路可以
三維的角度達到廣義的覆蓋面積，並在第一時間傳輸資料給指定的地面用戶，對於海
洋或森林等非人口密集地區提供了非常大的效益，大幅度的提供與地面通訊的靈活性
和整合性。
本研究只要探討使用低軌道衛星進行下鏈通訊傳輸資料至地面用戶，由於三維度
通訊網路中無線鏈路的長往返延遲和都卜勒效應的影響，使低軌道衛星的資料傳輸受
到雜訊干擾，使用預編碼算法以及功率控制策略，以消除通訊環境下的雜訊干擾，並
降低資料傳輸錯誤率。
設計問題採用最小化資料傳輸錯誤率與最大化總資料傳輸率作為設計目標。此聯
合設計是一個非凸問題。為解決這些設計困難，本研究提出使用低軌道衛星混合預編
碼算法來解決這個聯合問題，通過應用半正定鬆弛算法將原始問題轉化為寬鬆凸子問
題，進而求得低軌道衛星最低資料傳輸錯誤率算法。使用類比預編碼器使衛星先行對
準固定的幾個方向，在使用數位預編碼器消除其餘的雜訊干擾。

摘要(英)

In Beyond Fifth-Generation (B5G) and Sixth-Generation (6G) wireless communication,
non-terrestrial network (NTN) communication becomes very important. The traditional
terrestrial communication network is a two-dimensional communication network, which will
encounter many unavoidable problems, such as serious environmental interference in urban
areas And there are many shades, the deployment and maintenance costs of the ground network
in non-urban areas are quite high, and the satellite network can achieve a broad coverage area
from a three-dimensional perspective, and transmit data to designated ground users in the first
time. For oceans or forests Non-populated areas such as non-populated areas provide very large
benefits, and provide a large degree of flexibility and integration with ground communications.
This study only discusses the use of low earth orbit (LEO) satellites for downlink
communication to transmit data to ground users. Due to the long round-trip delay of the wireless
link in the three-dimensional communication network and the influence of the Doppler effect,
the data transmission of (LEO) satellites is interfered by noise , using precoding algorithm and
power control strategy to eliminate noise interference in the communication environment and
reduce the error rate of data transmission.
The design problem takes minimizing the data transmission error rate and maximizing the
total data transmission rate as design goals. This joint design is a non-convex problem. In order
to solve these design difficulties, this study proposes to use a hybrid precoding algorithm for
(LEO) satellites to solve this joint problem. By applying the semidefinite relaxation (SDR)
algorithm, the original problem is transformed into a loose convex subproblem, and then the
iii
lowest data transmission error rate algorithm for (LEO) satellites is obtained. The analog
precoder is used to align the satellites in several fixed directions in advance, and the digital
precoder is used to eliminate the rest of the noise interference.

關鍵字(中)

★ 非地面網路
★ 衛星通訊網路
★ 預編碼算法
★ 功率控制
★ 混合預編碼算法
★ 半正定鬆弛算法

關鍵字(英)

★ Index Terms- non-terrestrial network communication
★ satellite network
★ precoding algorithm
★ power control
★ hybrid precoding algorithm
★ semi-positive definite relaxation algorithm

論文目次

摘要 ................................................................................................................................ i
Abstract .......................................................................................................................... ii
目錄 ............................................................................................................................... v
圖目錄 ......................................................................................................................... vii
表目錄 ........................................................................................................................ viii
符號說明 ...................................................................................................................... ix
第一章緒論 .................................................................................................................. 1
1-1 研究背景與動機 ............................................................................................. 1
1-2 研究目的與問題 ............................................................................................. 3
1-3 文獻探討 ......................................................................................................... 5
1.3.1 低軌道衛星之預編碼應用 .................................................................. 5
1.3.2 混合預編碼演算法之無線通訊系統應用 .......................................... 7
1-4 論文貢獻 ....................................................................................................... 13
第二章低軌道衛星下鏈通訊 .................................................................................... 14
2-1 通道模型 ....................................................................................................... 14
2-2 系統模型 ....................................................................................................... 15
2-3 最佳化問題 ................................................................................................... 16
第三章低軌道衛星預編碼器演算法 ........................................................................ 17
3-1 低軌衛星下鏈地面用戶純數位預編碼演算法 ........................................... 17
..... 3.1.1 最大比例合併 (Maximum Ratio Combining, MRC) 預編碼演算法..17
...3.1.2 迫零 (Zero-forcing, ZF) 預編碼演算法 ………………………..……18
3-2 低軌衛星下鏈地面用戶混和預編碼演算法 ............................................... 19
3.2 基於SVD 混合預編碼演算法 ..................................................................... 19
第四章基於離散相位低軌道衛星混合預編碼演算法設計 .................................... 21
vi
4.1 基於基因演算法(Genetic Algorithm,GA)類比預編碼演算法 .................... 21
4.2.1 基於SDR 離散相位低軌道衛星類比預編碼器優化設計 ....................... 24
4.2.2 基於SDR 離散相位低軌道衛星數位預編碼器優化設計 ....................... 28
第五章模擬結果 ........................................................................................................ 32
5-1 類比預編碼器量化比較 ............................................................................... 33
5-2 混合預編碼演算法以及純數位預編碼演算法位元錯誤率比較 ............... 41
5-3 混合預編碼演算法以及純數位預編碼演算法總傳輸率比較 ................... 44
第六章結論 ................................................................................................................ 46
參考文獻 ..................................................................................................................... 47

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指導教授

古孟霖(Meng-Lin Ku)

審核日期

2023-6-13

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