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作者(中文):江衍緒
作者(外文):Chiang, Yen-Shu
論文名稱(中文):基於波束成型技術並適用於多用戶多輸入輸出下行通訊系統之干擾消除方法
論文名稱(外文):Beamforming-based Interference Cancellation for Multiuser MIMO Downlink Communications
指導教授(中文):馬席彬
指導教授(外文):Ma, Hsi-Pin
學位類別:碩士
校院名稱:國立清華大學
系所名稱:電機工程學系
學號:9661557
出版年(民國):99
畢業學年度:98
語文別:英文
論文頁數:72
中文關鍵詞:多用戶多輸入輸出下行通訊系統
外文關鍵詞:multiuser MIMO downlink
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此篇論文,提出了一種基於波束成型技術(MB-BD)並適用於多用戶多輸入輸出下行通訊系統(multiuser MIMO downlink communications)之干擾消除方法。最大化波束成型(Maximul Beamforming)是一種用來改善接收端訊號雜訊比的方法,但是只適用於單一訊號串流的傳輸。此論文提出之預先編碼方法是基於最大化波束成型並適用於多訊號串流傳輸,在多用戶多輸入輸出下行通訊系統的性能分析(總速率(sum rate)與位元錯誤率(bit error rate))上已用數學式仔細的計算並採用模擬驗證。MB-BD可以改善每一個接收端之SNR因其使用兩個對應到第一及第二大特徵值之強健特徵向量所形成的和空間來傳送資料,所提出的系統架構在錯誤率在0.001之條件下比區塊對角化(BD)之方法約有6dB的增益量且總速率跟區塊對角化是差不多的。

各種不同關於多用戶多輸入輸出下行通訊系統之傳輸方法比如說線性與非線性預先編碼之方法在此篇論文也會被拿來介紹與討論。區塊對角化是近年來非常引人注目之用於多用戶多輸入輸出下行通訊系統且可預先消除多用戶干擾的預先編碼技術,但此技術需要做兩次的特徵值分解(或奇異值分解)找出每個用戶對應到的預先編碼矩陣來預先消除多用戶干擾以及最大化總速率。跟區塊對角化來比,因為此提出的架構只要作一次的特徵值分解(或奇異值分解)和一次的QR分解就可以找出每個用戶對應到的預先編碼矩陣來預先消除多用戶干擾,此提出的架構在傳送端的運算複雜度上大致節省了約37.5%。

為了提升接收端的檢驗器性能且擁有比較低的運算複雜度,在每個接收端我們使用經化簡後的最大近似檢驗器,跟原來的最大近似檢驗器比較,在每個接收端大致可節省33.5%的運算複雜度。
1 Introduction 1
1.1 Multiuser MIMO Downlink Systems . . . .1
1.2 Motivation . . . . . . . . . . .2
1.3 Main Contributions . . . . . . . . 3
1.4 Thesis Organization . . . 4
2 Multiuser MIMO Downlink Systems 5
2.1 SystemDescriptions . . . . . 5
2.1.1 The Problems in Multi-User MIMO Channel .7
2.2 Multiuser MIMO Channel Estimation in TDD and FDD Systems 8
2.3 Degrees of Freedom in the Downlink . 9
2.4 Capacity in MIMO Channel . 9
3 Multiuser MIMO Transmit Processing with Instantaneous CSIT 13
3.1 Multi-User Transmission via Nonlinear Processing 13
3.1.1 Dirty-Paper Precoding . . . . . . 13
3.1.2 Tomlinson-Harashima Precoding . . . 14
3.1.3 Precoding Based on Vector Perturbation .16
3.2 Multi-User Transmission via Linear Processing 17
3.2.1 Channel Inversion . . . 18
3.2.2 Regularized Channel Inversion . . . . 23
3.2.3 Block Diagonalization . . . . 26
3.2.4 Generalised Zero-Forcing Channel Inversion 29
3.2.5 Generalised MMSE Channel Inversion . . 30
4 The Proposed Transmit Processing with Instantaneous CSIT 33
4.1 Maximum Beamforming . . . . . . . . 33
4.2 Proposed Interference Cancellation Method Based on Maximum Beamforming 35
4.3 Proposed System Model . . . 40
4.4 Process of Simplified ML Detection Method . . 41
4.5 Complexity Comparisons . . . . . . .43
5 Simulation Results and Discussions 47
5.1 Simulation Results and Discussions in MU-MIMO Systems with Perfect Channel 47
5.2 Simulation Results and Discussions in MU-MIMO Systems with Imperfect Channel . .58
6 Conclusions and Future Works 67
6.1 Conclusions . . . . 67
6.2 Future Works . . . 67
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