博碩士論文 100521009 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:26 、訪客IP:18.224.32.86
姓名 陳其懋(Chi-mao Chen)  查詢紙本館藏   畢業系所 電機工程學系
論文名稱 多使用者多輸入輸出系統之區塊性QR分解與湯林遜哈洛希瑪前編碼演算法及多模QR分解器實作
(Design of BD-QRD and B-THP algorithms and Implementation of multi-mode QRD for Multi-user MIMO precoding system)
相關論文
★ 具輸出級誤差消除機制之三位階三角積分D類放大器設計★ 應用於無線感測網路之多模式低複雜度收發機設計
★ 用於數位D類放大器的高效能三角積分調變器設計★ 交換電容式三角積分D類放大器電路設計
★ 適用於平行處理及排程技術的無衝突定址法演算法之快速傅立葉轉換處理器設計★ 適用於IEEE 802.11n之4×4多輸入多輸出偵測器設計
★ 應用於無線通訊系統之同質性可組態記憶體式快速傅立葉處理器★ 3GPP LTE正交分頻多工存取下行傳輸之接收端細胞搜尋與同步的設計與實現
★ 應用於3GPP-LTE下行多天線接收系統高速行駛下之通道追蹤與等化★ 適用於正交分頻多工系統多輸入多輸出訊號偵測之高吞吐量QR分解設計
★ 應用於室內極高速傳輸無線傳輸系統之 設計與評估★ 適用於3GPP LTE-A之渦輪解碼器硬體設計與實作
★ 下世代數位家庭之千兆級無線通訊系統★ 協作式通訊於超寬頻通訊系統之設計
★ 適用於3GPP-LTE系統高行車速率基頻接收機之設計★ 多使用者多輸入輸出前編碼演算法及關鍵組件設計
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 本篇論文提出改良型的前編碼技術,適用於 8x8多使用者多輸入多輸出系統,並且完成硬體設計。此無線通訊系統傳送機以及接收機星座圖對應支援到16QAM,而多輸入多輸出系統則是可以支援傳送端和接收端各8根天線。我們利用回傳的通道資訊來實現前編碼技術,並且為了善用多使用者多輸入輸出(MU-MIMO)中訊號多樣性的特性(Spatial diversity),我們捨棄了傳統的前編碼技術,改用了區塊性的前編碼技術,其中包括使用QR分解(QR decomposition)技術來消去多重存取干擾(multiple access interference, MAI),並且搭配區塊性THP (block-Tomlinson-Harashima precoding )將餘數索引(modulo index)分解以及消去剩餘的符際干擾(inter symbol interference, ISI),而我們也提出區塊性的排序方法來平衡各個使用者中的對角線的能量分布,最後,改良過後的球面解碼器不僅僅增加在區塊性前編碼系統之解碼效能,在複雜度上面也跟傳統解碼器相同。
在硬體實作方面,我們採用管線式架構來達到高吞吐量的目的,並且以相同的4x4 Sorted QR硬體架構,堆疊出8x8 Sorted QR硬體,並且提供逐層排序、逐區塊排序的功能。並且設計反向輸入的硬體架構,使同樣的硬體能更有效率的應用。在硬體實現上面,我們採用Givens Rotation演算法,並且以CORDIC實現。最後我們將設計實作,整體gate count 是1098 K,面積則是2605um*2605um,吞吐量則可以達到9.46MQRD/s,並且可以支援多層排序或者區塊排序等多種模式。
摘要(英) This thesis presents a multi-user MIMO transceiver design with a block-based decomposition and precoding scheme. To exploit spatial diversity, we propose to use block-diagonal QR decomposition (BD-QRD) to decompose the channel matrix. To eliminate multiple access interference (MAI), block-Tomlinson-Harashima precoding (B-THP) is further proposed to be combined with BD-QRD so that the equivalent channel matrix after precoding at the transmitter becomes a block diagonal matrix. On the other hand, the block-based sorting is adopted to balance the energy spread among all spatial pipes for BD-QRD and thus the performance can be further enhanced. With these decomposition and precoding techniques at the transmitter, the sphere decoding (SD) techniques can be employed at the receiver with a small revision to constrain the search space. We show that the proposed BD-QRD, B-THP, and constrained SD for multi-user MIMO systems retaining the spatial diversity ,outperforms the conventional QRD-THP and BD-SVD in the interested SNR region.
In hardware design, we use pipelined architecture to achieve high throughput . In order to reduce the complexity, the 8x8 Sorted QR can be built up by 4x4 Sorted QR. Two kinds of sorting strategies, one is per-layer sorting and the one is block-based sort. The Givens Rotation of the QRD is adopted for its merit in pipelining with the CORDIC operation. We have implemented the proposed system in TSMC 0.90um CMOS technology. The gate-count are 1098K, throughput is 9.46MQRD/s and chip area is 2605um*2605um.
關鍵字(中) ★ 多輸入多輸出
★ QR分解
★ 球面解碼器
關鍵字(英) ★ QRD
★ THP
★ BD-QRD
★ BD-THP
論文目次 目錄 iii
圖示目錄 v
表格目錄 vii
第1章 緒論 1
1.1 簡介 1
1.2 研究動機 2
1.3 論文組織 2
第2章 多使用者多輸入多輸出(MU-MIMO)系統 3
2.1 介紹 3
2.2 多輸入多輸出前編碼系統(MIMO Precoding) 4
2.2.1 傳統QRD及THP 6
2.2.1.1 QR分解(QR Decomposition ) 7
2.2.1.2 THP演算法(Tomlinson-Harashima Precoding)[8] 7
2.3 多使用者多輸入多輸出前編碼系統(MU-MIMO Precoding) 9
2.3.1 區塊對角化幾何平均分解法(Block-Diagonal GMD, BD-GMD) 9
2.3.2 區塊性奇異值分解法(Block Diagonal-Singular Value Decomposition ,BD-SVD)[6] 10
2.3.3 規則區塊對角化分解法(RBD)[6] 12
2.4 所提出的區塊性前編碼技術 13
2.4.1 區塊性QR分解(BD-QRD) 14
2.4.2 區塊性THP演算法(B-THP) 15
2.4.3 區塊性排序(Block-based sorting) 16
2.4.3.1 External Sorting 17
2.4.3.2 Internal Sorting 18
2.5 所提出的球面解碼機技術 19
2.5.1 傳統球面解碼機[12] 20
2.5.2 擴大搜尋的球面解碼機 22
2.5.3 所提出之球面解碼機 24
2.6 模擬與比較 25
第3章 硬體架構設計 28
3.1 硬體設計流程 28
3.2 QR分解 29
3.2.1 Givens Rotation演算法 29
3.2.2 CORDIC硬體 32
3.2.3 Complex PE 35
3.3 4x4 Sorted QRD 硬體 36
3.4 8x8 Sorted QRD 硬體 39
3.4.1 Pre-sorting 46
3.4.2 Remaining Norm Calculation 47
3.4.3 Memory control[12] 49
3.5 反向輸入硬體架構 50
3.6 決定Cordic階數及word length 54
3.7 硬體實現之模擬 57
第4章 電路實現與布局設計 60
4.1 晶片佈局設計 60
4.2 晶片佈局結果與規格 61
第5章 結論 64
參考文獻 65
參考文獻 [1] Rusek, F.; Persson, D.; Buon Kiong Lau; Larsson, E.G.; Marzetta, T.L.; Edfors, O.; Tufvesson, F., "Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays," IEEE Signal Processing Magazine, vol.30, no.1, pp.40,60, Jan. 2013.
[2] Y. Jiang, W. Hager, and J. Li, “The geometric mean decomposition,” Linear Algebra and Its Applications, vol. 396, pp. 373-384, Feb. 2005.
[3] C. P. Wu, and J. M. Wu, "Low-complexity channel decomposition for spatial multiplexing MIMO system," IEEE 9th Workshop on Signal Processing Advances in Wireless Communications, Jul. 2008, pp. 156-160.
[4] S. Lin, W. L. Ho, and Y. C. Liang, "Block-Diagonal Geometric Mean Decomposition (BD-GMD) for Multiuser MIMO Broadcast Channels," IEEE 17th International Symposium in Personal, Indoor and Mobile Radio Communications, 2006, pp. 1-5.
[5] Shaowei Lin, W. L. Ho, and Ying-Chang Liang, "Block-Diagonal Geometric Mean Decomposition (BD-GMD) for Multiuser MIMO Broadcast Channels", IEEE 17th PIMRC 2006, pp. 1-5.
[6] V. Stankovic, and M. Haardt, "Generalized Design of Multi-User MIMO Precoding Matrices," IEEE Trans. Wireless Commun., vol. 7, no. 3, pp. 953-961, March 2008.
[7] M. Joham and W. Utschick, "Ordered Spatial Tomlinson Harashima Precoding. chapter 20," EURASIP, Hindawi Publishing Corporation, 2005.
[8] M.B. Shenouda and T.N. Davidson, "A framework for designing mimo systems with decision feedback equalization or tomlinson-harashima precoding," IEEE Journal on Selected Areas in Communications, vol. 26, no. 2, pp. 401-411, Feb. 2008.
[9] Z. Y. Huang, and P. Y. Tsai, "Efficient Implementation of QR Decomposition for Gigabit MIMO-OFDM Systems," Circuits and Systems I: Regular Papers, IEEE Transactions, vol. 58, no. 10, pp. 2531-2542, Oct. 2011.
[10] C. H. Lin, P. Y. Tsai, “A Reduced-Complexity Multi-user MIMO Precoding Scheme with Sorted-QR Decomposition and Block-based Poweer Allocation,” ITST, 2011, pp. 658-662.
[11] D. Wubben, R. Bohnke, J. Rinas,V. Kuhn, and K.D.Kammeyer, "Efficient algorithm for decoding layered spacetime codes," Electronics Letters, vol. 37, no. 22, pp. 1348-1350, Oct. 2001.
[12] H.C Lin, "A 4×4 MIMO Detector for IEEE 802.11n Systems," master thesis, National Central University, July. 2009.
[13] M. Mohaisen et al. “Fixed complexity vector pertubation with block diagonalization for MU-MIMO systems,” IEEE Malaysia Conference on Communications, 2009, pp. 238-243.
[14] A. Maltsev, V. Pestretsov, R. Maslennikov, and A. Khoryaev, "Triangular systolic array with reduced latency for QRdecomposition of complex matrices," in Proc. IEEE International Symposium on Circuits and Systems, pp.385-388, May 2006.
[15] Z. Y. Huang, "High-Throughput QR Decomposition for MIMO Detection in OFDM Systems," master thesis, National Central University, Dec. 2010.
[16] C.Z. Zhan, K.Y. Jheng, Y.L. Chen, T.J. Jheng, and A.Y. Wu, "High-convergence-speed low-computation- complexity SVD algorithm for MIMO-OFDM systems," International Symposium on VLSI Design, Automation and Test, pp. 195-198, 2009.
指導教授 蔡佩芸(Pei-yun Tsai) 審核日期 2014-7-18
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明