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研究生: 陳俊安
Chen, Chun An
論文名稱: 適用於多使用者多輸出多輸入下漏訊號預編碼之廣義特徵值分解處理器設計及實作
Design and Implementation of Generalized Eigenvalue Decomposition Processor for Leakage-based Precoding in MU-MIMO Systems
指導教授: 黃元豪
Huang, Yuan Hao
口試委員: 賴以威
蔡佩芸
陳喬恩
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 通訊工程研究所
Communications Engineering
論文出版年: 2015
畢業學年度: 104
語文別: 英文
論文頁數: 64
中文關鍵詞: 多用戶多輸出輸入漏訊號預編碼廣義特徵值分解
外文關鍵詞: multi-user MIMO (MU-MIMO), Leagage-based, GEVD
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  • 在最近幾年,無線應用已經是生活上不可缺少的一部分,因此高速率,高可靠性的傳輸是必要的。考慮到實際基地台情況,多使用者的多輸出輸入系統被廣泛的研究。在這系統下的線性預編碼中,漏訊號預編碼是主要的一種技術,而在編碼過程中,不可避免的會使用到廣義特徵值分解運算。因此實作
    廣義特徵值分解處理器是有必要的,而提出的兩種硬體演算法是改善運算中的一部分,目的是為了避免完整的矩陣倒數的硬體來降低複雜度。在本論文中,完整實作了廣義特徵值分解處理器,並且提出的演算法改善了其中的一部分,最後還有硬體上的分析結果。


    The high data rate and the quality of transmission is attached great importance in recent years.Though the multiple-input-multiple-output (MIMO) system can achieve these requirement, the new MIMO technology called generalized spatial modulation MIMO (GSM-MIMO) that has additional consideration about power consumption.This thesis proposes a hardware design of CECML-OB-MMSE detector \cite{CECML} called parallel 4 shared index processing with joint QR-SIC in GSM-MIMO system.At the index selection, the new algorithm uses shared index method instead of memory access to reduce hardware resource and computational complexity.And the parallel technology trades off the hardware latency and area.At the symbol detection, we use joint QR-SIC detector \cite{JQRSIC} instead of MMSE detector to avoid matrix inverse and decrease hardware latency.After using error correction code (ECC), the BER performance of this algorithm is close to maximum likelihood (ML).The hardware architecture is designed and verificated by FPGA. The analysis of hareware area, hareware timing and hareware power are presented as well.

    1 Introduction 3 1.1 Multi-User MIMO (MU-MIMO System) . . . . . . . . . . . . . . . . . . 3 1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.3 Thesis Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2 MU-MIMO System and Precoding Scheme 7 2.1 MU-MIMO System Model . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2 MU-MIMO Precoding Scheme . . . . . . . . . . . . . . . . . . . . . . . . 8 2.2.1 BD-Based Precoder . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2.2 Leakage-Based Precoder . . . . . . . . . . . . . . . . . . . . . . . 11 3 Generalized Eigen-Value Decomposition 15 3.1 Definition of GEVD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.2 Implementation of GEVD . . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.2.1 Cholesky Decomposition . . . . . . . . . . . . . . . . . . . . . . . 19 3.2.2 Jacobi Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 4 Proposed GEVD with Matrix Inversion Bypass 25 4.1 Triangular Matrix Inversion with Block-wise Multiplication . . . . . . . . 25 4.2 Forward Substitution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 4.3 Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 5 Architecture Design 35 5.1 System Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 5.1.1 Matrix Initial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 5.1.2 Cholesky Decomposition . . . . . . . . . . . . . . . . . . . . . . . 38 5.1.3 TMI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 5.1.4 FS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 5.1.5 Jacobi Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 5.2 Fixed-point Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 5.3 Simulation Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 5.4 Synthesis Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 5.4.1 Synthesis Result of floating point notation . . . . . . . . . . . . . 57 6 Conclusion 61

    [1] Keke Zu; de Lamare, R.C.; Haardt, M., “Generalized Design of Low-Complexity Block Diagonalization Type Precoding Algorithms for Multiuser MIMO Systems,” in Communications, IEEE Transactions, vol. 57, no. 4, October 2013, pp. 4232–4242.
    [2] Sadek, M.; Tarighat, A.; Sayed, A.H., “A Leakage-Based Precoding Scheme for Downlink Multi-User MIMO Channels,” in Communications, IEEE Transactions, vol. 57, no. 4, May 2007, pp. 1711–1721.
    [3] C.-E. Chen, T.-W. Cho, and W.-H. Chung, “Blockwise-lattice-reduction-aided
    Tomlinsion-Harashima precoder Designs for MU-MIMO downlink communications with clusters of correlated users,” in IEEE Vehicular Technology, vol. 57, no. 4,
    Mar 2014.
    [4] S. Zhao, Y. Zhao, H. Sun, J. Liu, L. Zhang, and L. Gui, “An interference-aware precoding scheme with other-cell interference for downlink milti-user mimo channel,”
    in IEEE Vehicular Technology Conference, vol. 57, no. 4, Sept 2010.
    [5] U. Jayasinghe, N. Rajatheva, and M. Latva-aho, “Leakage based multi user beamforming scheme to mitigate interference in mimo-fbmc,” in 17th International ITG Workshop on Smart Antennas, vol. 57, no. 4, March 2013.
    62 BIBLIOGRAPHY
    [6] H.Stark and J.W.Woods, “Probability and Random Processes with Applications to Signal Processing,3rd,” in Edition Prentice Hall, 2002.
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    [8] F. Sch¨afer, M. Stege, C. Michalke, and G. Fettweis, “Efficient tracking of eigenspaces and its application to mimo systems,” in Proceedings of the IST Mobile and Wireless Communications Summit. Citeseer, 2003, pp. 1–6.
    [9] G. Huang and L. Wang, “High-speed signal reconstruction with orthogonal matching pursuit via matrix inversion bypass,” in Signal Processing Systems (SiPS), 2012 IEEE Workshop on, Oct 2012, pp. 191–196.
    [10] Yen-Lin Chen, “A Low-Complexity 128x7 Spatial Modulation MIMO Detector with Joint Subset QR Decomposition,” Master’s thesis, National Tsing Hua University, Taiwan, Nov 2015

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