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研究生: 林祺雄
Lin, Chi-Hsiung
論文名稱: 運用向量擾動及交換技術於相互關聯之多重輸入輸出通道及有限回饋系統
Vector Perturbation and Permutation for Correlated MIMO Channel with Limited Feedback System
指導教授: 吳仁銘
Wu, Jen-Ming
口試委員:
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: 2009
畢業學年度: 97
語文別: 英文
論文頁數: 61
中文關鍵詞: 向量擾動有限回饋向量交換相互關聯
外文關鍵詞: Vector Perturbation, Limited Feedback, Vector Permutation, Correlated
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  • 在本論文中,我們研究向量擾動技術於多輸入多輸出通訊。本論文最主要貢
    獻有三方面。首先,在多使用者之多輸入多輸出系統裡我們提出雙模式向量擾動
    技術,雙模式向量擾動技術可以減少球面編碼次數。其次,在點對點多輸入多輸
    出系統裡我們提出向量交換技術且把向量交換技術和向量擾動技術結合於多使
    用者的多輸入多輸出系統裡使傳輸能量功率減少,提出一個可以同時搜尋最佳擾
    動向量和交換向量的樹狀搜尋方法。第三,把提出的向量擾動及交換技術運用於
    相互關聯通道之有限回饋系統,提出的向量擾動及交換技術可以抵抗通道相互關
    聯之劣化,預先定義的查尋表被提出來為了搜尋最佳的擾動向量和交換向量。最
    後,我們利用數值模擬的方法來證實這三個提出來系統的效能。


    In this thesis, we have studied the vector perturbation precoding techniques for MIMO
    communications [1]. The major contributions of this thesis are in three folds. First, we
    propose dual modes vector perturbation transmitter based multiuser MIMO systems.
    The dual modes vector perturbaion transmitter can reduce the number of sphere encoder
    [1] calls. Second, we propose the vector permutation system for point-to-point MIMO
    systems and combine the vector permutation with vector perturbation for multi-user
    MIMO systems with multiple antenna receiver to further reduce the energy of tranmitted
    signal of vector perturbation system. A searching algorithm of optimal perturbation
    vector and permutation vector simultaneously by tree search is also proposed. Third,
    the proposed vector permutation and perturbation is applied to limited feedback system
    in correlated channel. The proposed vector permutation and perturbation system can
    combat the degradation of channel correlation. The predefining lookup table is proposed
    for searching the optimal perturbation and permutation vectors. Finally, we verify the
    performance of three proposed systems by means of numerical simulations.

    1 Introduction 1 2 Precoder of Limited Feedback MIMO System 4 2.1 Limited Feedback System [8] 5 2.1.1 System Model of Limited Feedback System 5 2.1.2 Receiver of Limited Feedback System 6 2.2 Matrix Quantization [8] 8 2.2.1 Minimum Singular Value Selection Criterion 8 2.2.2 Mean Squared Error Selection Criterion 9 2.2.3 Capacity Selection Criterion 10 2.3 Vector Quantization [9] 10 2.3.1 Quantization of Precoding Matrix 11 2.3.2 Reconstruction of Precoding Matrix 14 3 Vector Perturbation 16 3.1 Introduction of Vector Perturbation System [1] 17 3.1.1 System Model of Vecotr Perturbation System 17 3.1.2 Transmitter of Vector Perturbation System 18 3.1.3 Receiver of Vector Perturbation System 20 3.2 Sphere Endcoder [1, 3, 4] 21 3.3 Proposed Dual Modes Vector Perturbation Transmitter 24 3.3.1 Objective of Perturbation 24 3.3.2 The Proposed Dual Modes Transmitter 25 4 Proposed Vector Permutation in Vector Perturbation for Open Loop MIMO System 27 4.1 Vector Permutation for Point-to-Point MIMO System 28 4.1.1 System Model 28 4.1.2 Tree Search of Permutation Vector 30 4.2 Vector Permutation in Vector Perturbation for Point-to-Point MIMO System 34 4.2.1 System Model 34 4.2.2 Tree Search of Perturbation Vector and Permutation Vector 36 4.3 Vector Permutation in Vector Perturbation for Multi-user MIMO Systems with Multiple Antenna Receiver 40 5 Proposed Vector Perturbation and Permutation for Correlated MIMO Channel with Limited Feedback System 42 5.1 System Model 43 5.2 Searching Complexity 46 5.3 System Analysis 47 6 Simulation Results 50 6.1 Proposed Dual Modes Vector Perturbation Transmitter 50 6.2 Proposed Vector Permutation in Vector Perturbation for Multi-user with Multi-antenna MIMO Systems 53 6.3 Proposed Vector Perturbation and Permutation for Correlated MIMO Channel with Limited Feedback System 55 6.3.1 Matrix Quantization 55 6.3.2 Vector Quantization 56 7 Conclusion 59 Bibliography 60

    [1] B. M. Hochwald, C. B. Peel, and A. L. Swindlehurst, “A vector perturbation technique for near-capacity multiantenna multiuser communication-part II: Perturbation,”IEEE Transactions on Communications, vol. 53, pp. 537–544, Mar 2005.
    [2] C. B. Peel, B. M. Hochwald, and A. L. Swindlehurst, “A vector-perturbation technique for near-capacity multiantenna multiuser communication-Part I: Channel inversion and regularization,” IEEE Transactions on Communications, vol. 53, pp. 195–202, Jan 2005.
    [3] E. Agrell, T. Eriksson, A. Vardy, and K. Zeger, “Closest point searches in lattices,” IEEE Trans. Inf. Theory, vol. 48, pp. 2201–2214, Aug 2002.
    [4] Jianzhong Zhang; Kyeong Jin Kim, “Near-Capacity MIMO Multiuser Precoding with QRD-M Algorithm,” IEEE Signals, Systems and Computers, pp. 1498–1502, Oct 2005.
    [5] J. Jaldén, J. Maurer, and G. Matz, “On the diversity order of vector perturbation precoding with imperfect channel state information,” Proc. IEEE SPAWC’08, pp. 211–215, July. 2008.
    [6] J. MaurerJ., Jaldén, and G. Matz, “Transmit outage precodingwith imperfect channel state information under an instantaneous power constraint,” Proc. IEEE SPAWC’08,pp. 66–70, July. 2008.
    [7] J. P. Kermoal, L. Schumacher, K. I. Pedersen, P. E. Mogensen, and F. Frederiksen,“A stochastic MIMO radio channel model with experimental validation,” IEEE Jour. Select. Areas in Commun, vol. 20, pp. 1211–1226, Aug. 2002.
    [8] D. J. Love and R. W. Heath Jr., “Limited feedback unitary precoding for spatial multiplexing systems,” IEEE Transactions Information Theory, vol. 51, pp. 2967–2976, Aug 2005.
    [9] Q. Li and C. N. Georghiades, “Precoder quantization for MIMO-OFDM systems over frequency selective channels,”IEEE Mobile and Wireless Communications Summit,
    pp. 1–5, 2007.
    [10] M. H. M. Costa, “Writing on dirty paper,” IEEE Transactions on Information Theory,vol. 29,no. 3 pp. 439–441, May 1983.
    [11] D. J. Love. (2004) Complex Grassmannian codebook. [Online]. Available at http://www.ece.purdue.edu/~djlove/grass.html.
    [12] IEEE Std 802.16eTM-2005 and IEEE Std 802.16TM-2004/Cor1-2005, “Part 16: Air interface for fixed and mobile broadband wireless access systems,” pp. 457–458.

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