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系統識別號 U0026-2007201513214400
論文名稱(中文) 多重路徑時間延遲之有效回傳估計及其在OFDM系統的應用
論文名稱(英文) The estimation of channel delays and its application on the OFDM system
校院名稱 成功大學
系所名稱(中) 電腦與通信工程研究所
系所名稱(英) Institute of Computer & Communication
學年度 103
學期 2
出版年 104
研究生(中文) 蔡皓宇
研究生(英文) Hao-Yu Tsai
學號 Q36021363
學位類別 碩士
語文別 英文
論文頁數 51頁
口試委員 指導教授-張名先
口試委員-蘇賜麟
口試委員-劉宗憲
口試委員-賴癸江
中文關鍵字 通道資訊  方向性  最小方差貼合  壓縮  Karhunen–Loève Expansion  高斯量化  旋轉不變技術估計信號參數 
英文關鍵字 CSI  beamforming  least-square fitting  compression  Gaussian quantization  Karhunen-Loève Expansion  ESPRIT 
學科別分類
中文摘要 由於多天線-多載波系統擁有優異的通道容量及錯誤機率,並且可提昇傳輸效率,已受到矚目許久。藉由回傳的通道資訊,傳送端可使用預先編碼器改善系統的效能。方向性向量是重要的通道資訊,可以有效的應用在預先編碼-多輸出多輸入的系統上。為了更有效率的回傳通道資訊,我們基於Karhunen–Loève Expansion(KLE) ,提出回傳估測的通道響應至傳送端的方法。我們將KLE的係數當作通道響應重建的參數。而KLE係數的個數比起通道響應的數量少很多,這是很有效率的資料壓縮。這些係數為高斯分佈,在多輸入多輸出-正交分頻多工調變的系統下,為了有效率的回傳係數,我們使用高斯量化來減少量化誤差。

然而,在以往的研究中,通常會假設接收端已知完整的通道資訊,以利研究方便。而實際上,通道資訊往往會隨著環境改變。在無線通訊系統下,接收端會受到多重路徑延遲的影響,對於使用KLE於回傳估測的通道響應至傳送端的方法而言,若我們在未知實際多重路徑延遲之時間下回傳通道,傳送端收到的通道會因此而不準確,使得錯誤率提升。模擬結果顯示,若我們能在傳送端/接收端準確地估計出多重路徑延遲之時間,就能使通道的回傳更準確,使錯誤率不至於上升。
英文摘要 Multiple-antennas and multiple-carriers systems have been attracted a plenty of attention for a long time due to the outstanding capacity, error performance and throughput. The transmitter can apply the precoding based on the fed-back channel state information (CSI). The beamforming vectors, which are essential CSI, could be applied in precoded multiple-input multiple-output (MIMO) systems. In order to efficiently feed back CSI, we propose some schemes that feed back the estimated channel responses (CRs) in the receiver to the transmitter based on the Karhunen-Loeve Expansion (KLE). The coefficients of the KLE are used as the parameters for rebuilding CRs. The number of coefficients of the KLE is much fewer than the size of CRs within a block, and this leads to efficient compression. These KLE coefficients are of Gaussian distribution. To efficiently feed back the coefficients for the MIMO system with orthogonal frequency-division multiplexing (OFDM), we use the Gaussian quantization (GQ) to reduce quantization error. We consider two types of one-dimensional blocks of CRs. We also apply the two-dimensional block of CRs. We develop efficient methods to estimate the multipath delays in the transmitter by using some previously fedback CRs. With the better estimated channel delays in the transmitter, one can reduce the delay of CR feedback and enhance its application on the precoding of the MIMO system.
論文目次 中文摘要 i
Abstract iii
誌 謝 v
List of Tables viii
List of Figures viii
Chapter 1. 1
Introduction 1
1.1 Motivation 1
1.2 Organization of this thesis 2
Chapter 2. 4
Close-loop MIMO-OFDM Systems 4
2.1 System and Channel Model 4
2.2 Channel Model 8
2.2.1. Jake’s Rayleigh Fading Model 8
2.2.2. Multipath Model 9
2.3 Close-loop MIMO-OFDM Systems with Finite-Rate Feedback 12
2.4 The Karhunen-Loève Expansion(KLE) of a Random Vector 13
2.5 Karhunen-Loève Expansion of CRs in OFDM system 14
2.5.1 Signal Model 14
2.5.2 Across time slots ‒ Type A 16
2.5.3 Across time slots ‒ Type B 18
2.5.4 Two Dimension(2-D) block of CRs – Type C 22
2.6 Gaussian Quantization 24
2.7 Normalize coefficient’s variance 28
2.8 Compare performance with one Dimension and simulations 30
2.9 Feedback loads 33
Chapter 3. 34
Modified Frequency-Domain Approach for Channel Estimation 34
3.1 Traditional Estimation of Multipath time delay 34
3.2 Modified Estimation of Multipath time delay 37
3.3 Simulation 39
Chapter 4. 40
Conclusion 40
Bibliography 41
參考文獻 [1] Kuhne A., “throughput analysis of multi-user OFDMA-systems using imperfect CQI feedback and diversity techniques,” IEEE J. Select. Areas Commun., vol. 26, no. 8, pp. 1440 - 1450, October 2008.
[2] S.Guharoy, N.B. Mehta, “Joint Evaluation of Channel Feedback Schemes, Rate Adaptation, and Scheduling in OFDMA Downlinks With Feedback Delays,” IEEE Trans. Veh. Technol., vol. 62, No. 4, pp. 1719-1731, May 2013.
[3] Sungyoon Cho, S. A. Jafar, N. Jindal, S. Vishwanath, “Feedback-Topology Designs for Interference Alignment in MIMO Interference Channels,” IEEE Trans. Signal Process, vol. 60, No. 12, pp. 6561 - 6575, December 2012.
[4] Soysal, A., “Joint Channel Estimation and Resource Allocation for MIMO Systems–Part I: Single-User Analysis” IEEE Trans. Wireless Commun., vol.9, no.2, pp. 624- 631 February 2010.
[5] H. Sampath, P. Stoica, and A. Paulraj, “Generalized linear precoder and decoder design for MIMO channels using the weighted MMSE criterion,” IEEE Trans. Commun., vol. 49, no. 12, pp. 2198-2206 Dec. 2001.
[6] A. Scaglione, P. Stoica, S. Barbarossa, G. B. Giannakis, and H. Sampath, “Optimal designs for space-time linear precoders and decoders,” IEEE Trans. Signal Processing, vol. 50, no. 5, pp. 1051-1064, May. 2002.
[7] S. Zhou, G. B. Giannakis, “Optimal transmitter eigen-beamforming and space-time block coding based on channel mean feedback,” IEEE Trans. Signal Process, vol. 50, no. 10, pp. 2599-2613 ,Oct. 2002.
[8] J. C. Roh and B. D. Rao, “Transmit beamforming in multiple-antenna systems with finite rate feedback: a VQ-based approach,” IEEE Trans. Inform. Theory, vol. 52, no. 3, pp. 1101-1112, Mar. 2006.
[9] J. C. Roh and B. D. Rao, “Design and analysis of MIMO spatial multiplexing systems with quantized feedback,” IEEE Trans. Signal Processing, vol. 52, no. 8, pp. 2874-2886, Aug. 2006.
[10] B. C. Banister, J. R. Zeidler, “Feedback assisted transmission subspace tracking for MIMO systems”, IEEE Trans. Select. Areas Commun, vol. 21, no. 3, pp. 452-463, Apr. 2003.
[11] J. Yang and D. B. Williams, “Transmission subspace tracking for MIMO Systems with low-rate feedback,” IEEE Trans. Commun., vol. 55, no. 8, pp.1629-1639, Aug. 2007.
[12] J. Choi and R. W. Heath, Jr., “Interpolation based transmit beamforming for MIMO-OFDM with limited feedback,” IEEE Trans. Signal Processing, vol. 53, no. 11, pp. 4125-4135, Nov. 2005.
[13] J. Choi, B. Mondal, and R. W. Heath, Jr., “Interpolation based unitary precoding for spatial multiplexing MIMO-OFDM with limited feedback,” IEEE Trans. Signal Processing, vol. 54, no. 12, pp. 4730-4740, Dec. 2006.
[14] N. Khaled, B. Mondal, G. Leus, R. W. Heath Jr., F. Petr´e, “Interpolation-Based Multi-Mode Precoding for MIMO-OFDM Systems with Limited Feedback,” IEEE Trans. Wireless Commun., vol. 6, no. 3, pp. 1003-1013, Mar. 2007.
[15] T. Pande, D. J. Love, and J. V. Krogmeier, “A weighted least squares approach to precoding with pilots for MIMO-OFDM,” IEEE Trans. Signal Processing, vol. 54, no. 10, pp. 4067-4073, Oct. 2006.
[16] H. Zhang, Y. Li, V. Stolpman, and N. V. Waes, “A reduced CSI feedback approach for precoded MIMO-OFDM systems,” IEEE Trans. Wireless Commun., vol. 6, no. 1, pp. 55-58, Jan. 2007.
[17] S. Zhou, B. Li, and P. Willett, “Recursive and trellis-based feedback reduction for MIMO-OFDM with rate-limited feedback,” IEEE Trans. Wireless Commun., vol. 5, no. 12, pp. 3400-3405, Dec. 2006.
[18] L. Liu and H. Jafarkhani, “Successive transmit beamforming algorithms for multiple-antenna OFDM systems,” IEEE Trans. Wireless Commun., vol. 6, no. 4, pp. 1512-1522, Apr. 2007.
[19] D.J. Love, R.W. Heath. Jr., W. Santipach, M.L. Honig, “What is the value of limited feedback for MIMO channels” IEEE Commun. Mag vol. 42, No. 10, pp. 54-59, Oct. 2004.
[20] M. X. Chang and Y. T. Su, “Model-based channel estimation for OFDM signals in Rayleigh fading,” IEEE Trans. Commun., vol. 50, pp. 540-544, Apr. 2002.
[21] M. X. Chang and Y. T. Su, “Performance analysis of equalized OFDM systems in Rayleigh fading,” IEEE Trans. Wireless Commun., vol. 1, pp. 721-732, Oct. 2002.
[22] D.J. Love, R.W. Heath. Jr., W. Santipach, M.L. Honig, “What is the value of limited feedback for MIMO channels” IEEE Commun. Mag vol. 42, No. 10, pp. 54-59, Oct. 2004.
[23] L. Yunxin and H. Xiaojing, "The simulation of independent Rayleigh faders,", IEEE Trans. Commun.s, vol. 50, pp. 1503-1514, 2002.
[24] V. Erceg, et. al., “IEEE P802.11 Wireless Lans: TGn Channel Models,” IEEE 802.11-03/940r4, 2004.
[25] S. Haykin, “Communication System,” 4th ed. John Wiley & Sons, New Jersey, 2001.
[26] B. Vucetic, J. Yuan, “Space-Time Coding,” John Wiley & Sons, England, 2003
[26] Y. V. Zakharov and T. C. Tozer, “Local splines in signal processing applications: low complexity, high accuracy” Communication Research Group, Department of Electronics, University of York, York YO10 5DD,UK.
[27] Y. V. Zakharov and T. C. Tozer, ”Local spline approximation of time-varying channel model,” ELECTRONICS LETTERS 8th November 2001 Vol. 37 No. 23.
[28] Michael Unser, Member, IEEE, Akram Aldroubi, and Murray Eden, Life Felloe, IEEE,”B-Spline Signal Processing: Part I-Theory”, IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 41, NO. 2. FEBRUARY 1993.
[29] Michael Unser, Member, IEEE, Akram Aldroubi, and Murray Eden, Life Felloe,
IEEE,” B-Spline Signal Processing: Part II-Efficient Design and Applications” IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 41, NO. 2. FEBRUARY 1993.
[30] Yuriy V. Zakharov, Member, IEEE, Tim C. Tozer, Member, IEEE, and Jonathan F. Adlard,”Polynomial Spline-Approximation of Clark’s Model” IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 52, NO. 5. MAY 2004
[31] Faculty of Mathematics and Mechanics, Moscow State University, 119 899, Moscow, Russia,”Spline Approximation of random processes and design problems” Journal of Statistical Planning and Inference 84 (2000) 249-262.
[32] Efficient Estimation of Channel Path Delays for the OFDM System.
[33] Channel State Information (CSI) Reduction in Frequency and Time Domain for Close-loop MIMO-OFDM Systems.
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