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Tài liệu tham khảo chuyên ngành viễn thông Semi-blind signal detection for mimo and mimo-ofdm systems
SEMI-BLIND SIGNAL DETECTION FOR MIMO AND MIMO-OFDM SYSTEMS MA SHAODAN Ph. D. THESIS THE UNIVERSITY OF HONG KONG 2006 Abstract of thesis entitled “Semi-Blind Signal Detection for MIMO and MIMO-OFDM Systems” Submitted by Ma Shaodan for the degree of Doctor of Philosophy at The University of Hong Kong in May 2006 MIMO (Multiple Input Multiple Output) and MIMO-OFDM (Orthogonal Frequency Division Multiplexing) systems have attracted a lot of research interest in recent years due to their potential for future high speed wireless communications. This thesis focuses on the problem of signal detection and proposes three semi-blind algorithms for MIMO, MIMO-OFDM with short cyclic prefix (CP), and MIMO-OFDM without CP, respectively. A three-step semi-blind Rake-based multi-user detection technique is proposed for quasi-synchronous MIMO systems. The first step separates the multi-user multi-path signal vector into multi-user single-path signal vectors based on second-order statistics (SOS) of the received signals. A simple estimation method is proposed in the second step to estimate the time delays with the aid of pilots. The third step combines multiple multi-user single-path signal vectors for signal detection. System performance is improved by time diversity and only the upper bounds of the channel length and the time delays are required. Simulation results show that the proposed technique achieves good performance and is not sensitive to over-estimation of the maximum channel length and the maximum time delay. A MIMO-OFDM system with short CP is next considered for higher bandwidth efficiency and a time domain semi-blind signal detection algorithm is proposed. A new system model in which the ith received OFDM symbol is left shifted by J samples is introduced. Based on some structural properties of the new system model, an equalizer is designed using SOS of the received signals to cancel most of the inter-symbol interference (ISI). The transmitted signals are then detected from the equalizer output. In the proposed algorithm, only 2P (P is the number of transmit antennas/users in MIMO-OFDM systems) columns of the channel matrix need to be estimated, and channel length estimation is unnecessary. In addition, the proposed algorithm is applicable irrespective of whether the channel length is shorter than, equal to or longer than the CP length. Simulation results verify the effectiveness of the proposed algorithm, and show that it outperforms the existing ones in all cases. Finally, in order to further improve bandwidth efficiency, a MIMO-OFDM system without CP is considered and a two-step semi-blind signal detection algorithm is proposed. The algorithm is based on some structural properties derived from shifting the received OFDM symbols. The first step cancels inter-carrier interference (ICI) and ISI with an equalizer designed using SOS of the shifted received OFDM symbols. The second step involves signal detection from the equalizer output in which the signals are still corrupted with multi-antenna interference (MAI). In the proposed algorithm, precise knowledge of the channel length is unnecessary and only one pilot OFDM symbol is utilized to estimate the required channel state information. Simulation results show that the proposed algorithm achieves comparable performance to algorithms for standard MIMO-OFDM systems and it is robust against channel length overestimation. The number of words: 460 Semi-Blind Signal Detection for MIMO and MIMO-OFDM Systems by Ma Shaodan B. Eng., M. Eng., Nankai University, P. R. China A thesis submitted in partial fulfillment of the requirements for the Degree of Doctor of Philosophy at The University of Hong Kong May 2006 i Declaration I declare that this thesis represents my own work, except where due acknowledgement is made, and that it has not been previously included in a thesis, dissertation or report submitted to this University or to any other institution for a degree, diploma or other qualifications. Signed _________________________________ Ma Shaodan ii Acknowledgements I would like to take this chance to express the deepest gratitude to my supervisor, Professor T. S. Ng, for his continuous guidance and constructive suggestions during the course of my Ph.D. program. I owe my gratitude to my dear husband, Mr. Yang Guanghua, for his encouragement, support and helpful advices. I would like to thank Dr. K. W. Yip, Dr. N. Wong and Dr. Yonghong Zeng for their helpful discussions and valuable suggestions. I would also like to thank the members in my research group, Dr. Zhou Yiqing, Mr. Chen Jianwu, Mr. Zheng gan, Mr. Ng ChiuWa, Mr. Wang Hongzheng, Ms. Pan Xinyue, Ms. Peng Wei, for their friendship and useful discussions. I would express my thanks to all the staff in the Department of Electrical and Electronic Engineering for their supportive work. I also want to thank the University of Hong Kong for the award of postgraduate studentship. It supports my life in Hong Kong and makes me focus on my research. Finally, I owe my deepest gratitude to my parents, for their trust and support all the time. iii Contents Declaration ……………………………………………………………………….i Acknowledgements………………………………………………………………ii Table of Contents……………………………………………………………….iii List of Figures………………………………………………………………… .vi Abbreviations………………………………………………………………… viii Chapter 1 Introduction ………………………………………………… .1 1.1 MIMO ……………………………………………………………… 1 1.2 MIMO-OFDM ……………………………………………………….3 1.3 Semi-blind signal detection ………………………………………….4 1.4 Motivation and organization of the thesis ………………………… .6 Chapter 2 Semi-Blind Rake-Based Multi-User Detection for Quasi-Synchronous MIMO Systems ……………………………… 9 2.1 Introduction ………………………………………………………….9 2.2 System model ………………………………………………………12 2.3 Semi-blind Rake-based multi-user detection technique ……………14 2.3.1 Multi-user single-path signal separation ………………….15 2.3.2 Time delay estimation …………………………………….17 2.3.3 Multi-path combining …………………………………….19 2.3.4 Channel noise consideration …………………………… .21 2.3.5 Performance analysis …………………………………… 22 iv 2.4 Examples and simulation results ………………………………… .25 2.4.1 Time delay estimation …………………………………….25 2.4.2 Semi-blind Rake-based multi-user detection technique … 27 2.4.2.1 Example 1 ………………………………………….27 2.4.2.2 Example 2 ………………………………………….30 2.5 Summary ……………………………………………………………33 Chapter 3 Time Domain Semi-blind Signal Detection for MIMO-OFDM Systems with Short Cyclic Prefix ………………….35 3.1 Introduction ……………………………………………………… .35 3.2 System Model ……………………………………………………38 3.3 Time Domain Semi-Blind Signal Detection ……………………….41 3.3.1 Zero-noise case ………………………………………… .43 3.3.1.1 Equalization and signal detection ………………….44 3.3.1.2 partH estimation ……………………………………47 3.3.1.3 Remark ………………………………………… .48 3.3.2 Channel noise consideration …………………………… 49 3.3.3 Computational complexity ……………………………….50 3.4 Simulation results ………………………………………………….51 3.4.1 The case where the channel length is shorter than or equal to the CP length: L D≤ ……………………………………………52 3.4.2 The case where the channel length is longer than the CP length: L D> ……………………………………………………54 3.4.3 Comparison ……………………………………………….56 3.4.4 Data length effect …………………………………………57 3.5 Summary ……………………………………………………………58 v Chapter 4 Two-Step Semi-Blind Signal Detection for MIMO-OFDM Systems without Cyclic Prefix …………………………… .60 4.1 Introduction ……………………………………………………… 60 4.2 System Model ………………………………………………………62 4.3 Two-Step Semi-blind Signal Detection ……………………………66 4.3.1 Blind ICI and ISI cancellation ……………………………67 4.3.2 Signal detection in the presence of MAI ………………….70 4.3.3 Effect of channel noise ……………………………………71 4.3.4 Implementation ………………………………………… 72 4.4 Simulation Results …………………………………………………73 4.4.1 Effect of SNR ………………………………………….…73 4.4.2 Effect of the parameter K ……………………………… 76 4.4.3 Effect of channel length overestimation ………………….78 4.5 Summary ……………………………………………………………79 Chapter 5 Conclusions and suggestions for future research …………80 Reference ……………………………………………………83 Publications ………………………………………………….89 vi List of Figures 1.1 MIMO system ………………………………………………….2 1.2 MIMO-OFDM system ………………………………………… .4 1.3 Semi-blind technique …………………………………………….6 2.1 Quasi-synchronous transmission scheme ……………………….12 2.2 Block diagram of semi-blind Rake-based multi-user detection technique ……………………………………………………….15 2.3 Rake-based receiver …………………………………………….20 2.4 Time delay estimation (1d = 2, 2d =4 and 3d=1) ………………26 2.5 BER versus SNR (synchronous MIMO system) ……………… 29 2.6 BER versus the estimated maximum channel length ˆL (SNR = 18dB; synchronous MIMO systems) ……………………………30 2.7 BER versus SNR (quasi-synchronous MIMO system) …………31 2.8 BER versus the estimated maximum channel length ˆL (SNR = 20dB; quasi-synchronous MIMO systems) …………………… 32 2.9 BER versus the estimated maximum delay ˆPUd (SNR = 20dB; quasi-synchronous MIMO system) …………………………….33 3.1 Block diagram of time domain signal detection algorithm for MIMO-OFDM system with short CP ………………………… .42 [...]... sequence and blind information Blind methods All symbols are considered as unknown Fig 1.3 Semi-blind technique 1.4 Motivation and organization of the thesis In MIMO and MIMO- OFDM systems, a number of signals from multiple antennas are transmitted through multi-path channels They may suffer from a deep fading and be corrupted by interference and noise at the receiver Signal detection is therefore an... mobile communication systems and for higher bandwidth efficiency, this thesis addresses the signal detection problem for three systems in the following three chapters In Chapter 2, a quasi-synchronous MIMO system is considered and a semi-blind Rake-based multi-user detection technique is proposed It consists of three steps: multi-user single-path signal separation, time delay estimation and multi-path combination... received signals of all users as synchronous so that many of the existing signal detection algorithms [Zhu, Ding and Cao, 1999; Lopez-Valcarce and Dasgupta, 2001; Moulines, Duhamel, Cardoso and Mayrargue, 1995; Tugnait, 2001; Miller, Taylor and Gough, 2001; Abed-Meraim, Loubaton and Moulines, 1997; Liu and Xu, 1997; Hua, An and Xiang, 2003] for synchronous MIMO systems can be used to separate the users’ signals... that better BER performance is achieved by time diversity and the proposed technique is not sensitive to over-estimation of the maximum channel length and the maximum time delay In Chapter 3, a MIMO- OFDM system with short CP is considered for higher bandwidth efficiency and a time domain semi-blind signal detection algorithm is proposed An equalizer is designed using SOS of the received signals to cancel... Receiver RX M Fig 1.2 MIMO- OFDM system 1.3 Semi-blind signal detection Traditional signal detection techniques use training sequences to estimate the channel as the first step Signal detection then follows equalization Most mobile communication standards such as GSM (Global System of Mobile communication) include training sequence to estimate the channels These techniques are robust and yield accurate... capacity of MIMO systems can grow linearly with the number of transmit and receive antennas [Winters, Salz and Gitlin, 1994; Foschini and Gans, 1998; Paulraj, Gore, Nabar and Bolcskei, 2004] A lot of research interest has thus been attracted to MIMO systems due to their high capacity and spectral efficiency in recent years [Dai, Molisch and Poor, 2004; Chizhik, Ling, Wolniansky, Valenzuela, Costa and Huber,... step is signal detection from the equalizer 7 output in which the signals are still corrupted with multi-antenna interference (MAI) In the proposed algorithm, precise knowledge of the channel length is unnecessary and only one pilot OFDM symbol is utilized By computer simulations, it is shown that the proposed algorithm achieves comparable performance to algorithms for standard MIMO- OFDM systems and it... in time delay estimation and intersymbol interference cancellation As a promising candidate for the future 4G mobile communication standards, MIMO- OFDM has high system capacity and is robust against frequency selective fading However, in most of the works for MIMO- OFDM system, a cyclic prefix is required at the beginning of each OFDM symbol [Sampath, Talwar, Tellado, Erceg 6 and Paulraj, 2002; Stuber,... [Sampath, Talwar, Tellado, Erceg and Paulraj, 2002; Stuber, Barry, Mclaughlin, Li, Ingram and Pratt, 2004; Bolcskei, Gesbert and Paulraj, 2002; Bolcskei, Borgmann and Paulraj, 2003; Dubuc, Starks, Creasy and Hou, 2004] It is being adopted in the coming WLAN standard (IEEE 802.11n) and is recognized as a strong candidate for the future 4th generation (4G) mobile communications standards CP insertion TX 2 IDFT... separates the multi-user multi-path signal vector into multi-user single-path signal vectors based on second order statistics (SOS) of the received signals without knowledge of the channel state information The second step is time delay estimation which is essential for signal detection The third step combines multiple multi-user single-path signals and detects the multi-user signals The first step in the . 2006 Abstract of thesis entitled Semi-Blind Signal Detection for MIMO and MIMO- OFDM Systems Submitted by Ma Shaodan for the degree of Doctor of Philosophy. SEMI-BLIND SIGNAL DETECTION FOR MIMO AND MIMO- OFDM SYSTEMS MA SHAODAN Ph. D. THESIS