MIMO-OFDM系统信道估计技术研究
摘要
随着近几年来无线通信的迅猛发展,对下一代移动通信(4G)的研究已经开展得如火如荼。新一代移动通信可以提供更高的数据传输速率,在有限的频谱资源上实现高速率和大容量。其中,正交频分复用(OFDM)可以有效地将频率选择性衰落信道转化成多个并行平坦衰落信道,从而大大提高传输效率。多输入多输出(MIMO)在原有传输带宽和功率消耗的基础上,在发射机与接收机之间并行传输多路独立数据,大大增加信道容量,成倍地提高频谱利用效率。
将OFDM和MIMO技术相结合,可以兼具OFDM抗多径时延特性、抗频率选择性衰落以及高频谱利用率,和MIMO有效提高系统容量,显著提高网络覆盖范围和传输可靠性的优点。
在MIMO-OFDM系统中,通过接收端信道估计获得信道状态信息(CSI,Channel State Information),是正确恢复发送信号的必要环节,其准确性将直接影响系统整体性能。本文主要针对MIMO-OFDM系统中信道估计展开研究。
第一章介绍了OFDM、MIMO的技术背景与发展现状,及信道估计技术概况。
第二章介绍了无线信道的传播特性。首先介绍了无线信道传播中信号强度的影响因素,进而引出衰落信道的定义和分类。
第三章介绍了OFDM、MIMO及MIMO-OFDM系统,并简要介绍了MIMO系统空时编码技术及发展情况。最后对OFDM系统中的重要参数做了说明。
第四章研究SISO-OFDM系统中的信道估计技术。针对块状、梳状和散布状导频信道估计,重点研究了4种导频估计算法、6种内插算法以及导频图案对传输性能的影响。
第五章研究MIMO-OFDM系统中的信道估计技术。针对频域估计,研究了导频图案设计。针对时域估计,推导了主要抽头简化算法和利用最优训练序列优化估计性能,并提出判决反馈时域重要抽头改进算法。最后,基于前面研究结果,结合WiMAX802.16e协议,完整实现了MIMO-OFDM系统中的信道估计。
第六章总结了本文的工作,给出结论,对下一步工作进行了展望。
With the rapidly increase of wireless data and multimedia application in recent years, research on the next generation(4G) mobile communication has being widely and deeply developed. The 4G communication system is a wireless network with high spectrum efficiency and high rate in limited bandwidth, and it supports high bit rate data transmission for many services. With the parallel modulation, orthogonal frequency-division multiplexing (OFDM) can change a frequency selective fading channel to be several flat fading channels, thus improving the transmission efficiency tremendously. Multiple-input multiple-output (MIMO) system which utilize multiple transmit/receive antennas can significantly increase the channel capacity, greatly improve the spectrum efficiency.
Combination of OFDM and MIMO techniques can take advantages of the merit of both techniques, keeps the robust performance in the frequency-selective fading channel by OFDM and enhance system capacity enormously by MIMO.
MIMO-OFDM technology relies on accurate channel state information (CSI) to be available at the receiver. Channel estimation is critical in the design of MIMO-OFDM systems for coherent detection and decoding. Therefore, this thesis has investigated the channel estimation techniques for MIMO-OFDM systems.
In chapter 1, the background and development of OFDM and MIMO technologies are introduced, as well as the channel estimation technology profile.
In chapter 2, the characteristics of mobile communication channel are discussed. Firstly the influence factors of signal strength are discussed, then the definition and classification are introduced.
In chapter 3, the OFDM, MIMO and MIMO-OFDM system are introduced, besides, the introduction of space-time coding in MIMO system is presented, and the significant parameters in OFDM systems are introduced.
In chapter 4, the channel estimation techniques for SISO-OFDM systems are investigated, mainly towards block-type, comb-type and spread-type pilots channel estimation, a survey of recent pilot assisted estimation algorithms is provided, including 4 pilot estimation algorithms and 6 interpolation algorithms. Besides, the influence to transmit performance by pilot-pattern is also studied.
In chapter 5, the channel estimation techniques for MIMO-OFDM systems are investigated. In the frequency-domain, the design of pilot-pattern is studied with computer simulation. In the time-domain, we provide and simulate a design of main-tap algorithm to simplify the estimators, and a design of optimal training symbols to optimize channel estimation performance. Then we propose a channel estimation scheme using both two algorithms discussed above adding decision feed back technology in time-domain. Consequently, based on the research results presented above and 802.16e WiMAX standard, the complete simulation and performance evaluation of MIMO-OFDM system channel estimation techniques are provided.
In last chapter, the conclusion of thesis is given, as well as the necessary future work.
将OFDM和MIMO技术相结合,可以兼具OFDM抗多径时延特性、抗频率选择性衰落以及高频谱利用率,和MIMO有效提高系统容量,显著提高网络覆盖范围和传输可靠性的优点。
在MIMO-OFDM系统中,通过接收端信道估计获得信道状态信息(CSI,Channel State Information),是正确恢复发送信号的必要环节,其准确性将直接影响系统整体性能。本文主要针对MIMO-OFDM系统中信道估计展开研究。
第一章介绍了OFDM、MIMO的技术背景与发展现状,及信道估计技术概况。
第二章介绍了无线信道的传播特性。首先介绍了无线信道传播中信号强度的影响因素,进而引出衰落信道的定义和分类。
第三章介绍了OFDM、MIMO及MIMO-OFDM系统,并简要介绍了MIMO系统空时编码技术及发展情况。最后对OFDM系统中的重要参数做了说明。
第四章研究SISO-OFDM系统中的信道估计技术。针对块状、梳状和散布状导频信道估计,重点研究了4种导频估计算法、6种内插算法以及导频图案对传输性能的影响。
第五章研究MIMO-OFDM系统中的信道估计技术。针对频域估计,研究了导频图案设计。针对时域估计,推导了主要抽头简化算法和利用最优训练序列优化估计性能,并提出判决反馈时域重要抽头改进算法。最后,基于前面研究结果,结合WiMAX802.16e协议,完整实现了MIMO-OFDM系统中的信道估计。
第六章总结了本文的工作,给出结论,对下一步工作进行了展望。
With the rapidly increase of wireless data and multimedia application in recent years, research on the next generation(4G) mobile communication has being widely and deeply developed. The 4G communication system is a wireless network with high spectrum efficiency and high rate in limited bandwidth, and it supports high bit rate data transmission for many services. With the parallel modulation, orthogonal frequency-division multiplexing (OFDM) can change a frequency selective fading channel to be several flat fading channels, thus improving the transmission efficiency tremendously. Multiple-input multiple-output (MIMO) system which utilize multiple transmit/receive antennas can significantly increase the channel capacity, greatly improve the spectrum efficiency.
Combination of OFDM and MIMO techniques can take advantages of the merit of both techniques, keeps the robust performance in the frequency-selective fading channel by OFDM and enhance system capacity enormously by MIMO.
MIMO-OFDM technology relies on accurate channel state information (CSI) to be available at the receiver. Channel estimation is critical in the design of MIMO-OFDM systems for coherent detection and decoding. Therefore, this thesis has investigated the channel estimation techniques for MIMO-OFDM systems.
In chapter 1, the background and development of OFDM and MIMO technologies are introduced, as well as the channel estimation technology profile.
In chapter 2, the characteristics of mobile communication channel are discussed. Firstly the influence factors of signal strength are discussed, then the definition and classification are introduced.
In chapter 3, the OFDM, MIMO and MIMO-OFDM system are introduced, besides, the introduction of space-time coding in MIMO system is presented, and the significant parameters in OFDM systems are introduced.
In chapter 4, the channel estimation techniques for SISO-OFDM systems are investigated, mainly towards block-type, comb-type and spread-type pilots channel estimation, a survey of recent pilot assisted estimation algorithms is provided, including 4 pilot estimation algorithms and 6 interpolation algorithms. Besides, the influence to transmit performance by pilot-pattern is also studied.
In chapter 5, the channel estimation techniques for MIMO-OFDM systems are investigated. In the frequency-domain, the design of pilot-pattern is studied with computer simulation. In the time-domain, we provide and simulate a design of main-tap algorithm to simplify the estimators, and a design of optimal training symbols to optimize channel estimation performance. Then we propose a channel estimation scheme using both two algorithms discussed above adding decision feed back technology in time-domain. Consequently, based on the research results presented above and 802.16e WiMAX standard, the complete simulation and performance evaluation of MIMO-OFDM system channel estimation techniques are provided.
In last chapter, the conclusion of thesis is given, as well as the necessary future work.
引文
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[4] Local and Metropolitan Area Networks-Part 16, Air Interface for Fixed Broadband Wireless Access Systems, IEEE Standard IEEE 802.16a.
[5] G. J. Foschini and M. J. Gans. On limits of wireless communications in a fading environment when using multiple antennas. Wireless Pers. Com vol.6, no.3, pp. 311-335, Mar. 1998.
[6] Chiurtu. N, Rimoldi. B, Telatar. E. On the capacity of multi-antenna Gaussian channels. Information Theory. Proceedings. IEEE Internatinal Symposium on 24-29 June, 2001 pp.53
[7] G J. Foschini, Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas, Bell Labs Technical Journal, 41～59,Aug 1996.
[8] S.Alamouti. a simple transmit diversity technique for wireless communications. IEEE J.Sel.Areas Commun, Vol.16, No.8, pp: 1451-1458, Oct 1998
[9] Tarokh. V, Jafarkhani. H, Calderbank. A. R. Space-time block codes from orthogonal designs. Information Theory, IEEE Transactions, vol.45, issue 5, pp. 1256-1267, July 1999
[10] Siavash M. Alamouti. A simple transmit diversity technique for wireless communications. IEEE J. Select. Areas Commun., vol. 16, pp.1451-1458, Aug.1998.
[11] Tarokh. V, Seshadri. N, Calderbank. A. R. Space-time codes for high data rate wireless communication: Performance criterion and code construction. Information Theory,IEEE Transaction,Vol.44,issue 2,pp.744-765,March 1998
[12]Wolniansky P.W,G.J.Foschini,G.D.Golden,R.A.Valenzuela.V-Blast:An Architecture for Realizing Very High Data Rates Over the Rich-Scattering Wireless Channel.1998 URSI ISSSE,98,Pisa,29 Sept,2 Oct.1998,pp.195-200.
[13]张海滨.正交频分复用的基本原理与关键技术.国防工业出版社.2006
[14]Feifei Gao,A.Nallanathan.Blind channel estimation for MIMO OFDM systems via nonredundant linear precoding.IEEE trans on signal processing 2007
[15]杨大成,移动传播环境,机械工业出版社,2003年8月
[16]K.Fazel,S.Kaiser.multi-cartier and spread spectrum systems.John Wiley &Sons,Ltd,2003
[17]Volker Kuhn.wireless communications over MIMO channels.John Wiley &Sons,Ltd.Sep.2006
[18]V.Tarokh,N.Seshadri,S.Calderbank.space-time codes for high data rate wireless communication:performance criterion and code construction.IEEE Trans.Inf.Theory,Vol.44,No.2,pp:744-765.Mar 1998
[19]Branka Vucetic,Jinhong Yuan.space-time coding.John Wiley,2003
[20]Sinem Coeri,Mustafa Ergen,Anuj Puri,Ahmad Bahai.Channel estimation techniques based on pilot arrangement in OFDM systems.IEEE trans on broadcasing,vol.48,no.3,Sep 2002
[21]Jan-Jaap van de Beek,Ove Edfors,Magnus Sandell,Sarah Kate Wilson,Per Ola Borjesson.On channel estimation in OFDM systems.IEEE 1995
[22]Edfors O,Sandell M,Van de Beek,J.J,Wilson,S.K,Borjesson,P.O.OFDM channel estimation by singular value decomposition.IEEE Trans.Commun,1998,46,pp.931-939
[23]赵冬,闫发军,王文博.OFDM系统中导频设置方式对信道估计算法性能的影响.中国无线电.2006年05期
[24]Xiaodai Dong,Wu-Sheng Lu,Anthony C.K.Soong.linear interpolation in pilot symbol assisted channel estimation for OFDM.IEEE transactions on wireless ommunications,Vol.6,No.5,May 2007
[25]Meng-Han Hsieh,Che-Ho Wei.Channel estimation for OFDM systems based on comb-type pilot arrangemengt in frequency selective fading channels.IEEE trans on consumer electronis,Vol.44,No.1,Feb 1998
[26]Jae Kyoung Moon,Song In Chol.Performance of channel estimation methods for ofdm systems in a multipath fading channels.IEEE trans on consumer electronics,vol.46,No.1,Feb 2000
[27]Einar Maeland.On the comparison of interpolation methods.IEEE trans on medical imaging,vol.7,No.3,Sep.1988
[28]Yuping Zhao,Aiping Huang.A novel channel estimation method for OFDM mobile communication systems based on pilot signals and transform-domain processing IEEE VIC97,1997,pp 2089-2094
[29]杨志刚,何丰.基于导频符号的OFDM信道估计技术研究.寒山师范学院学报.2006年03期
[30]Hoeher P,Kaiser S.Two-dimensional pilot-symbol-aided channel estimation by Wiener Filtering.In Proc.IEEE ICASSP'97,Munich,Germany,Apr.1997
[31]田永毅.OFDM系统中基于导频的二维信道估计.陕西科技大学学报.Jun.2006.Vol.24
[32]Changho Suh,Chan-Soo Hwang,Hokyu Choi.comparative study of time-domain and frequency-domain channel estimation in MIMO-OFDM systems.The 14th IEEE 2003
[33]Xiaolin Hou,Xueyuan Zhao,Changchuan Yin,Guangxin Yue.Unified view of channel estimation in MIMO-OFDM systems.IEEE 2005
[34]Dongxu Shen,Zhifeng Diao,Kai-Kit Wong,Victor O.K.Li.analysis of pilot-assisted channel estimators for OFDM systems with transmit diversity.IEEE trans on broadcasting,voi.52,No.2,June 2006
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