MIMO-OFDM无线通信系统中信道估计的研究
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摘要
随着无线通信技术的迅猛发展,当今人们对通信业务的需求不仅仅局限于语音业务上,对于图像、视频、数据、网络的需求也日益增长,这就对无信通信系统提出了更高的要求,高速率、大容量、高可靠性、多业务种类将是无线通信系统未来发展的趋势。MIMO-OFDM无线通信系统正好符合下一代通信系统的这类需求,而信道估计又是MIMO-OFDM无线通信系统中直接关系到通信质量的重要环节。
本文对MIMO (Multiple Input and Multiple Output,多输入多输出)和OFDM (Orthogonal Frequency Division Multiplexing,正交频分复用)技术进行了相关介绍,MIMO技术通过多天线分集实现了大容量的无线通信,而OFDM技术通过多载波并行传输,同时对各路子载波信号进行严格的正交化,降低了系统的频谱带宽需求,这对目前越来越紧缺的频谱资源来说无疑是一个较大的进步,在抵抗噪声和干扰、抑制信号多径造成的衰落方面也具有良好的效果,二者的结合构成了MIMO-OFDM无线通信系统。然后对无线信道的特性与模型进行了相关研究,对其中的多径时延、多普勒频移、瑞利衰落展开了相关的讨论,对无线信道的模型进行了理论分析。最后对MIMO-OFDM无线通信系统中基于导频的非盲信道估计进行了研究和讨论,对于导频的形式与结构进行了介绍,主要讨论了最小平方误差信道估计算法、最小均方误差信道估计算法、线性最小均方误差信道估计算法,通过Matlab仿真对比了它们各自的优缺点和性能,针对算法的复杂度与应用性能展开了相关分析。对于信道估计的内插、滤波进行了一定的改进,通过小波去噪、加窗函数处理等方式,一方面尽量去除噪声信号,另一方面集中有用信号的能量,将系统的性能进一步提升,降低了系统的误码率。通过仿真表明改进后的内插滤波效果随着信噪比的增加在不断提高,这对于优化MIMO-OFDM无线通信系统的接收性能有很大帮助。
对MIMO-OFDM无线通信系统信道估计的相关研究和仿真表明,MIMO-OFDM无线通信系统的信道估计是一个非常具有发展前景的研究领域。
With the rapid development of wireless communication technology, the demand for communication services is not limited in voice area. Images, video, data, network services are also on the growth. This requires advanced capability for wireless communication system. High-speed, large capacity, high reliability, multi-service types will be the main features of the future wireless communication system. At the same time, the MIMO-OFDM wireless communication system greatly meets the needs of the next generation communication system. The channel estimation for MIMO-OFDM wireless communication system is a significant part which is directly related to communication quality.
In this paper, we mainly introduced MIMO(Multiple Input and Multiple Output) and OFDM (Orthogonal Frequency Division Multiplexing) techniques. MIMO technique supplies high-capacity by multi-antennas, while OFDM technique generates multi-carrier signals by parallel transmission technology which is strictly orthogonal between each other. Through this, we weaken the needs for system's wide spectral bandwidth, which is undoubtedly a big improvement under the circumstance of the rare spectrum resources. In this way, we resisted the noise, interference, signal fading effect. The two techniques constitute MIMO-OFDM wireless communication system. Then we discussed the features of the wireless channel, analyzed the model of it, including multi-path delay, Doppler frequency shift and Rayleigh fading. Finally, we made the research on non-blind channel estimation in MIMO-OFDM wireless communication system based on pilot signal, introduced the form and structure of pilot signal, mainly discussed the least square error channel estimation algorithm, minimum mean-square error channel estimation algorithm, linear minimum mean-square error channel estimation algorithm, compared the performance of the three ways through Matlab computer simulation and analyzed the complexity of the algorithms and application performance. We improved the interpolation and filter way in the channel estimation process to remove the noise as much as possible and concentrate the energy of the useful signal through wavelet denoising and adding window function. And in this way we lower down the bit error rate of the system. The computer simulation results show the performance is better and better as the signal to noise ratio has improved. This way provides great help to the optimization of MIMO-OFDM wireless communication system.
The study and simulation of channel estimation in MIMO-OFDM wireless communication system indicates it is a very promising area.
本文对MIMO (Multiple Input and Multiple Output,多输入多输出)和OFDM (Orthogonal Frequency Division Multiplexing,正交频分复用)技术进行了相关介绍,MIMO技术通过多天线分集实现了大容量的无线通信,而OFDM技术通过多载波并行传输,同时对各路子载波信号进行严格的正交化,降低了系统的频谱带宽需求,这对目前越来越紧缺的频谱资源来说无疑是一个较大的进步,在抵抗噪声和干扰、抑制信号多径造成的衰落方面也具有良好的效果,二者的结合构成了MIMO-OFDM无线通信系统。然后对无线信道的特性与模型进行了相关研究,对其中的多径时延、多普勒频移、瑞利衰落展开了相关的讨论,对无线信道的模型进行了理论分析。最后对MIMO-OFDM无线通信系统中基于导频的非盲信道估计进行了研究和讨论,对于导频的形式与结构进行了介绍,主要讨论了最小平方误差信道估计算法、最小均方误差信道估计算法、线性最小均方误差信道估计算法,通过Matlab仿真对比了它们各自的优缺点和性能,针对算法的复杂度与应用性能展开了相关分析。对于信道估计的内插、滤波进行了一定的改进,通过小波去噪、加窗函数处理等方式,一方面尽量去除噪声信号,另一方面集中有用信号的能量,将系统的性能进一步提升,降低了系统的误码率。通过仿真表明改进后的内插滤波效果随着信噪比的增加在不断提高,这对于优化MIMO-OFDM无线通信系统的接收性能有很大帮助。
对MIMO-OFDM无线通信系统信道估计的相关研究和仿真表明,MIMO-OFDM无线通信系统的信道估计是一个非常具有发展前景的研究领域。
With the rapid development of wireless communication technology, the demand for communication services is not limited in voice area. Images, video, data, network services are also on the growth. This requires advanced capability for wireless communication system. High-speed, large capacity, high reliability, multi-service types will be the main features of the future wireless communication system. At the same time, the MIMO-OFDM wireless communication system greatly meets the needs of the next generation communication system. The channel estimation for MIMO-OFDM wireless communication system is a significant part which is directly related to communication quality.
In this paper, we mainly introduced MIMO(Multiple Input and Multiple Output) and OFDM (Orthogonal Frequency Division Multiplexing) techniques. MIMO technique supplies high-capacity by multi-antennas, while OFDM technique generates multi-carrier signals by parallel transmission technology which is strictly orthogonal between each other. Through this, we weaken the needs for system's wide spectral bandwidth, which is undoubtedly a big improvement under the circumstance of the rare spectrum resources. In this way, we resisted the noise, interference, signal fading effect. The two techniques constitute MIMO-OFDM wireless communication system. Then we discussed the features of the wireless channel, analyzed the model of it, including multi-path delay, Doppler frequency shift and Rayleigh fading. Finally, we made the research on non-blind channel estimation in MIMO-OFDM wireless communication system based on pilot signal, introduced the form and structure of pilot signal, mainly discussed the least square error channel estimation algorithm, minimum mean-square error channel estimation algorithm, linear minimum mean-square error channel estimation algorithm, compared the performance of the three ways through Matlab computer simulation and analyzed the complexity of the algorithms and application performance. We improved the interpolation and filter way in the channel estimation process to remove the noise as much as possible and concentrate the energy of the useful signal through wavelet denoising and adding window function. And in this way we lower down the bit error rate of the system. The computer simulation results show the performance is better and better as the signal to noise ratio has improved. This way provides great help to the optimization of MIMO-OFDM wireless communication system.
The study and simulation of channel estimation in MIMO-OFDM wireless communication system indicates it is a very promising area.
引文
[1]吴伟陵,牛凯.移动通信原理[M].电子工业出版社,2005
[2]佟学俭,罗淘.OFDM移动通信技术原理与应用[M].人民邮电出版社2003
[3]张士兵,张力军,徐晨.基于多带的超宽带通信系统[J].通信学报,2006,27(3)：79-85
[4]黄韬,袁超伟,杨睿哲,刘鸣.MIMO相关技术与应用[M].机械工业出版社,2006
[5]T.S Rappaport著,周文安等译.无线通信原理与应用[M].北京电子工业出版社,2006.
[6]王颖,孟嗣仪.MIMO-OFDM系统中的信道估计方法分析[J].中国数据通信,2005年第6期：122-125
[7]杨大成.移动传播环境：理论基础、分析方法和建模技术[M].机械工业出版社,2003.8
[8]周恩,张兴,吕召彪,孙宇昊.下一代宽带无线通信OFDM与MIMO技术[M].人民邮电出版社,2008
[9]王东明、高西奇、尤肖虎、韩冰.宽带MIMO-OFDM系统信道估计算法研究[J].电子学报,2005.7：1254-1257.
[10]王文博.宽带无线通信-OFDM技术[M].人民邮电出版社,2003
[11]瞿逢重,宋征卫,陈文正.一种改进的MIMO-OFDM帧同步和载波频估计方法[J].浙江大学学报(工学版),2005年2月,Vol.40,No.2:254-257
[12]樊昌信通信原理[M].国防工业出版社,2002
[13]William H.Trante等著,肖明波等译.通信系统仿真原理与无线应用[M].北京：电子工业出版社,2005.
[14]罗涛,乐光新.多天线无线通信原理与应用[M].北京邮电大学出版社,2005
[15]李建新、刘乃安、刘继平.现代通信系统分析与仿真[M].西电出版社,2000
[16]刘刚,郭漪,葛建华.MIMO-OFDM系统中的信道估计[J].华中科技大学学报(自然科学版)2005年9月Vol.33,No.9：26-29
[17]陈曦、刘学林、高焕英.广义逆矩阵在OFDM系统信道估计中的应用[J].无线电工程,2005,35(7)：1-6.
[18]谢显中等.基于TDD的第四代移动通信技术[M].电子工业出版社,2005
[19]周先军,胡修林,张蕴玉,王甲池.超宽带无线通信关键技术[J].电子技术应用,2005(10)：50-53
[20]罗任泽新一代无线移动通信系统关键技术[M].北京邮电大学出版社,2007
[21]王德胜、朱光喜、林宏志.MIMO-OFDM最优导频设置与优化的信道估计方法[J].通信学报,2005.1：34-39.
[22]杨志刚,何丰.基于导频符号的信道估计技术研究[J].寒山师范学院学报,2006年第3期
[23]董艳男、朱琦.基于802.16aMIMO-OFDM系统的信道估计方法研究[J].南京邮电学院学报,2006,25(2)：62-66
[24]李妍MATLAB通信仿真开发手册[M].国防工业出版社,2005
[25]张贤达、保铮.通信信号处理[M].国防工业出版社,2000
[26]周健多输入多输出天线OFDM系统的信道估计[J].南京邮电大学学报,2006,25(5)：11-16
[27]李承恕,赵荣黎.扩展频谱通信.[M].人民邮电出版社,1995
[28]Foschini G J, ChiZhik D, Gans M J. Analysis and Performance of some basic space-time architectures[J]. IEEE Journal on Selected Areas on Communications,2003,21(3):303-320
[29]Hua Zhang, Ye Li, Anthony Reid, and John Terry. Optimum Training Symbol Design for MIMO-OFDM in Correlated Fading Channels[J]. IEEE Trans,2006,50(3):2343-2347
[30]Michele Morelli, Umberto Mengali. A Comparison of Pilot-Aided Channel Estimation Methods for OFDM Systems[J]. IEEE Trans. Sig. Proc,2001,49(12):3065-3073.
[31]Wiesel A, Eldar Y C, Shamai S. Semi-definite relaxation for detection of 16 QAM signaling in MIMO channels[J].IEEE Signal Processing Letters,2005,12(9):653-656
[32]Giangaspero L, Agarossi L, Paltenghi G Co-channel interference cancellation based on MIMO-OFDM systems[J]. IEEE Wireless Communications,2002,9(6):8-17
[33]Jing Liang; Zhi Ding. FIR channel estimation through generalized cumulant slice weighting[J]. IEEE Transactions on Signal Processing, Vol.52,March 2004:657-667
[34]Christina Fragouli, Naofal AI-Dhahir and William Turin. Training-Based channel Estimation for Multiple-Antenna Broadband Transmissions[J]. IEEE Transactions On Wireless Communication, vol.2(2) 2003:21-50
[35]Y.R. ZHENG and C.S.XIAO. Improved models for the generation of multiple uncorrelated Rayleigh fading waveforms[J].IEEE Communications Letters.2002 vol.6,No.6:256-258
[36]Imad Barhumi, GeertLeus. Optimal Training Design for MIMO-OFDM Systems in Mobile Wireless Channels[J].IEEE Transaction on Signal Processing,2003,51(6):3-5
[37]K. Yu, B. Ottersten. Models for MIMO Propagation Channels-A Review[J]. Wiley Journal on Wireless Communications and Mobile Computing.2002,2(7):653～666
[38]H. Bolcskei, D. Gesbert, and A. J. Paulraj.On the capacity of OFDM-based spatial multiplexing systems[J]. IEEE Trans,2002.Feb On Commun 50(2):225-234
[39]J. K. Moon and S. I. Choi. Performance of channel estimation methods for OFDM systems in a multipath fading channels[J].IEEE Trans.Consumer Electronics, vol.46, Feb 2000:161-170
[40]S. L. Loyka. Channel capacity of MIMO architecture using the exponential correlation matrix[J]. IEEE Commun. Lett 2001,5(9):369-371
[41]Myeongchoel Shin,H.Lee and Chungyong Lee. Enhanced Channel Estimation Technique for MIMO-OFDM systems[J]. IEEE Transations on Vehicular Technology,2004,53 (1):261-265
[42]Simeone O, Bar-Ness Y, Spagnolini U. Pilot based channel estimation for OFDM systems by tracking the delay-subspace[J]. IEEE Transaction on Wireless Communications,2004,3(1): 315-325
[43]Sampath H.Talwar, Tellado J. A fourth-generation MIMO-OFDM broadband wireless system:Design,Performance,field trial results[J].IEEE Communication Magazine,2002,38(9): 143～149
[44]S. Loyka, A. Kouki. On MIMO Channel Capacity, Correlations, and Keyholes:Analysis of Degenerate Channels[J]. IEEE Trans. Commun.2002,50(12):1886～1888
[45]C.Komninakis, C.Fraggouli, A.H.Sayed, R.D.Wesel. Multi-input Multi-output fading channel tracking and equalization using Kalman estimation[J]. IEEE Transations on Signal Processing,2002,50(5):1065-1076
[46]Miller C L,Taylor D P.Gough P T. Estimation of co-channel signals with linear complexity[J]. IEEE Transactions on Communications,2001,49(11):1997-2005
[47]J.K.Cavers. An analysis of pilot symbol assisted modulation for Rayleign fading channels",IEEE Trans.Veh.Technol.,vol.40,No.4,1991:689-693
[48]L.Zheng, et al. Diversity and Multiplexing:A fundamental Tradeoff in Multiple-Antenna Channels[J]. IEEE Trans. On Inf. Theory, vol.49, No.5, May 2003:1073-1096
[49]Samardzija D, Mandayam N. Pilot-assisted estimation of MIMO fading channel response and achievable data rates[J]. IEEE Transaction on Signal Processing,2005,51(11):2882-2890
[2]佟学俭,罗淘.OFDM移动通信技术原理与应用[M].人民邮电出版社2003
[3]张士兵,张力军,徐晨.基于多带的超宽带通信系统[J].通信学报,2006,27(3)：79-85
[4]黄韬,袁超伟,杨睿哲,刘鸣.MIMO相关技术与应用[M].机械工业出版社,2006
[5]T.S Rappaport著,周文安等译.无线通信原理与应用[M].北京电子工业出版社,2006.
[6]王颖,孟嗣仪.MIMO-OFDM系统中的信道估计方法分析[J].中国数据通信,2005年第6期：122-125
[7]杨大成.移动传播环境：理论基础、分析方法和建模技术[M].机械工业出版社,2003.8
[8]周恩,张兴,吕召彪,孙宇昊.下一代宽带无线通信OFDM与MIMO技术[M].人民邮电出版社,2008
[9]王东明、高西奇、尤肖虎、韩冰.宽带MIMO-OFDM系统信道估计算法研究[J].电子学报,2005.7：1254-1257.
[10]王文博.宽带无线通信-OFDM技术[M].人民邮电出版社,2003
[11]瞿逢重,宋征卫,陈文正.一种改进的MIMO-OFDM帧同步和载波频估计方法[J].浙江大学学报(工学版),2005年2月,Vol.40,No.2:254-257
[12]樊昌信通信原理[M].国防工业出版社,2002
[13]William H.Trante等著,肖明波等译.通信系统仿真原理与无线应用[M].北京：电子工业出版社,2005.
[14]罗涛,乐光新.多天线无线通信原理与应用[M].北京邮电大学出版社,2005
[15]李建新、刘乃安、刘继平.现代通信系统分析与仿真[M].西电出版社,2000
[16]刘刚,郭漪,葛建华.MIMO-OFDM系统中的信道估计[J].华中科技大学学报(自然科学版)2005年9月Vol.33,No.9：26-29
[17]陈曦、刘学林、高焕英.广义逆矩阵在OFDM系统信道估计中的应用[J].无线电工程,2005,35(7)：1-6.
[18]谢显中等.基于TDD的第四代移动通信技术[M].电子工业出版社,2005
[19]周先军,胡修林,张蕴玉,王甲池.超宽带无线通信关键技术[J].电子技术应用,2005(10)：50-53
[20]罗任泽新一代无线移动通信系统关键技术[M].北京邮电大学出版社,2007
[21]王德胜、朱光喜、林宏志.MIMO-OFDM最优导频设置与优化的信道估计方法[J].通信学报,2005.1：34-39.
[22]杨志刚,何丰.基于导频符号的信道估计技术研究[J].寒山师范学院学报,2006年第3期
[23]董艳男、朱琦.基于802.16aMIMO-OFDM系统的信道估计方法研究[J].南京邮电学院学报,2006,25(2)：62-66
[24]李妍MATLAB通信仿真开发手册[M].国防工业出版社,2005
[25]张贤达、保铮.通信信号处理[M].国防工业出版社,2000
[26]周健多输入多输出天线OFDM系统的信道估计[J].南京邮电大学学报,2006,25(5)：11-16
[27]李承恕,赵荣黎.扩展频谱通信.[M].人民邮电出版社,1995
[28]Foschini G J, ChiZhik D, Gans M J. Analysis and Performance of some basic space-time architectures[J]. IEEE Journal on Selected Areas on Communications,2003,21(3):303-320
[29]Hua Zhang, Ye Li, Anthony Reid, and John Terry. Optimum Training Symbol Design for MIMO-OFDM in Correlated Fading Channels[J]. IEEE Trans,2006,50(3):2343-2347
[30]Michele Morelli, Umberto Mengali. A Comparison of Pilot-Aided Channel Estimation Methods for OFDM Systems[J]. IEEE Trans. Sig. Proc,2001,49(12):3065-3073.
[31]Wiesel A, Eldar Y C, Shamai S. Semi-definite relaxation for detection of 16 QAM signaling in MIMO channels[J].IEEE Signal Processing Letters,2005,12(9):653-656
[32]Giangaspero L, Agarossi L, Paltenghi G Co-channel interference cancellation based on MIMO-OFDM systems[J]. IEEE Wireless Communications,2002,9(6):8-17
[33]Jing Liang; Zhi Ding. FIR channel estimation through generalized cumulant slice weighting[J]. IEEE Transactions on Signal Processing, Vol.52,March 2004:657-667
[34]Christina Fragouli, Naofal AI-Dhahir and William Turin. Training-Based channel Estimation for Multiple-Antenna Broadband Transmissions[J]. IEEE Transactions On Wireless Communication, vol.2(2) 2003:21-50
[35]Y.R. ZHENG and C.S.XIAO. Improved models for the generation of multiple uncorrelated Rayleigh fading waveforms[J].IEEE Communications Letters.2002 vol.6,No.6:256-258
[36]Imad Barhumi, GeertLeus. Optimal Training Design for MIMO-OFDM Systems in Mobile Wireless Channels[J].IEEE Transaction on Signal Processing,2003,51(6):3-5
[37]K. Yu, B. Ottersten. Models for MIMO Propagation Channels-A Review[J]. Wiley Journal on Wireless Communications and Mobile Computing.2002,2(7):653～666
[38]H. Bolcskei, D. Gesbert, and A. J. Paulraj.On the capacity of OFDM-based spatial multiplexing systems[J]. IEEE Trans,2002.Feb On Commun 50(2):225-234
[39]J. K. Moon and S. I. Choi. Performance of channel estimation methods for OFDM systems in a multipath fading channels[J].IEEE Trans.Consumer Electronics, vol.46, Feb 2000:161-170
[40]S. L. Loyka. Channel capacity of MIMO architecture using the exponential correlation matrix[J]. IEEE Commun. Lett 2001,5(9):369-371
[41]Myeongchoel Shin,H.Lee and Chungyong Lee. Enhanced Channel Estimation Technique for MIMO-OFDM systems[J]. IEEE Transations on Vehicular Technology,2004,53 (1):261-265
[42]Simeone O, Bar-Ness Y, Spagnolini U. Pilot based channel estimation for OFDM systems by tracking the delay-subspace[J]. IEEE Transaction on Wireless Communications,2004,3(1): 315-325
[43]Sampath H.Talwar, Tellado J. A fourth-generation MIMO-OFDM broadband wireless system:Design,Performance,field trial results[J].IEEE Communication Magazine,2002,38(9): 143～149
[44]S. Loyka, A. Kouki. On MIMO Channel Capacity, Correlations, and Keyholes:Analysis of Degenerate Channels[J]. IEEE Trans. Commun.2002,50(12):1886～1888
[45]C.Komninakis, C.Fraggouli, A.H.Sayed, R.D.Wesel. Multi-input Multi-output fading channel tracking and equalization using Kalman estimation[J]. IEEE Transations on Signal Processing,2002,50(5):1065-1076
[46]Miller C L,Taylor D P.Gough P T. Estimation of co-channel signals with linear complexity[J]. IEEE Transactions on Communications,2001,49(11):1997-2005
[47]J.K.Cavers. An analysis of pilot symbol assisted modulation for Rayleign fading channels",IEEE Trans.Veh.Technol.,vol.40,No.4,1991:689-693
[48]L.Zheng, et al. Diversity and Multiplexing:A fundamental Tradeoff in Multiple-Antenna Channels[J]. IEEE Trans. On Inf. Theory, vol.49, No.5, May 2003:1073-1096
[49]Samardzija D, Mandayam N. Pilot-assisted estimation of MIMO fading channel response and achievable data rates[J]. IEEE Transaction on Signal Processing,2005,51(11):2882-2890