基于导频的OFDM系统信道估计
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摘要
由于宽带移动通信系统的无线信道的频率选择性和时变特性,OFDM信号需要在解调前进行必要的信道估计,补偿由于无线信道由于多径效应和多普勒效应引起的信道衰落,从而提高系统的误码性能。
OFDM系统的信道估计主要用来对抗无线传输中的小尺度衰落,因此在OFDM系统性能研究中,信道模型的建立对信道估计的性能至关重要。在无线信道模型中,经典的Clarke冲激响应模型被业界广泛采用,它可以产生相关的瑞利或莱斯衰落；同时ITU通过大量的测试,提出了IMT2000在不同移动环境下的多径模型,如PA、PB、VA等多径衰落模型。同时移动速度所产生的多普勒频移是信道模型的另外一个重要指标。本文构建了PA多径和速度为120km/h、PB多径和速度为3km/h的信道模型研究信道估计的系统性能。
在单天线系统(SISO)条件下,OFDM系统的衰落信道可看作为二维信号：时域和频域。通常OFDM系统采用的估计器是一维信道估计器,即先进行一维(频域)的估计,然后再进行另一维(时域)的估计,以获得二维的信道估计。高速的数据速率和低的误码要求迫使信道估计器兼有低的复杂度和较高的准确性。目前单天线系统(SISO) OFDM系统信道估计的算法有很多种,如线性插值、二阶插值、低通插值、最大似然估计、最小二乘估计、最小均方误差估计等。
MIMO多天线技术由于其大幅度的提高系统的频谱效率而被业界推崇。相比SISO信道系统,信道估计由于空间的多种信道路径可看作三维信号,同时对信道估计的准确度要求更高。目前关于MIMO系统的信道估计的方法主要分为三大类：线性估计,如最小二乘法(LS)、最小均方误差法(MMSE);非线性估计,如最大似然法(ML)；线性自适应估计,如最小均方法(LMS)、递归最小二乘法(RLS)。
本论文设计了OFDM系统的仿真平台,并建立了Clarke经典信道衰落模型和ITU关于IMT2000的多径衰落模型,同时研究、仿真并验证了该模型的相关特性,如时域相关函数、频域相关函数等。分析和仿真了UMB系统基于SISO信道的线性插值及最小均方误差的系统误码性能,在此基础上提出了改进的信道估计,即利用正确解调的数据信号对信道进行重新估计,从而达到更好的系统误码性能；同时研究和仿真了UMB系统基于MMO信道的线性信道估计,即最小二乘法(LS)、最小均方误差法(MMSE),并对串行干扰消除接收检测进行了研究。最后利用上述方法对UMB系统的信道估计性能进行了仿真,提出了不同信道环境下,最适合的信道估计方法。
Due to inherent frequency selective and time variant channel of broadband mobile communication system, it is essential to employ necessary channel estimation to improve system BER performance to combat multi-path and Doppler effects.
It is important to setup a rational channel model for an OFDM system channel estimation performance evaluation. So far, classic channel model for wireless communication, i.e., Clarke channel model, is one of the most popular accepted channel models applied for simulation of channel fading response. Meanwhile, ITU has developed a multi-path power delay profile for IMT2000 under different wireless conditions, such as pedestrian A and B, vehicle A.
Types of channel estimation for OFDM system can be divided into two main groups:parameters based and non-parameters based. The former asks for real time estimation on path time delay and fading amplitude, which are difficult to be converged over time variance and causes it difficult to be employed in reality; while the later is mostly based on pilot inserted on sub-carriers for channel estimation using different algorithms for different wireless condition and is very common for OFDM system.
OFDM technique makes use of time-space and frequency-space at the same time, so that channel estimation can be conducted in two dimensions. However, the calculation complexity of two-dimensional estimation makes its difficult to be use in reality, which causes two one-dimensional applied in time-space first and then frequency-space, or vice versa. In general, there are two types of pilot based channel estimation for OFDM systems, i.e., interpolation and filter methodologies. The dissertation focuses on pilot based channel estimation analysis and simulation for UMB system with different pilot spacing in frequency space under different time spreading and frequency spreading channel environments. While in time space, linear interpolation of channel estimation is used. Finally, the simulation results and recommendations of channel estimation are proposed under different channel environments.
OFDM系统的信道估计主要用来对抗无线传输中的小尺度衰落,因此在OFDM系统性能研究中,信道模型的建立对信道估计的性能至关重要。在无线信道模型中,经典的Clarke冲激响应模型被业界广泛采用,它可以产生相关的瑞利或莱斯衰落；同时ITU通过大量的测试,提出了IMT2000在不同移动环境下的多径模型,如PA、PB、VA等多径衰落模型。同时移动速度所产生的多普勒频移是信道模型的另外一个重要指标。本文构建了PA多径和速度为120km/h、PB多径和速度为3km/h的信道模型研究信道估计的系统性能。
在单天线系统(SISO)条件下,OFDM系统的衰落信道可看作为二维信号：时域和频域。通常OFDM系统采用的估计器是一维信道估计器,即先进行一维(频域)的估计,然后再进行另一维(时域)的估计,以获得二维的信道估计。高速的数据速率和低的误码要求迫使信道估计器兼有低的复杂度和较高的准确性。目前单天线系统(SISO) OFDM系统信道估计的算法有很多种,如线性插值、二阶插值、低通插值、最大似然估计、最小二乘估计、最小均方误差估计等。
MIMO多天线技术由于其大幅度的提高系统的频谱效率而被业界推崇。相比SISO信道系统,信道估计由于空间的多种信道路径可看作三维信号,同时对信道估计的准确度要求更高。目前关于MIMO系统的信道估计的方法主要分为三大类：线性估计,如最小二乘法(LS)、最小均方误差法(MMSE);非线性估计,如最大似然法(ML)；线性自适应估计,如最小均方法(LMS)、递归最小二乘法(RLS)。
本论文设计了OFDM系统的仿真平台,并建立了Clarke经典信道衰落模型和ITU关于IMT2000的多径衰落模型,同时研究、仿真并验证了该模型的相关特性,如时域相关函数、频域相关函数等。分析和仿真了UMB系统基于SISO信道的线性插值及最小均方误差的系统误码性能,在此基础上提出了改进的信道估计,即利用正确解调的数据信号对信道进行重新估计,从而达到更好的系统误码性能；同时研究和仿真了UMB系统基于MMO信道的线性信道估计,即最小二乘法(LS)、最小均方误差法(MMSE),并对串行干扰消除接收检测进行了研究。最后利用上述方法对UMB系统的信道估计性能进行了仿真,提出了不同信道环境下,最适合的信道估计方法。
Due to inherent frequency selective and time variant channel of broadband mobile communication system, it is essential to employ necessary channel estimation to improve system BER performance to combat multi-path and Doppler effects.
It is important to setup a rational channel model for an OFDM system channel estimation performance evaluation. So far, classic channel model for wireless communication, i.e., Clarke channel model, is one of the most popular accepted channel models applied for simulation of channel fading response. Meanwhile, ITU has developed a multi-path power delay profile for IMT2000 under different wireless conditions, such as pedestrian A and B, vehicle A.
Types of channel estimation for OFDM system can be divided into two main groups:parameters based and non-parameters based. The former asks for real time estimation on path time delay and fading amplitude, which are difficult to be converged over time variance and causes it difficult to be employed in reality; while the later is mostly based on pilot inserted on sub-carriers for channel estimation using different algorithms for different wireless condition and is very common for OFDM system.
OFDM technique makes use of time-space and frequency-space at the same time, so that channel estimation can be conducted in two dimensions. However, the calculation complexity of two-dimensional estimation makes its difficult to be use in reality, which causes two one-dimensional applied in time-space first and then frequency-space, or vice versa. In general, there are two types of pilot based channel estimation for OFDM systems, i.e., interpolation and filter methodologies. The dissertation focuses on pilot based channel estimation analysis and simulation for UMB system with different pilot spacing in frequency space under different time spreading and frequency spreading channel environments. While in time space, linear interpolation of channel estimation is used. Finally, the simulation results and recommendations of channel estimation are proposed under different channel environments.
引文
[1]Andrea Goldsmith "Wireless Communications" Cambridge University Press (2005).
[2]Dimitris Manolakis at al., "Statistical and Adaptive Signal Processing" The McGraw-Hill Companies, Inc. (2000).
[3]Tranter William H at al., "Principles Of Communication Systems Simulation With Wireless Applications" Pearson Education, Inc. (2004).
[4]Gordan L. Stuber, "Principles of Mobile Communications",2nd Edition, Kluwer Academic Publishers,2001.
[5]John G. Proaksis, "Digital Communications",4th Edition, McGraw-Hill, 2001.
[6]Richard van Nee at al., "OFDM for wireless multimedia communications" Artech House universal personal communications library (2000).
[7]Ramjee Prasad "OFDM for wireless communications systems" Artech House universal personal communications library (2004)
[8]C.S0084-001-0, Physical Layer for Ultra Mobile Broadband (UMB) Air Interface 9 Specification
[9]Van de Beek, J.-J., Edfors, O. S., Sandell, M., Wilson, S. K., and Borjesson, O. P., "On channel estimation in OFDM systems," 45th IEEE Vehicular Technology Conference, Chicago, Ⅱ., vol.2, pp.815-819, July 1995.
[10]Edfors, O., Sandell, M., Van de Beek, J.-J., and Wilson, S. K.,
"OFDM Channel Estimation by Singular Value Decomposition," IEEE Transactions on Communications, vol.46, pp.931-939, July 1998.
[11]Strobach, P., "Low-Rank Adaptive Filters," IEEE Transactions on Signal Processing, vol.44, pp.2932-2947. Dec.1996.
[12]Coleri, S., Ergen, M., Puri, A., and Bahai, A., "Channel Estimation Techniques Based on Pilot Arrangement in OFDM Systems," IEEE Transactions on Broadcasting, vol.48, pp.223-229, Sept.2002.
[13]Wu, J., and Wu, W., "A Comparative Study of Robust Channel Estimators for OFDM Systems," Proceedings of ICCT, pp.1932-1935,2003.
[14]Yang, B., Letaief, K. B., Cheng, R. S., and Cao, Z., "Channel Estimation for OFDM Transmission in Multipath Fading channels Based on Parametric Channel Modeling," IEEE Transactions on Communications, vol. 49, pp.467-479, March 2001.
[15]Ottersten, B., Viberg, M., and Kailath, T., "Performance Analysis of the Total Least Squares ESPRIT Algorithm," IEEE Transactions on Signal Processing, vol.39, pp.1122-1135, May 1991.
[16]Hou, X., Li, S., Liu, D., Yin, C., and Yue, G., "On Two-dimensional Adaptive Channel Estimation in OFDM Systems," 60th IEEE Vehicular Technology Conference, Los Angeles, Ca., vol.1, pp.498-502, Sept.2004.
[17]Sanzi, F., Sven, J., and Speidel, J., "A Comparative Study of Iterative
Channel Estimators for Mobile OFDM Systems," IEEE Transactions on Wireless Communications, vol.2, pp.849-859, Sept.2003.
[18]Li, Y., "Simplified Channel Estimation for OFDM Systems with Multiple Transmit Antennas," IEEE Transactions on Communications, vol.1, pp.67-75, January 2002.
[19]Auer, G., "Channel Estimation in Two Dimensions for OFDM Systems with Multiple Transmit Antennas," GLOBECOM, pp.322-326,2003.
[20]Sinem Coleri, et al., "Channel Estimation Techniques Based on Pilot Arrangement in OFDM Systems", IEEE Transactions on Broadcasting, Vol.48, No.3, Page(s):223-229, September 2002.
[21]Meng-Han Hsieh and Che-Ho Wei, "Channel Estimation for OFDM Systems Based on Comb-Type Pilot Arrangement in Frequency Selective Fading Channels", IEEE Transactions on Consumer Electronics, Vol.44, No.1, Page(s):217-225, February 1998.
[22]M. Speth, et al., "Optimum Receiver Design for OFDM-based Broad-band Transmission-Part Ⅱ:A Case Study", IEEE Transactions on Communications, Vol 49, No.4, Page(s):571-578, April 2001.
[23]Jae Kyoung and Song In Chol, "Performance of Channel Estimation Methods For OFDM Systems in a Multipath Fading Channels", IEEE Transactions on Consumer Electronics, Volume 46, Issue 1, Feb 2000 Page(s):161-170
[24]Bjarne Kjaer Ersboll, Knut Conradsen "An Introduction to Statistics Vol.2", Lecture Notes, IMM, DTU,2005.
[25]Ming-Xian Chang and Yu. T. Su "Model-Based Channel Estimation for OFDM Signals in Rayleigh Fading", IEEE Transactions on Communications, Vol.50, No.4, April 2002, Page(s):540-544.
[26]Ming-Xian Chang and Yu. T. Su "2D Regression Channel Estimation for Equalizing OFDM Signals", IEEE Vehicular Technology Conference Proceedings,2000. VTC 2000-Spring Tokyo, Vol.1, Page(s):240-244
[27]Xiaowen Wang and K.J. Ray Liu "An Adaptive Channel Estimation Algorithm Using Time-Frequency Polynomial for OFDM with Fading Multipath Channels", EURASIP Journal on Applied Signal Processing, August 2002, Page(s):818-830
[28]Haiyun Tang, Kam Y. Lau and Robert W. Brodersen, "Interpolation-Based Maximum Likelihood Channel Estimation Using OFDM Pilot Symbols", IEEE Global Telecommunications Conference, November 2002. GLOBECOM'02, Vol.2, Page(s):1860-1864.
[29]Magnus Sandell and Over Edfors "A comparative study of pilot-based channel estimators for wireless OFDM", Research Report, Lulea University of Technology, Sweden, September 1996
[30]Over Edfors et al., "Analysis of DFT-Based Channel Estimators for OFDM", Wireless Personal Communications, Page(s):55-70, Kluwer Academic Publishers,2000
[31]Michele Morelli and Umberto Mengali, "A Comparison of Pilot-Aided Channel Estimation Methods for OFDM Systems", IEEE Transactions on Signal Processing, Vol.49, Issue 2, December 2001, Page(s):3065-3073
[32]F. Shu, J. Lee, N. Wu and G.L. Zhao, "Time-Frequency Channel Estimating for Digital Amplitude Modulation Broadcasting Systems based on OFDM", IEEE Proceedings on Communications, Vol.150, Issue 4, August 2003, Page(s):259-264
[33]I. Barhumi, G. Leus, and M. Moonen, "Optimal training design for MIMO OFDM systems in mobile wireless channels," IEEE Trans. Signal Process., vol.51, no.6, pp.1615-1624, Jun.2003.
[34]M. Biguesh and A. B. Gershman, "Training based MIMO channel estimation:A study of estimator tradeoffs and optimal training signals," IEEE Trans. Signal Process., vol.54, no.3, pp.884-893, Mar.2006.
[35]Michael Mao Wang,, Sandip Sarkar, Tamer Kadous, Multi-Antenna Techniques in Ultra Mobile Broadband Communication Systems, Communication Networks and Services Research Conference,2008. CNSR 2008.6th Annual 5-8 May 2008 Page(s):397-403
[36]Sandip Sarkar, Tamer Kadous, Tingfang Ji, MIMO in Wireless WAN-the UMB System, Communication Systems Software and Middleware and Workshops,2008. COMSWARE 2008.3rd International Conference,6-10 Jan.2008 Page(s):57-64
[37]Jingming-Wang; Daneshrad, B., A comparative study of MIMO detection algorithms for wideband spatial multiplexing systems, Wireless Communications and Networking Conference,2005 IEEE, Volume 1,13-17 March 2005 Page(s):408-413 Vol.1
[2]Dimitris Manolakis at al., "Statistical and Adaptive Signal Processing" The McGraw-Hill Companies, Inc. (2000).
[3]Tranter William H at al., "Principles Of Communication Systems Simulation With Wireless Applications" Pearson Education, Inc. (2004).
[4]Gordan L. Stuber, "Principles of Mobile Communications",2nd Edition, Kluwer Academic Publishers,2001.
[5]John G. Proaksis, "Digital Communications",4th Edition, McGraw-Hill, 2001.
[6]Richard van Nee at al., "OFDM for wireless multimedia communications" Artech House universal personal communications library (2000).
[7]Ramjee Prasad "OFDM for wireless communications systems" Artech House universal personal communications library (2004)
[8]C.S0084-001-0, Physical Layer for Ultra Mobile Broadband (UMB) Air Interface 9 Specification
[9]Van de Beek, J.-J., Edfors, O. S., Sandell, M., Wilson, S. K., and Borjesson, O. P., "On channel estimation in OFDM systems," 45th IEEE Vehicular Technology Conference, Chicago, Ⅱ., vol.2, pp.815-819, July 1995.
[10]Edfors, O., Sandell, M., Van de Beek, J.-J., and Wilson, S. K.,
"OFDM Channel Estimation by Singular Value Decomposition," IEEE Transactions on Communications, vol.46, pp.931-939, July 1998.
[11]Strobach, P., "Low-Rank Adaptive Filters," IEEE Transactions on Signal Processing, vol.44, pp.2932-2947. Dec.1996.
[12]Coleri, S., Ergen, M., Puri, A., and Bahai, A., "Channel Estimation Techniques Based on Pilot Arrangement in OFDM Systems," IEEE Transactions on Broadcasting, vol.48, pp.223-229, Sept.2002.
[13]Wu, J., and Wu, W., "A Comparative Study of Robust Channel Estimators for OFDM Systems," Proceedings of ICCT, pp.1932-1935,2003.
[14]Yang, B., Letaief, K. B., Cheng, R. S., and Cao, Z., "Channel Estimation for OFDM Transmission in Multipath Fading channels Based on Parametric Channel Modeling," IEEE Transactions on Communications, vol. 49, pp.467-479, March 2001.
[15]Ottersten, B., Viberg, M., and Kailath, T., "Performance Analysis of the Total Least Squares ESPRIT Algorithm," IEEE Transactions on Signal Processing, vol.39, pp.1122-1135, May 1991.
[16]Hou, X., Li, S., Liu, D., Yin, C., and Yue, G., "On Two-dimensional Adaptive Channel Estimation in OFDM Systems," 60th IEEE Vehicular Technology Conference, Los Angeles, Ca., vol.1, pp.498-502, Sept.2004.
[17]Sanzi, F., Sven, J., and Speidel, J., "A Comparative Study of Iterative
Channel Estimators for Mobile OFDM Systems," IEEE Transactions on Wireless Communications, vol.2, pp.849-859, Sept.2003.
[18]Li, Y., "Simplified Channel Estimation for OFDM Systems with Multiple Transmit Antennas," IEEE Transactions on Communications, vol.1, pp.67-75, January 2002.
[19]Auer, G., "Channel Estimation in Two Dimensions for OFDM Systems with Multiple Transmit Antennas," GLOBECOM, pp.322-326,2003.
[20]Sinem Coleri, et al., "Channel Estimation Techniques Based on Pilot Arrangement in OFDM Systems", IEEE Transactions on Broadcasting, Vol.48, No.3, Page(s):223-229, September 2002.
[21]Meng-Han Hsieh and Che-Ho Wei, "Channel Estimation for OFDM Systems Based on Comb-Type Pilot Arrangement in Frequency Selective Fading Channels", IEEE Transactions on Consumer Electronics, Vol.44, No.1, Page(s):217-225, February 1998.
[22]M. Speth, et al., "Optimum Receiver Design for OFDM-based Broad-band Transmission-Part Ⅱ:A Case Study", IEEE Transactions on Communications, Vol 49, No.4, Page(s):571-578, April 2001.
[23]Jae Kyoung and Song In Chol, "Performance of Channel Estimation Methods For OFDM Systems in a Multipath Fading Channels", IEEE Transactions on Consumer Electronics, Volume 46, Issue 1, Feb 2000 Page(s):161-170
[24]Bjarne Kjaer Ersboll, Knut Conradsen "An Introduction to Statistics Vol.2", Lecture Notes, IMM, DTU,2005.
[25]Ming-Xian Chang and Yu. T. Su "Model-Based Channel Estimation for OFDM Signals in Rayleigh Fading", IEEE Transactions on Communications, Vol.50, No.4, April 2002, Page(s):540-544.
[26]Ming-Xian Chang and Yu. T. Su "2D Regression Channel Estimation for Equalizing OFDM Signals", IEEE Vehicular Technology Conference Proceedings,2000. VTC 2000-Spring Tokyo, Vol.1, Page(s):240-244
[27]Xiaowen Wang and K.J. Ray Liu "An Adaptive Channel Estimation Algorithm Using Time-Frequency Polynomial for OFDM with Fading Multipath Channels", EURASIP Journal on Applied Signal Processing, August 2002, Page(s):818-830
[28]Haiyun Tang, Kam Y. Lau and Robert W. Brodersen, "Interpolation-Based Maximum Likelihood Channel Estimation Using OFDM Pilot Symbols", IEEE Global Telecommunications Conference, November 2002. GLOBECOM'02, Vol.2, Page(s):1860-1864.
[29]Magnus Sandell and Over Edfors "A comparative study of pilot-based channel estimators for wireless OFDM", Research Report, Lulea University of Technology, Sweden, September 1996
[30]Over Edfors et al., "Analysis of DFT-Based Channel Estimators for OFDM", Wireless Personal Communications, Page(s):55-70, Kluwer Academic Publishers,2000
[31]Michele Morelli and Umberto Mengali, "A Comparison of Pilot-Aided Channel Estimation Methods for OFDM Systems", IEEE Transactions on Signal Processing, Vol.49, Issue 2, December 2001, Page(s):3065-3073
[32]F. Shu, J. Lee, N. Wu and G.L. Zhao, "Time-Frequency Channel Estimating for Digital Amplitude Modulation Broadcasting Systems based on OFDM", IEEE Proceedings on Communications, Vol.150, Issue 4, August 2003, Page(s):259-264
[33]I. Barhumi, G. Leus, and M. Moonen, "Optimal training design for MIMO OFDM systems in mobile wireless channels," IEEE Trans. Signal Process., vol.51, no.6, pp.1615-1624, Jun.2003.
[34]M. Biguesh and A. B. Gershman, "Training based MIMO channel estimation:A study of estimator tradeoffs and optimal training signals," IEEE Trans. Signal Process., vol.54, no.3, pp.884-893, Mar.2006.
[35]Michael Mao Wang,, Sandip Sarkar, Tamer Kadous, Multi-Antenna Techniques in Ultra Mobile Broadband Communication Systems, Communication Networks and Services Research Conference,2008. CNSR 2008.6th Annual 5-8 May 2008 Page(s):397-403
[36]Sandip Sarkar, Tamer Kadous, Tingfang Ji, MIMO in Wireless WAN-the UMB System, Communication Systems Software and Middleware and Workshops,2008. COMSWARE 2008.3rd International Conference,6-10 Jan.2008 Page(s):57-64
[37]Jingming-Wang; Daneshrad, B., A comparative study of MIMO detection algorithms for wideband spatial multiplexing systems, Wireless Communications and Networking Conference,2005 IEEE, Volume 1,13-17 March 2005 Page(s):408-413 Vol.1