基于信道预测的时变TDD-MIMO信道互易性补偿方法
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摘要
MIMO技术在提高无线通信系统容量和可靠性上具有的巨大优势,使其成为未来移动通信普遍采用的技术之一。采用时分双工(TDD)的MIMO系统可以利用上下行信道的互易性,使得基站能够直接根据估计得到的上行信道状态信息进行下行发端预处理,而不需要额外的反馈开销。但是信道的时变特性将导致信道互易性的损失,使TDD系统的优势无法发挥。
论文分析了信道时变对TDD-MIMO通信系统信道互易性的影响,在此基础上提出了相应的补偿方法。本文主要内容如下:
1.分析了时变空间信道模型NE-3GPP SCM(newly extended-3GPP spatial channel model),及TDD系统的帧结构,并在此基础上通过仿真讨论了时变信道的特性;
2.基于奇异值分解(SVD)方法,分别推导了信道时不变和信道时变情况下的系统容量公式,并进行了仿真验证,仿真结果表明,采用预编码方式时,信道时变严重影响了系统误码率和容量性能,信道互易性损失;
3.为了补偿时变信道引起的信道互易性的损失,给出了基于信道预测的补偿方法,仿真结果表明,该方法能够补偿信道时变造成的TDD-MIMO信道互易性的损失,有效提高TDD-MIMO误码率性能和容量。
With an enormous advantage of achieving high system capacity, MIMO technique has been one of the widely used techniques in future wireless communication systems. By using channel reciprocity in time division duplex(TDD) MIMO systems, the base station(BS) can preprocess transmitting data according to the channel state information (CSI) obtained by uplink measurement without additional feedback overhead. But time-varying channel leads to the loss of channel reciprocity, which will invalidate the advantage of TDD systems.
This thesis analyzes the impact of time-varying channel on channel reciprocity in TDD-MIMO communication systems. And then method compensating channel reciprocity is proposed. The main contributions are as follows:
1. The time-varying channel model NE-3GPP SCM (newly extended-3GPP spatial channel model) and the frame structure applicable to TDD systems are discussed, and the characteristics of time-varying channel are analyzed.
2. According to the SVD-based systems, the capacities over time-invariant channel and time-varying channel are derived respectively. Simulation results show that the bit error rate(BER) performance and system capacity are severely degraded over time-varying channel,the channel reciprocity is destroyed.
3. A compensation method is given to compensate the loss of channel reciprocity due to time-varying channel. Simulation results show that, using channel prediction in BS can significantly improves the BER performance and the system capacity. Thus, the channel reciprocity is compensated effectively.
论文分析了信道时变对TDD-MIMO通信系统信道互易性的影响,在此基础上提出了相应的补偿方法。本文主要内容如下:
1.分析了时变空间信道模型NE-3GPP SCM(newly extended-3GPP spatial channel model),及TDD系统的帧结构,并在此基础上通过仿真讨论了时变信道的特性;
2.基于奇异值分解(SVD)方法,分别推导了信道时不变和信道时变情况下的系统容量公式,并进行了仿真验证,仿真结果表明,采用预编码方式时,信道时变严重影响了系统误码率和容量性能,信道互易性损失;
3.为了补偿时变信道引起的信道互易性的损失,给出了基于信道预测的补偿方法,仿真结果表明,该方法能够补偿信道时变造成的TDD-MIMO信道互易性的损失,有效提高TDD-MIMO误码率性能和容量。
With an enormous advantage of achieving high system capacity, MIMO technique has been one of the widely used techniques in future wireless communication systems. By using channel reciprocity in time division duplex(TDD) MIMO systems, the base station(BS) can preprocess transmitting data according to the channel state information (CSI) obtained by uplink measurement without additional feedback overhead. But time-varying channel leads to the loss of channel reciprocity, which will invalidate the advantage of TDD systems.
This thesis analyzes the impact of time-varying channel on channel reciprocity in TDD-MIMO communication systems. And then method compensating channel reciprocity is proposed. The main contributions are as follows:
1. The time-varying channel model NE-3GPP SCM (newly extended-3GPP spatial channel model) and the frame structure applicable to TDD systems are discussed, and the characteristics of time-varying channel are analyzed.
2. According to the SVD-based systems, the capacities over time-invariant channel and time-varying channel are derived respectively. Simulation results show that the bit error rate(BER) performance and system capacity are severely degraded over time-varying channel,the channel reciprocity is destroyed.
3. A compensation method is given to compensate the loss of channel reciprocity due to time-varying channel. Simulation results show that, using channel prediction in BS can significantly improves the BER performance and the system capacity. Thus, the channel reciprocity is compensated effectively.
引文
[1]. ITU-R M.1645. Framework and over all objectives of the future development of IMT-2000 and systems beyond IMT-2000[EB/OL]. http:// www. itu.int/rec/ R-REC-M . 1645/e.
[2]. ITU-RIMT-ADV/2-E, Submission and evaluation process and consensus building,(2008-08-07). http:// www.itu.int/md/R07-IMT.ADV-C-0002/en.
[3].孙韶辉,王映民. TD-SCDMA向B3G演进的关键技术研究[J].移动通信2008, 8 (下): 32-37.
[4]. J.C.Haartsen. Impact of Non-Reciprocal Channel Conditions in Broadband TDD systems[C]. the 19th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC’08). 2008: 1-5.
[5]. Matilde Sanchez-Fernandez and Angel Lozano. Doppler Sensitivity of Link Reciprocity in TDD MIMO Systems[C]. IEEE Globecom. 2005: 3073-3076.
[6]. Antti Tolli, Marian Codreanu and Markku Juntti. Compensation of Non-Reciprocal Interference in Adaptive MIMO-OFDM Cellular Systems[J]. IEEE Transactions on Wireless Communications. 2007, 6(2): 545-555.
[7]. Liu Jian, Bourdoux A, Craninckx J, et al. Impact of Front-end Effects on the Performance of Downlink OFDM-MIMO Transmission[C]. IEEE Radio and Wireless Conference. Sept. 2004: 159-162.
[8]. Changkee Min and Namseok Chang, et al. MIMO-OFDM Downlink Channel Prediction for IEEE802.16e Systems Using Kalman Filter[C]. IEEE Communications Society subject matter experts for publication in the WCNC proceedings. 2007: 943-947.
[9].苏钢. TDD系统中部分信道状态下广义高斯理论的应用研究[D].博士学位论文.华中科技大学. 2007.
[10]. Jae Kyoumg Moon, Song In Choi. Performance of channel estimation methods for OFDM systems in a multipath fading channel[J]. Consumer Electronics, IEEE Transactions on 2000, 1(46): 161-170.
[11].蓝霄剑,蒋良成,尤肖虎. Rake接收机中信道最大多普勒频移估计的一种新方法及其在信道估计中的应用[J].电路与系统学报. 2000, 5(3): 1-5.
[12]. Landstorm D.S.L, van de Beek J-J, Borjesson PO. Symbol time offset estimation in coherent OFDM system[J]. IEEE Transactions on Communication. 2002, 50(4): 545-549.
[13].李卫.下一代移动通信系统中MIMO-OFDM若干关键技术的研究[D].北京邮电大学博士学位论文. 2007.
[14]. Yun Hee Kim, Lickho Song, Seokho Yoon, So Ryoung Park. An efficient frequency offset estimator for OFDM systems and its performance characteristics[J]. IEEE Transactions on Vehicular Technology. 2001, 50(5): 1307-1312.
[15]. Chang Soon Park, Kwang Bok Lee. Transmit Power Allocation for BER Permance Improvemwnt in Multicarrier Systems[J]. IEEE Transactions on Communications. 2004, 52(10): 1658-1663.
[16]. Kan Zheng, Lin Huang, Wenbo Wang. Improved power allocation schemes based on STBC-OFDM in frequency selective fading channel[C]. In Prof. Communication Technology Proceedings(ICCT2003). Sept.2003:1042-1045.
[17]. B.Hochwald, T.L.Marzetta and C.B.Papadias. A transmitter diversity scheme for wideband CDMA systems based on space-time spreading[J]. IEEE, Journal on Selected Areas in Commun. 2001, 19(1): 48-60.
[18].苏彦兵,振辉.开环和闭环发射分集的性能分析[J].重庆邮电学院学报. 2003, 15(1): 10-14.
[19].冯锡平,刘元安. MIMO-OFDM技术与IEEE802.11n标准[J].现代电信科技,2005.
[20].谢显中. TDD模式与第三代移动通信[J].现代电信科技. 2000, Vol.(2): 28-31.
[21].谢显中. TDD-SCDMA和第三代移动通信技术[M].北京:电子工业出版社. 2004
[22]. R. Steele. Mobile Radio Communication[M]. New York: Wiley, 1974.
[23]. J. G. Proakis. Digital Communication, Fourth Edition[M]. McGraw-Hill, Boston, 2001.
[24]. 3GPP TR 996 v6.1.0. Spatial Channel Model for Multiple Input Multiple Output (MIMO) Simulations[S]. 2003.
[25]. Daniel S. Baum and Jan Hansen, Giovanni Del Galdo and Marko Milojevic, Jari Salo, pekka Kyosti. An Interim Channel Model for Beyond-3G Systems: Extending the 3GPP Spatial Channel Model (SCM)[J]. Proc. IEEE VTC'05, May 2005: 3132-3136.
[26]. Hui Xiao, Alister G.Burr, Lingyang Song. A Time-Variant Wideband Spatial Channel Model Based on the 3GPP Model[J]. IEEE Vehicular Technology Conference. 2006: 1-5.
[27].程云鹏.矩阵论[M].第二版.西安:西北工业大学出版社,2005: 225-233.
[28]. David Tse, Pramod Viswanath. Fundamentals of Wireless Communication[M]. Cambridge University Press. 2004: 342-347.
[29]. G. Lebrum, T. Ying and M. Faulkner. MIMO transmission over a time-varying TDD channel using SVD[J]. Electronics letters, Vol.37, No.22, October 2001:1363-1364
[30]. G. Lebrum, J. Gao and M. Faulkner. MIMO Transmission Over a Time-Varying Channel Using SVD[J]. IEEE Transactions on Wireless Communications, Vol.4, No.2, March 2005:757-764.
[31]. 3GPP TS 36.211 v8.1.0. E-UTRA Physical Channels and Modulation[S]. 2007.
[32]. Alexandra Duel-Hallen. Fading Channel Prediction for Mobile Radio Adaptive Transmission Systems[J]. Proceedings of the IEEE, Vol. 95, No. 12, December 2007: 2299-2313.
[33]. Ebrahim Karami and Mohsen Shiva. Blind Multi-Input–Multi-Output Channel Tracking Using Decision-Directed Maximum-Likelihood Estimation[J]. IEEE Transactions on Vehicular Technology, Vol. 56, No. 3, May 2007: 1447-1454.
[34]. Christos Komninakis, Christina Fragouli, Ali H. Sayed. Multi-Input Multi-Output Fading Channel Tracking and Equalization Using Kalman Estimation[J]. IEEE Transactions on Signal Processing, Vol. 50, No. 5, May 2002:1065-1076.
[35]. Mehdi Seyfi, Mehrzad Biguesh , Roozbeh Mohammadian. An LMS-like Predictive Estimation for Fading MIMO Channels[C]. The 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications. 2007: 1-5.
[36].李欣.快速衰落时变信道的估计与均衡技术[D].硕士学位论文.电子科技大学. 2002.
[37].徐茂格,宋耀良,刘力维.一种新颖的无线信道跟踪方案[J].系统仿真学报. 2008, 20(6):1623-1625.
[38]. Linhai Li, Hong Li, Hongyi Yu,etc. A New Algorithm for MIMO Channel Tracking Based on Kalman Filter[J]. IEEE proc. WCNC proceedings. 2007: 164-168.
[39].李林海,于宏毅,胡捍英.基于Kalman滤波的MIMO时变信道估计[J].计算机工程. 2008, 34(5): 22-24.
[40]. Hani Mehrpouyan and Steven D. Blostein. ARMA Synthesis of Fading Channels-an Application to the Generation of Dynamic MIMO Channels[J].proc. IEEE GLOBECOM proceedings. 2007:3755-3759.
[41]. Bin Yang. Projection Approximation Subspace Tracking[J]. IEEE Transactions on Signal Processing, vol. 43, no.1, Jan. 1995: 95-107.
[42]. Sharon Gannott, Amir Leshemt, Ofer Shayevitz. Tracking a MIMO Channel Singular Value Decomposition via Projection Approximation[J]. IEEE 24th Convention of Electrical and Electronics Engineers in Israel. 2006: 91-94.
[43]. W.Liu, L. L.Yang and L.Hanzo. Subspace Tracking Based Blind MIMO Transmit Preprocessing[J]. IEEE Vehicular Technology Conference. 2007: 2228-2232.
[44]. Hung Tuan Nguyen, Geert Leus, Nadia Khaled. Prediction of the eigenvectors for spatial multiplexing MIMO systems in time-varying channels[C]. IEEE International Symposium on Signal Processing and Information Technology, 2005: 119-124.
[45]. Heidari A., Khandani A.K., Mcavoy D. Channel prediction for 3G communication systems[C]. Technical report, Bell Mobility. August 2004, available at http:// cst.uwaterloo.ca/~reza.
[46]. Heidari A., Khandani A.K., Mcavoy D. Adaptive modeling and long-range prediction of mobile fading channels[C]. IET Commun., Vol.4, lss.1. 2010:39-50.
[2]. ITU-RIMT-ADV/2-E, Submission and evaluation process and consensus building,(2008-08-07). http:// www.itu.int/md/R07-IMT.ADV-C-0002/en.
[3].孙韶辉,王映民. TD-SCDMA向B3G演进的关键技术研究[J].移动通信2008, 8 (下): 32-37.
[4]. J.C.Haartsen. Impact of Non-Reciprocal Channel Conditions in Broadband TDD systems[C]. the 19th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC’08). 2008: 1-5.
[5]. Matilde Sanchez-Fernandez and Angel Lozano. Doppler Sensitivity of Link Reciprocity in TDD MIMO Systems[C]. IEEE Globecom. 2005: 3073-3076.
[6]. Antti Tolli, Marian Codreanu and Markku Juntti. Compensation of Non-Reciprocal Interference in Adaptive MIMO-OFDM Cellular Systems[J]. IEEE Transactions on Wireless Communications. 2007, 6(2): 545-555.
[7]. Liu Jian, Bourdoux A, Craninckx J, et al. Impact of Front-end Effects on the Performance of Downlink OFDM-MIMO Transmission[C]. IEEE Radio and Wireless Conference. Sept. 2004: 159-162.
[8]. Changkee Min and Namseok Chang, et al. MIMO-OFDM Downlink Channel Prediction for IEEE802.16e Systems Using Kalman Filter[C]. IEEE Communications Society subject matter experts for publication in the WCNC proceedings. 2007: 943-947.
[9].苏钢. TDD系统中部分信道状态下广义高斯理论的应用研究[D].博士学位论文.华中科技大学. 2007.
[10]. Jae Kyoumg Moon, Song In Choi. Performance of channel estimation methods for OFDM systems in a multipath fading channel[J]. Consumer Electronics, IEEE Transactions on 2000, 1(46): 161-170.
[11].蓝霄剑,蒋良成,尤肖虎. Rake接收机中信道最大多普勒频移估计的一种新方法及其在信道估计中的应用[J].电路与系统学报. 2000, 5(3): 1-5.
[12]. Landstorm D.S.L, van de Beek J-J, Borjesson PO. Symbol time offset estimation in coherent OFDM system[J]. IEEE Transactions on Communication. 2002, 50(4): 545-549.
[13].李卫.下一代移动通信系统中MIMO-OFDM若干关键技术的研究[D].北京邮电大学博士学位论文. 2007.
[14]. Yun Hee Kim, Lickho Song, Seokho Yoon, So Ryoung Park. An efficient frequency offset estimator for OFDM systems and its performance characteristics[J]. IEEE Transactions on Vehicular Technology. 2001, 50(5): 1307-1312.
[15]. Chang Soon Park, Kwang Bok Lee. Transmit Power Allocation for BER Permance Improvemwnt in Multicarrier Systems[J]. IEEE Transactions on Communications. 2004, 52(10): 1658-1663.
[16]. Kan Zheng, Lin Huang, Wenbo Wang. Improved power allocation schemes based on STBC-OFDM in frequency selective fading channel[C]. In Prof. Communication Technology Proceedings(ICCT2003). Sept.2003:1042-1045.
[17]. B.Hochwald, T.L.Marzetta and C.B.Papadias. A transmitter diversity scheme for wideband CDMA systems based on space-time spreading[J]. IEEE, Journal on Selected Areas in Commun. 2001, 19(1): 48-60.
[18].苏彦兵,振辉.开环和闭环发射分集的性能分析[J].重庆邮电学院学报. 2003, 15(1): 10-14.
[19].冯锡平,刘元安. MIMO-OFDM技术与IEEE802.11n标准[J].现代电信科技,2005.
[20].谢显中. TDD模式与第三代移动通信[J].现代电信科技. 2000, Vol.(2): 28-31.
[21].谢显中. TDD-SCDMA和第三代移动通信技术[M].北京:电子工业出版社. 2004
[22]. R. Steele. Mobile Radio Communication[M]. New York: Wiley, 1974.
[23]. J. G. Proakis. Digital Communication, Fourth Edition[M]. McGraw-Hill, Boston, 2001.
[24]. 3GPP TR 996 v6.1.0. Spatial Channel Model for Multiple Input Multiple Output (MIMO) Simulations[S]. 2003.
[25]. Daniel S. Baum and Jan Hansen, Giovanni Del Galdo and Marko Milojevic, Jari Salo, pekka Kyosti. An Interim Channel Model for Beyond-3G Systems: Extending the 3GPP Spatial Channel Model (SCM)[J]. Proc. IEEE VTC'05, May 2005: 3132-3136.
[26]. Hui Xiao, Alister G.Burr, Lingyang Song. A Time-Variant Wideband Spatial Channel Model Based on the 3GPP Model[J]. IEEE Vehicular Technology Conference. 2006: 1-5.
[27].程云鹏.矩阵论[M].第二版.西安:西北工业大学出版社,2005: 225-233.
[28]. David Tse, Pramod Viswanath. Fundamentals of Wireless Communication[M]. Cambridge University Press. 2004: 342-347.
[29]. G. Lebrum, T. Ying and M. Faulkner. MIMO transmission over a time-varying TDD channel using SVD[J]. Electronics letters, Vol.37, No.22, October 2001:1363-1364
[30]. G. Lebrum, J. Gao and M. Faulkner. MIMO Transmission Over a Time-Varying Channel Using SVD[J]. IEEE Transactions on Wireless Communications, Vol.4, No.2, March 2005:757-764.
[31]. 3GPP TS 36.211 v8.1.0. E-UTRA Physical Channels and Modulation[S]. 2007.
[32]. Alexandra Duel-Hallen. Fading Channel Prediction for Mobile Radio Adaptive Transmission Systems[J]. Proceedings of the IEEE, Vol. 95, No. 12, December 2007: 2299-2313.
[33]. Ebrahim Karami and Mohsen Shiva. Blind Multi-Input–Multi-Output Channel Tracking Using Decision-Directed Maximum-Likelihood Estimation[J]. IEEE Transactions on Vehicular Technology, Vol. 56, No. 3, May 2007: 1447-1454.
[34]. Christos Komninakis, Christina Fragouli, Ali H. Sayed. Multi-Input Multi-Output Fading Channel Tracking and Equalization Using Kalman Estimation[J]. IEEE Transactions on Signal Processing, Vol. 50, No. 5, May 2002:1065-1076.
[35]. Mehdi Seyfi, Mehrzad Biguesh , Roozbeh Mohammadian. An LMS-like Predictive Estimation for Fading MIMO Channels[C]. The 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications. 2007: 1-5.
[36].李欣.快速衰落时变信道的估计与均衡技术[D].硕士学位论文.电子科技大学. 2002.
[37].徐茂格,宋耀良,刘力维.一种新颖的无线信道跟踪方案[J].系统仿真学报. 2008, 20(6):1623-1625.
[38]. Linhai Li, Hong Li, Hongyi Yu,etc. A New Algorithm for MIMO Channel Tracking Based on Kalman Filter[J]. IEEE proc. WCNC proceedings. 2007: 164-168.
[39].李林海,于宏毅,胡捍英.基于Kalman滤波的MIMO时变信道估计[J].计算机工程. 2008, 34(5): 22-24.
[40]. Hani Mehrpouyan and Steven D. Blostein. ARMA Synthesis of Fading Channels-an Application to the Generation of Dynamic MIMO Channels[J].proc. IEEE GLOBECOM proceedings. 2007:3755-3759.
[41]. Bin Yang. Projection Approximation Subspace Tracking[J]. IEEE Transactions on Signal Processing, vol. 43, no.1, Jan. 1995: 95-107.
[42]. Sharon Gannott, Amir Leshemt, Ofer Shayevitz. Tracking a MIMO Channel Singular Value Decomposition via Projection Approximation[J]. IEEE 24th Convention of Electrical and Electronics Engineers in Israel. 2006: 91-94.
[43]. W.Liu, L. L.Yang and L.Hanzo. Subspace Tracking Based Blind MIMO Transmit Preprocessing[J]. IEEE Vehicular Technology Conference. 2007: 2228-2232.
[44]. Hung Tuan Nguyen, Geert Leus, Nadia Khaled. Prediction of the eigenvectors for spatial multiplexing MIMO systems in time-varying channels[C]. IEEE International Symposium on Signal Processing and Information Technology, 2005: 119-124.
[45]. Heidari A., Khandani A.K., Mcavoy D. Channel prediction for 3G communication systems[C]. Technical report, Bell Mobility. August 2004, available at http:// cst.uwaterloo.ca/~reza.
[46]. Heidari A., Khandani A.K., Mcavoy D. Adaptive modeling and long-range prediction of mobile fading channels[C]. IET Commun., Vol.4, lss.1. 2010:39-50.