高速移动无线信道自适应均衡研究
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摘要
本文首先研究了无线通信信道小尺度衰落特性,并对多径衰落信道进行仿真。小尺度衰落包括多径效应和多普勒频移等问题。多径效应造成的码间干扰会极大地降低通信系统的性能,而自适应均衡是时变无线移动信道中对抗码间干扰的一项重要技术。在研究自适应均衡的原理、结构和算法的基础上,本文深入研究了最大似然序列估计(MLSE)。
在无线信道中应用MLSE存在两个问题,即存在较大的判决延迟和较高的计算复杂度。判决延迟在高速移动无线信道中影响尤为严重。本文研究分析了减少MLSE判决延迟和计算复杂度的多种改进方法,并将逐幸存处理算法(PSP)和基于簇的序列估计(CBSE)算法作为研究的重点。在保证性能的前提下,PSP算法减少了判决延迟,而CBSE算法大大减少计算复杂度。本文详细介绍了这两种算法的基本原理和实现方法。针对在无线时变信道中具体应用该算法时存在的问题,尤其是在高速移动且快速时变环境中应用时出现的问题,提出了改进方法,并结合仿真,分析比较其性能,最后给出详细的计算复杂度比较。
图38幅,表10个,参考文献39篇。
First of all, this paper does a lot of research on the characteristics of mobile wireless channel, especially on the small-scale fading. Simulation of multipath fading channel is also presented. Multipath effect and Doppler shift are two troublesome problems in mobile wireless channel. Inter symbol interference (ISI) caused by multipath effect is a major factor to degrade the performance of modern digital communication systems. Adaptive equalization is an important technique to combat the ISI in time varying mobile wireless channel. This paper focuses on Maximum Likelihood Sequence Estimate (MLSE), based on the widely study of basic principle, structure and algorithms of adaptive equalization.
When MLSE is put into real practice, decision delay and computational complexity are two problems to be solved. The decision delay is terribly serious in high speed mobile wireless channel. Many improvement methods of MLSE are discussed. This paper mainly concerns two of them, i.e., PSP and CBSE. Per-Survivor-Processing (PSP) is an effective way to solve the problem of decision delay. Cluster Based Sequence Estimation (CBSE) is an effective solution to reduce the computational complexity of classic MLSE.When those schemes are used in the mobile wireless communication system, especially in the high speed mobile environment, some problems come out and solutions to them are proposed in this paper. Analysis of performance and complexity are also presented, combined with simulation.
在无线信道中应用MLSE存在两个问题,即存在较大的判决延迟和较高的计算复杂度。判决延迟在高速移动无线信道中影响尤为严重。本文研究分析了减少MLSE判决延迟和计算复杂度的多种改进方法,并将逐幸存处理算法(PSP)和基于簇的序列估计(CBSE)算法作为研究的重点。在保证性能的前提下,PSP算法减少了判决延迟,而CBSE算法大大减少计算复杂度。本文详细介绍了这两种算法的基本原理和实现方法。针对在无线时变信道中具体应用该算法时存在的问题,尤其是在高速移动且快速时变环境中应用时出现的问题,提出了改进方法,并结合仿真,分析比较其性能,最后给出详细的计算复杂度比较。
图38幅,表10个,参考文献39篇。
First of all, this paper does a lot of research on the characteristics of mobile wireless channel, especially on the small-scale fading. Simulation of multipath fading channel is also presented. Multipath effect and Doppler shift are two troublesome problems in mobile wireless channel. Inter symbol interference (ISI) caused by multipath effect is a major factor to degrade the performance of modern digital communication systems. Adaptive equalization is an important technique to combat the ISI in time varying mobile wireless channel. This paper focuses on Maximum Likelihood Sequence Estimate (MLSE), based on the widely study of basic principle, structure and algorithms of adaptive equalization.
When MLSE is put into real practice, decision delay and computational complexity are two problems to be solved. The decision delay is terribly serious in high speed mobile wireless channel. Many improvement methods of MLSE are discussed. This paper mainly concerns two of them, i.e., PSP and CBSE. Per-Survivor-Processing (PSP) is an effective way to solve the problem of decision delay. Cluster Based Sequence Estimation (CBSE) is an effective solution to reduce the computational complexity of classic MLSE.When those schemes are used in the mobile wireless communication system, especially in the high speed mobile environment, some problems come out and solutions to them are proposed in this paper. Analysis of performance and complexity are also presented, combined with simulation.
引文
[1] Theodore S. Rappaport.蔡涛等.无线通信原理与应用. 第一版.北京.电子工业出版社.1999.103-142, 222-240
[2] Gordon L. Stuber.裴昌幸.移动通信原理. 第二版.北京.电子工业出版社.2004.29-75
[3] H.Kubo.An adaptive maximum likelihood sequence estimator for fast time-varying intersymbol interference channels. IEEE Transactions on Communications.1994.42 (2/3/4):1872 -1880
[4] Riccardo Raheli, Andreas Polydoros, Ching-Kate Tzou.Per-Survivor Processing: A General Approach to MLSE in Uncertain Environments.IEEE Transactions on Communications.1995.43(2/3/ 4).354-364
[5] Riccardo Raheli, Giovanni Marino, Piero Castoldi.Per-survivor processing and tentative decisions: what is in between?. IEEE Transactions on Communications.1996.44(2):127-129
[6] Jung-Suk Joo, Seung-Chul Hong, Yong-Hoon Lee. Adaptive MLSE receiver: hybrid of per-survivor processing and tentative decision MLSE.Electronic Letters. 2000.36(7).78-680
[7] Zhenyu Zhu,Hamid R. Sadjadpour.An Adaptive Per-Survivor Processing Algorithm.IEEE Transactions on Communications.2002.50(11).1716-1718
[8] John G Proakis.张力军.数字通信.第四版.北京.电子工业出版社.2003.349-350,467-489
[9] Yannis Kopsinis, Sergios Theodoridis.A novel cluster baesd MLSE equalizers for M-PAM signaling schemes. IEEE Transactions on Signal Processing.2003.1905-1918
[10] 杨大成等.现代移动通信中的先进技术.北京.机械工业出版社.2005.62-67
[11] 杨大成等.移动传播环境:理论基础、分析方法和建模技术.北京.机械工业出版社.2003
[12] 邓华.Matlab 通信仿真及应用实例详解.北京.人民邮电出版社.2003.116-149
[13] Bernard Sklar.徐平平.数字通信——基础与应用.第二版.北京.电子工业出版社.2005.293-333
[14] Widrow B., Stearns S., Adaptive Signal Processing.Prentice-Hall.1985
[15] 吕振肃,黄石.一种改进的变步长 ELMS 算法.电子与信息学报.2005.10
[16] 张贤达,保铮.通信信号处理.北京.国防工业出版社.2000.232-264
[17] Gordon L. Stuber.裴昌幸.移动通信原理.第二版.北京.电子工业出版社.2004.241-270
[18] 邱天爽,魏东兴等.通信信号中的自适应信号处理.北京电子工业出版社.2005.23-47
[19] G. D. Forney Jr.Maximum likelihood sequence estimation of digital sequence in the presence of intersymbol interference.IEEE Transactions on Information Theory.1972.18(3).363-378
[20] Ungerboeck.Adaptative maximum-likelihood receiver for carrier modulated data-trasmission system.IEEE Transactions on Communications. 1974.22. 624-636
[21] S.U.H. Qureshi.An adaptive for data transmission over time-dispersive channels.IEEE Tansacation on Information Theory.1973.19(7).448-457
[22] M.Chiu and C.Chao.Analysis of LMS-adaptive MLSE equalization on multipath fading channels.IEEE Transactions Communication.1996.44(12).1648-1692
[23] J.Wu, A.H. Aghvami.A new adaptive equalizer with channel estimator for mobile radio communications.IEEE Transacations on Vehicular Technology.1996.45(3).1178-1190
[24] 黄当征.高速铁路移动信道的均衡技术的研究.北京:北京交通大学电子信息工程学院.1999.27-54
[25] William H. Tranter.Principles of communication systems simulation with wireless applications.USA.Prentice Hall.2004.538-581
[26] John G. Proakis, Masoud Salehi, Gerhard Bauch. 刘树棠.现代通信系统(MATLAB 版).第二版.北京.电子工业出版社.2005.275-310
[27] 张永强,向倩,茹国宝等.一种改进的减少状态的逐幸存处理均衡器.武汉大学学报(理学版).2004.50 (5).629-632
[28] M.Vedat Eyuboglu,Shahid U.H.Qureshi.Reduced-State Sequence Estimation with Set Partitioning and Decision Feedback. IEEE Transactions on Communications.1988.36(1).13-20
[29] 茹国宝,张永强,杨浩等.一种用于无线信道的逐幸存处理均衡器.信息与电子工程.2005.3 (1).6-10
[30] A. Duel-Hallen, C. Heegard.Delayed decision feedback sequence estimation. IEEE Transactions on Communications.1989.37(5).428-436
[31] 郭经红,程时昕.GSM 数字移动通信系统中自适应均衡器技术研究.应用科学学报.1997.15(3).169-173
[32] 孙德刚.自适应均衡技术在 GSM 接收机中的应用.北京:北京交通大学计算机与信息技术学院.2002
[33] J.B.Evans,B.Liu.Variable step size methods for the LMS adaptive algorithm.Proc.IEEEE Int.Symp.Circuits and System.1987.422-425
[34] Yannis Kopsinis, Sergios Theodoridis.A novel low complexity cluster based MLSE equalizer for QPSK signaling scheme.IEEE DSP.2002.45-48
[35] Yannis Kopsinis, Sergios Theodoridis.An efficient low complexity technique for MLSE equalizers for linear and nonlinear channels. IEEE Transcations on Signal Processing.2003.5 (12).3236-3248
[36] Yannis Kopsinis, Sergios Theodoridis.An efficient low complexity cluster-based MLSE equalizer for frequency-selective fading channels.IEEE Transcations on Wireless Communications. 2006.5(4).705-711
[37] Eleftherios Kofidis.Yannis Kopsinis, Sergios Theodoridis.On the least-squares performance of a novel efficient center estimation method for clustering-based MLSE equalization.2006.54(4).1459-1471
[38] Michael Kerner, Ofer Amrani.Viterbi Algorithm Motives in Turbo Decoding.Proc. of IEEE ISOC ITW2005 on Coding and Complexity.2005.98-102.
[39] Yasuhiko Tanabe, Akihito Hanaki, Takeo Ohgane. Novel spatiotemporal equalization based on cascaded connection of multibeam adaptive array and multi-input MLSE.IEEE Transactions on Wireless Communications.2005.4(6).2716-2725
[2] Gordon L. Stuber.裴昌幸.移动通信原理. 第二版.北京.电子工业出版社.2004.29-75
[3] H.Kubo.An adaptive maximum likelihood sequence estimator for fast time-varying intersymbol interference channels. IEEE Transactions on Communications.1994.42 (2/3/4):1872 -1880
[4] Riccardo Raheli, Andreas Polydoros, Ching-Kate Tzou.Per-Survivor Processing: A General Approach to MLSE in Uncertain Environments.IEEE Transactions on Communications.1995.43(2/3/ 4).354-364
[5] Riccardo Raheli, Giovanni Marino, Piero Castoldi.Per-survivor processing and tentative decisions: what is in between?. IEEE Transactions on Communications.1996.44(2):127-129
[6] Jung-Suk Joo, Seung-Chul Hong, Yong-Hoon Lee. Adaptive MLSE receiver: hybrid of per-survivor processing and tentative decision MLSE.Electronic Letters. 2000.36(7).78-680
[7] Zhenyu Zhu,Hamid R. Sadjadpour.An Adaptive Per-Survivor Processing Algorithm.IEEE Transactions on Communications.2002.50(11).1716-1718
[8] John G Proakis.张力军.数字通信.第四版.北京.电子工业出版社.2003.349-350,467-489
[9] Yannis Kopsinis, Sergios Theodoridis.A novel cluster baesd MLSE equalizers for M-PAM signaling schemes. IEEE Transactions on Signal Processing.2003.1905-1918
[10] 杨大成等.现代移动通信中的先进技术.北京.机械工业出版社.2005.62-67
[11] 杨大成等.移动传播环境:理论基础、分析方法和建模技术.北京.机械工业出版社.2003
[12] 邓华.Matlab 通信仿真及应用实例详解.北京.人民邮电出版社.2003.116-149
[13] Bernard Sklar.徐平平.数字通信——基础与应用.第二版.北京.电子工业出版社.2005.293-333
[14] Widrow B., Stearns S., Adaptive Signal Processing.Prentice-Hall.1985
[15] 吕振肃,黄石.一种改进的变步长 ELMS 算法.电子与信息学报.2005.10
[16] 张贤达,保铮.通信信号处理.北京.国防工业出版社.2000.232-264
[17] Gordon L. Stuber.裴昌幸.移动通信原理.第二版.北京.电子工业出版社.2004.241-270
[18] 邱天爽,魏东兴等.通信信号中的自适应信号处理.北京电子工业出版社.2005.23-47
[19] G. D. Forney Jr.Maximum likelihood sequence estimation of digital sequence in the presence of intersymbol interference.IEEE Transactions on Information Theory.1972.18(3).363-378
[20] Ungerboeck.Adaptative maximum-likelihood receiver for carrier modulated data-trasmission system.IEEE Transactions on Communications. 1974.22. 624-636
[21] S.U.H. Qureshi.An adaptive for data transmission over time-dispersive channels.IEEE Tansacation on Information Theory.1973.19(7).448-457
[22] M.Chiu and C.Chao.Analysis of LMS-adaptive MLSE equalization on multipath fading channels.IEEE Transactions Communication.1996.44(12).1648-1692
[23] J.Wu, A.H. Aghvami.A new adaptive equalizer with channel estimator for mobile radio communications.IEEE Transacations on Vehicular Technology.1996.45(3).1178-1190
[24] 黄当征.高速铁路移动信道的均衡技术的研究.北京:北京交通大学电子信息工程学院.1999.27-54
[25] William H. Tranter.Principles of communication systems simulation with wireless applications.USA.Prentice Hall.2004.538-581
[26] John G. Proakis, Masoud Salehi, Gerhard Bauch. 刘树棠.现代通信系统(MATLAB 版).第二版.北京.电子工业出版社.2005.275-310
[27] 张永强,向倩,茹国宝等.一种改进的减少状态的逐幸存处理均衡器.武汉大学学报(理学版).2004.50 (5).629-632
[28] M.Vedat Eyuboglu,Shahid U.H.Qureshi.Reduced-State Sequence Estimation with Set Partitioning and Decision Feedback. IEEE Transactions on Communications.1988.36(1).13-20
[29] 茹国宝,张永强,杨浩等.一种用于无线信道的逐幸存处理均衡器.信息与电子工程.2005.3 (1).6-10
[30] A. Duel-Hallen, C. Heegard.Delayed decision feedback sequence estimation. IEEE Transactions on Communications.1989.37(5).428-436
[31] 郭经红,程时昕.GSM 数字移动通信系统中自适应均衡器技术研究.应用科学学报.1997.15(3).169-173
[32] 孙德刚.自适应均衡技术在 GSM 接收机中的应用.北京:北京交通大学计算机与信息技术学院.2002
[33] J.B.Evans,B.Liu.Variable step size methods for the LMS adaptive algorithm.Proc.IEEEE Int.Symp.Circuits and System.1987.422-425
[34] Yannis Kopsinis, Sergios Theodoridis.A novel low complexity cluster based MLSE equalizer for QPSK signaling scheme.IEEE DSP.2002.45-48
[35] Yannis Kopsinis, Sergios Theodoridis.An efficient low complexity technique for MLSE equalizers for linear and nonlinear channels. IEEE Transcations on Signal Processing.2003.5 (12).3236-3248
[36] Yannis Kopsinis, Sergios Theodoridis.An efficient low complexity cluster-based MLSE equalizer for frequency-selective fading channels.IEEE Transcations on Wireless Communications. 2006.5(4).705-711
[37] Eleftherios Kofidis.Yannis Kopsinis, Sergios Theodoridis.On the least-squares performance of a novel efficient center estimation method for clustering-based MLSE equalization.2006.54(4).1459-1471
[38] Michael Kerner, Ofer Amrani.Viterbi Algorithm Motives in Turbo Decoding.Proc. of IEEE ISOC ITW2005 on Coding and Complexity.2005.98-102.
[39] Yasuhiko Tanabe, Akihito Hanaki, Takeo Ohgane. Novel spatiotemporal equalization based on cascaded connection of multibeam adaptive array and multi-input MLSE.IEEE Transactions on Wireless Communications.2005.4(6).2716-2725