多发送天线系统下检测算法的研究
摘要
多输入多输出(MIMO)技术是未来无线通信的发展方向,它改变了以往的单天线收发结构,在发射端和接收端同时使用多天线,不仅能够大幅度提高信道容量,而且能够提供复用增益和分集增益,同时提高信息传输速率和改善信号接收质量。垂直分层空时码(V-BLAST)是MIMO系统中一种典型的分层空时码,可以获得很高的频带利用率和较低的系统复杂度,是实现MIMO系统的优秀解决方案之一。MIMO系统接收端检测算法的设计对系统的误码率性能和复杂度有着较大的影响,研究高性能、低复杂度的MIMO信号检测算法具有重大意义。
本文在国内外相关研究工作的基础上对MIMO系统信号检测技术进行了研究。首先分析了MIMO系统V-BLAST结构的模型,其次介绍了基本的检测算法,包括最大似然检测算法(ML)、迫零检测(ZF)、最小均方误差检测(MMSE).连续干扰抵消检测(SIC)、排序连续干扰抵消检测(OSIC)以及正交三角(QR)分解检测等,并通过理论分析和性能仿真对检测算法的性能和复杂度进行了比较。
本文随后重点研究了球形检测(SD),在阐述球形检测基本原理的基础上,对多种球形检测算法初始半径选择方法以及搜索半径更新策略进行了理论分析和性能比较,并讨论了K-BEST检测和我们提出的改进搜索策略的K-BEST检测。理论分析和仿真结果均表明,改进的K-BEST检测在几乎不损失性能的同时大幅降低了复杂度。
As one of the development direction of future wireless communications, multi-input multi-output technology has changed the previous single antenna system structure and uses multiple antennas at the transmitter and receiver both, which not only can increase the channel capacity significantly, but also can provide reuse gain and diversity gain, increase the information transmission rate and improve the signal reception quality. V-BLAST is a typical layered space-time code in MIMO system and an excellent solution for MIMO system, which can get higher bandwidth efficiency and lower system complexity. Design of the MIMO system receiver detection algorithm has a greater impact on the system BER performance and complexity, which makes great significance on the research of MIMO system detection algorithm with high performance and low complexity.
In this paper, we do some research work on MIMO system detection algorithm on the basis of relevant research work at home and abroad. First, we have an analysis on the structure model of the MIMO system, then we have an introduction of the basic detection algorithm, including maximum likelihood detection, zero forcing detection, minimum mean square error detection, successive interference cancellation detection, ordered successive interference cancellation detection and orthogonal decomposition of triangular detection and so on, finally we compare their performance and complexity through theoretical analysis and performance simulation.
The paper will then focus on sphere detection. On the basis of describing the basic principle of the sphere detection, we do theoretical analysis and performance simulation on a variety of initial radius selection methods and search radius update strategy of sphere detection algorithm, and discuss the K-BEST detection algorithm and our proposed improved search strategy K-BEST algorithm. Both the theoretical analysis and simulation results shows that the improved K-BEST algorithm reduces the complexity dramatically while with almost no loss of the performance.
本文在国内外相关研究工作的基础上对MIMO系统信号检测技术进行了研究。首先分析了MIMO系统V-BLAST结构的模型,其次介绍了基本的检测算法,包括最大似然检测算法(ML)、迫零检测(ZF)、最小均方误差检测(MMSE).连续干扰抵消检测(SIC)、排序连续干扰抵消检测(OSIC)以及正交三角(QR)分解检测等,并通过理论分析和性能仿真对检测算法的性能和复杂度进行了比较。
本文随后重点研究了球形检测(SD),在阐述球形检测基本原理的基础上,对多种球形检测算法初始半径选择方法以及搜索半径更新策略进行了理论分析和性能比较,并讨论了K-BEST检测和我们提出的改进搜索策略的K-BEST检测。理论分析和仿真结果均表明,改进的K-BEST检测在几乎不损失性能的同时大幅降低了复杂度。
As one of the development direction of future wireless communications, multi-input multi-output technology has changed the previous single antenna system structure and uses multiple antennas at the transmitter and receiver both, which not only can increase the channel capacity significantly, but also can provide reuse gain and diversity gain, increase the information transmission rate and improve the signal reception quality. V-BLAST is a typical layered space-time code in MIMO system and an excellent solution for MIMO system, which can get higher bandwidth efficiency and lower system complexity. Design of the MIMO system receiver detection algorithm has a greater impact on the system BER performance and complexity, which makes great significance on the research of MIMO system detection algorithm with high performance and low complexity.
In this paper, we do some research work on MIMO system detection algorithm on the basis of relevant research work at home and abroad. First, we have an analysis on the structure model of the MIMO system, then we have an introduction of the basic detection algorithm, including maximum likelihood detection, zero forcing detection, minimum mean square error detection, successive interference cancellation detection, ordered successive interference cancellation detection and orthogonal decomposition of triangular detection and so on, finally we compare their performance and complexity through theoretical analysis and performance simulation.
The paper will then focus on sphere detection. On the basis of describing the basic principle of the sphere detection, we do theoretical analysis and performance simulation on a variety of initial radius selection methods and search radius update strategy of sphere detection algorithm, and discuss the K-BEST detection algorithm and our proposed improved search strategy K-BEST algorithm. Both the theoretical analysis and simulation results shows that the improved K-BEST algorithm reduces the complexity dramatically while with almost no loss of the performance.
引文
[1]堪璟MIMO信号检测技术研究：[博士学位论文].武汉：华中科技大学信息与通信工程专业.2006
[2]C. Berrou, A. Glavieux, and P. Thitimajshima. Near Shannon limit error-correction coding and decoding:Turbo-codes. Proc. IEEE ICC'93,1993, vol.2, pp.1064-1070
[3]R. G. Gallager, Low-density parity-check codes based on very sparse matrices, IRE Trans. Info. Theory,1962, vol.7, pp.21-28
[4]Branka Vucetic, Jinhong Yuan. Space-time Coding. England:John Wiley & Sons Ltd, 2003. pp.54-63
[5]I. E. Telatar. Capacity of Multi-antenna Gaussion Channels. Bell Labs Technical Memorandum,1995. pp.1-28
[6]G. J. Foschini, M. J. Gans. On limits of wireless communication in a fading environment when using multiple antennas. Wireless Personal Communication,1998, vol.6, pp.311-335
[7]G. J. Foschini. Layered space-time architecture for wireless communication in fading environment when using multiple antennas. Bell Labs Technical Journal,1996, vol.1, no.2, pp.41-59
[8]G. D. Golden, G. J. Foschini, R. A. Valenzuala, and P. W. Volniansky. Detection algorithm and initial laboratory results using V-BLAST space-time communication architecture. Electronic Letters,1999, vol.35, no.1, pp.6-7
[9]V. Tarokh, N. Seshadri, and A. R. Calderbank. Space-time codes for high data rate wireless communication:performance criterion and code construction. IEEE Transactions on Information Theory,1998, vol.44, no.2, pp.744-765
[10]S. M. Alamouti. A Simple Transmitter Diversity Scheme for Wireless Communications. IEEEJ. Select. Areas Commun.,1998,vol.16, pp.1451-1458
[11]V. Tarokh, H. Jafarkhani, and A. R. Calderbank, Space-time block codes from orthogonal designs. IEEE Transactions on Information Theory,1999, vol.45, no.5, pp. 1456-1467
[12]P. W. Volniansky, G. J. Foschini, G. D. Golden, and R. A. Valenzuala, V-BLAST: An architecture for realizing very high data rates over the rich-scattering wireless channel. In Proc. URSIISSSE. Pisa, Italy,1998, pp.295-300
[13]O. Damen, A. Chkief, and J. C. Belfiore. Lattice code decoder for space-time codes. IEEE Communications Letters,2000, vol.4, no.5, pp.161-163
[14]E. Viterbo, J. Bouros. A universal lattice code decoder for fading channels. IEEE Transactions on Information Theory,1999, vol.45, no.5, pp.1639-1642
[15]邵玉斌Matlab/Simulink通信系统建模与仿真实例分析.北京：清华大学出版社,2008
[16]David Tse, Pramod Viswanath. Fundamentals of Wireless Communication. London: Cambridge University Press,2005. pp.10-33
[17]汪凡MIMO系统检测算法研究及收发技术联合设计：[博士学位论文].杭州：浙江大学电子科学与技术专业.2008
[18]B. Vucetic, J. Nicolas. Performance of M-PSK trellis codes over nonlinear fading mobile satellite channels. IEE Proceedings I,1992, vol.139, pp.462-471
[19]任品毅等.V-BLAST系统中一种基于噪声分析的简化最大似然检测算法.电子与信息学报,2010,32(3)：539-543
[20]潘文,蒋占军等.BLAST结构ML检测简化方法分析.中国科学E辑：信息科学,2008,38(8)：1277-1283
[211 V. Pammer, Y. Delignon, W. Savaya, and D. A. Boulinguez. A low complexity suboptimal MIMO receiver:the combined ZF-MLD algorithm.14th IEEE Proceedings On Personnal, Indoor and Mobile Radio Communications,2003, vol.3, pp.2271-2275
[22]W. H. Chin, A. G. Constantinides, and D. B. Ward. Parallel multistage detection for multiple attennas wireless systems. Electronics Letters,2002, vol.38, no.12, pp.597-599
[23]F. Wang, Y. Xiong, and X. M. Yang. Approximate ML detection based on MMSE for MIMO communication systems. Progress in Electromagnetics Research Symposium,2007, vol.3, no.4, pp.475-480
[24]D. W. Waters, J. R. Barry. The chase family of detection algorithm for multi-input multi-output channels. IEEE Transactions on Signal Processing,2008, vol.56, no.2, pp. 739-747
[25]L. Yang, M. Chen, S. X. Cheng, et al.. Combined maximum likelihood and ordered successive interference cancellation grouped detection algorithm for multistream MIMO ISSSTA'2004,2004. pp.250-254
[26]D. Wubben, R. Bohnke, J. Rinas, et al.. Efficient algorithm for decoding layered space-time codes. Electronics Letters,2001, vol.37, pp.1248-1350
[27]孙艳华,吴伟陵.基于QR分解V-BLAST检测算法研究与比较.无线电工程,2006,36(12)：26-29
[28]W. J. Choi, R. Negi, and J. M. Cioffi. Combined ML and DFE for the V-BLAST system. IEEE International Conference on Communications,2002, vol.3, pp.1243-1248
[29]D.W.Waters,J.R.Barry.The sorted-QR chase detector for multi-input multi-output channels.2005 IEEE Wireless.Communications and Networking Conference,2005,Vol.1,pp. 538-543
[30]游月辉.MIMO通信系统信号检测技术研究：[硕士学位论文].大连：大连理工大学信号与信息处理专业.2009
[31]B.Hassibi,H.Vikalo.On the sphere-decoding algorithm Ⅰ:expected camplexity IEEE Trans.Signa,Process,2005,Vol.53,no.8,pp.2806-2818
[32]A.M.Chan,I.Lee.A new reduced-complexity sphere decoder for multiple antenna systems.IEEE International,Conference on Communications,2002,vol.1,pp.460-464
1331 C.P.Schnorr,M.Euchner.Lattice basis reduction:Improved practical algorithms and solving subset sum problems.Mathematical Programming,1994,Vol.66,pp.181-199
[34]U.Fincke,M.Phost.Improved methods for calculating vectors of short length in a lattice,including a camplexity analysis.Mathemalics of Computiation,1985,vol.44,pp.463-471
[35]A.Ghaderipoor,C.Tellambura.A statistical pruning strategy for Schnorr-Euchner sphere decoding.IEEE Commun.Lett.,2008,vol.12,no.2,pp.121-123
[36]Q.L.Liu,L.X.Yang.A novel method for initial radius selection of sphere decoding. 2004 IEEE 60th Vehicular Technology Conference,2004,vol.2,1280一1283
[37]邹涵MIMO系统中的球形检测算法：[硕士学位论文].北京：北京交通大学信号与信息处理专业.2009
[38]T.Takahashi,T.Fukuda,C.K.Sun,et al..An appropriate radius for reduced-complexity sphere decoding.ICCCAS'2010,2010,pp.41-44
[39]陈云杰,吴耀军等.基于MIMO系统的球形译码算法的改进.通信技术,2010,43(6)： 24-28
[40]W.Xu,J.Jiang,et al..An effcient tree search algorithm for optimal detection of MIMO signals with channel estimation errors.2004 IEEE 60th Vehicular Technology Conference,2004,Vol.2,1503-1507
[41]S.M.Razavizadeh,V.T.Vakili,and P.Azmi.A new faster sphere decoder for MIMO systems.Signal Processing and Information Technology,2003,pp.86-89
[42]B.Hassibi,H.Vikalo.On the expected camplexity of integer least-squares problems. In Pro.IEEE ICASSP,2002,Vol.2,pp.1497-1500
[43]Y.Hnang,P.M.Djuric.Multiuser detection of synchronous CDMA signals by the Gibbs coupler.In Pro.IEEE ICASSP,2001,Vol.4,pp.2273-2276
[44]Q. W. Li, Z. F. Wang. Improved K-BEST sphere decoding algorithm for MIMO systems. IEEE ISCAS'06,2006, pp.1159-1162
[45]贾龙直,李兆训.多入多出系统中改进的QRD-M检测算法.计算机工程,2011,37(3)：77-79
[2]C. Berrou, A. Glavieux, and P. Thitimajshima. Near Shannon limit error-correction coding and decoding:Turbo-codes. Proc. IEEE ICC'93,1993, vol.2, pp.1064-1070
[3]R. G. Gallager, Low-density parity-check codes based on very sparse matrices, IRE Trans. Info. Theory,1962, vol.7, pp.21-28
[4]Branka Vucetic, Jinhong Yuan. Space-time Coding. England:John Wiley & Sons Ltd, 2003. pp.54-63
[5]I. E. Telatar. Capacity of Multi-antenna Gaussion Channels. Bell Labs Technical Memorandum,1995. pp.1-28
[6]G. J. Foschini, M. J. Gans. On limits of wireless communication in a fading environment when using multiple antennas. Wireless Personal Communication,1998, vol.6, pp.311-335
[7]G. J. Foschini. Layered space-time architecture for wireless communication in fading environment when using multiple antennas. Bell Labs Technical Journal,1996, vol.1, no.2, pp.41-59
[8]G. D. Golden, G. J. Foschini, R. A. Valenzuala, and P. W. Volniansky. Detection algorithm and initial laboratory results using V-BLAST space-time communication architecture. Electronic Letters,1999, vol.35, no.1, pp.6-7
[9]V. Tarokh, N. Seshadri, and A. R. Calderbank. Space-time codes for high data rate wireless communication:performance criterion and code construction. IEEE Transactions on Information Theory,1998, vol.44, no.2, pp.744-765
[10]S. M. Alamouti. A Simple Transmitter Diversity Scheme for Wireless Communications. IEEEJ. Select. Areas Commun.,1998,vol.16, pp.1451-1458
[11]V. Tarokh, H. Jafarkhani, and A. R. Calderbank, Space-time block codes from orthogonal designs. IEEE Transactions on Information Theory,1999, vol.45, no.5, pp. 1456-1467
[12]P. W. Volniansky, G. J. Foschini, G. D. Golden, and R. A. Valenzuala, V-BLAST: An architecture for realizing very high data rates over the rich-scattering wireless channel. In Proc. URSIISSSE. Pisa, Italy,1998, pp.295-300
[13]O. Damen, A. Chkief, and J. C. Belfiore. Lattice code decoder for space-time codes. IEEE Communications Letters,2000, vol.4, no.5, pp.161-163
[14]E. Viterbo, J. Bouros. A universal lattice code decoder for fading channels. IEEE Transactions on Information Theory,1999, vol.45, no.5, pp.1639-1642
[15]邵玉斌Matlab/Simulink通信系统建模与仿真实例分析.北京：清华大学出版社,2008
[16]David Tse, Pramod Viswanath. Fundamentals of Wireless Communication. London: Cambridge University Press,2005. pp.10-33
[17]汪凡MIMO系统检测算法研究及收发技术联合设计：[博士学位论文].杭州：浙江大学电子科学与技术专业.2008
[18]B. Vucetic, J. Nicolas. Performance of M-PSK trellis codes over nonlinear fading mobile satellite channels. IEE Proceedings I,1992, vol.139, pp.462-471
[19]任品毅等.V-BLAST系统中一种基于噪声分析的简化最大似然检测算法.电子与信息学报,2010,32(3)：539-543
[20]潘文,蒋占军等.BLAST结构ML检测简化方法分析.中国科学E辑：信息科学,2008,38(8)：1277-1283
[211 V. Pammer, Y. Delignon, W. Savaya, and D. A. Boulinguez. A low complexity suboptimal MIMO receiver:the combined ZF-MLD algorithm.14th IEEE Proceedings On Personnal, Indoor and Mobile Radio Communications,2003, vol.3, pp.2271-2275
[22]W. H. Chin, A. G. Constantinides, and D. B. Ward. Parallel multistage detection for multiple attennas wireless systems. Electronics Letters,2002, vol.38, no.12, pp.597-599
[23]F. Wang, Y. Xiong, and X. M. Yang. Approximate ML detection based on MMSE for MIMO communication systems. Progress in Electromagnetics Research Symposium,2007, vol.3, no.4, pp.475-480
[24]D. W. Waters, J. R. Barry. The chase family of detection algorithm for multi-input multi-output channels. IEEE Transactions on Signal Processing,2008, vol.56, no.2, pp. 739-747
[25]L. Yang, M. Chen, S. X. Cheng, et al.. Combined maximum likelihood and ordered successive interference cancellation grouped detection algorithm for multistream MIMO ISSSTA'2004,2004. pp.250-254
[26]D. Wubben, R. Bohnke, J. Rinas, et al.. Efficient algorithm for decoding layered space-time codes. Electronics Letters,2001, vol.37, pp.1248-1350
[27]孙艳华,吴伟陵.基于QR分解V-BLAST检测算法研究与比较.无线电工程,2006,36(12)：26-29
[28]W. J. Choi, R. Negi, and J. M. Cioffi. Combined ML and DFE for the V-BLAST system. IEEE International Conference on Communications,2002, vol.3, pp.1243-1248
[29]D.W.Waters,J.R.Barry.The sorted-QR chase detector for multi-input multi-output channels.2005 IEEE Wireless.Communications and Networking Conference,2005,Vol.1,pp. 538-543
[30]游月辉.MIMO通信系统信号检测技术研究：[硕士学位论文].大连：大连理工大学信号与信息处理专业.2009
[31]B.Hassibi,H.Vikalo.On the sphere-decoding algorithm Ⅰ:expected camplexity IEEE Trans.Signa,Process,2005,Vol.53,no.8,pp.2806-2818
[32]A.M.Chan,I.Lee.A new reduced-complexity sphere decoder for multiple antenna systems.IEEE International,Conference on Communications,2002,vol.1,pp.460-464
1331 C.P.Schnorr,M.Euchner.Lattice basis reduction:Improved practical algorithms and solving subset sum problems.Mathematical Programming,1994,Vol.66,pp.181-199
[34]U.Fincke,M.Phost.Improved methods for calculating vectors of short length in a lattice,including a camplexity analysis.Mathemalics of Computiation,1985,vol.44,pp.463-471
[35]A.Ghaderipoor,C.Tellambura.A statistical pruning strategy for Schnorr-Euchner sphere decoding.IEEE Commun.Lett.,2008,vol.12,no.2,pp.121-123
[36]Q.L.Liu,L.X.Yang.A novel method for initial radius selection of sphere decoding. 2004 IEEE 60th Vehicular Technology Conference,2004,vol.2,1280一1283
[37]邹涵MIMO系统中的球形检测算法：[硕士学位论文].北京：北京交通大学信号与信息处理专业.2009
[38]T.Takahashi,T.Fukuda,C.K.Sun,et al..An appropriate radius for reduced-complexity sphere decoding.ICCCAS'2010,2010,pp.41-44
[39]陈云杰,吴耀军等.基于MIMO系统的球形译码算法的改进.通信技术,2010,43(6)： 24-28
[40]W.Xu,J.Jiang,et al..An effcient tree search algorithm for optimal detection of MIMO signals with channel estimation errors.2004 IEEE 60th Vehicular Technology Conference,2004,Vol.2,1503-1507
[41]S.M.Razavizadeh,V.T.Vakili,and P.Azmi.A new faster sphere decoder for MIMO systems.Signal Processing and Information Technology,2003,pp.86-89
[42]B.Hassibi,H.Vikalo.On the expected camplexity of integer least-squares problems. In Pro.IEEE ICASSP,2002,Vol.2,pp.1497-1500
[43]Y.Hnang,P.M.Djuric.Multiuser detection of synchronous CDMA signals by the Gibbs coupler.In Pro.IEEE ICASSP,2001,Vol.4,pp.2273-2276
[44]Q. W. Li, Z. F. Wang. Improved K-BEST sphere decoding algorithm for MIMO systems. IEEE ISCAS'06,2006, pp.1159-1162
[45]贾龙直,李兆训.多入多出系统中改进的QRD-M检测算法.计算机工程,2011,37(3)：77-79