室内MIMO关键技术研究
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摘要
本文研究了MIMO系统信道间的空间相关性对信道容量的影响,分析了天线间距和角度扩展等参数与空间相关性大小的关系,而这些所得结论对MIMO技术在室内环境中更好的应用具有指导意义。本文还涉及了MIMO系统接收端检测算法的性能仿真分析,为进一步提出高效低复杂度的检测算法提供理论依据。
首先,本文基于相关矩阵法建立了一种MIMO信道空间相关模型,该模型主要考虑了两种空间信道参数,一个是以角度功率谱来描述的角度扩展,另一个是天线间距。从仿真结果可以得出,在瑞利衰落信道下,天线之间的相关系数与天线间距、到达波的角度扩展有着直接的关联,一般地,天线间距越大,达波角度扩展越宽,则相关系数越小,反之则相关系数越大,而较大的空间相关性会引起信道容量的损失。
其次,本文讨论了一种小尺度衰落的室内MIMO信道模型:直射路径与散射路径共存的莱斯衰落信道,通过仿真对该模型的性能进行了预测,分析了直射分量、散射分量、以及莱斯因子对信道容量的影响,得出在直射矩阵低秩的信道下,随着莱斯因子值的增大,MIMO系统的信道容量降低。
最后,对MIMO系统中最具代表性的垂直分层空时编码系统进行了介绍,并仿真分析了该系统几种检测算法性能。在假设理想信道估计下,得出最大似然算法检测性能最优,但其算法复杂度比较高,很难在实际中应用;基于迫零、最小均方误差准则算法的复杂度比较低,但它们的检测性能却较差;而基于串行干扰消除思想的迫零、最小均方误差算法的性能和复杂度就比较适中,而且当收发天线数都为4时,这两种算法的性能都要好于收发天线数为2的情况。
This paper studies on the spatial correlation between channel and channel capacity in MIMO wireless system, analyzes the relationship between spatial correlation and several parameters, such as angle spread, antenna spacing. And these conclusions have guiding significance for better application of MIMO technology in indoor environment. This paper has also covered the performance simulation analysis of the receiver detection algorithm in MIMO system, this provides theoretical basis to further put forward the high efficient and low complexity algorithm.
First, this paper establishes a kind of MIMO spatial correlation channel model based on correlation matrix method. The model considers the two main space channel parameters, one is angle spread (AS) that is described with power azimuth spectrum (PAS), the other is antenna spacing. From the simulation results can conclude, under Rayleigh fading channel, the correlation coefficient between antennas is directly related to antenna spacing and angle spread. Generally, the greater angle spread and antenna spacing, the smaller correlation coefficient, in contrast, the greater correlation coefficient, and the larger spatial correlativity can cause channel capacity loss.
Secondly, the paper discusses a small scale decline indoor MIMO channel models: Rice fading channel, which includes LOS (line-of-sight) and NLOS (non line-of-sight) propagation environment. Through the simulation predicts the performance of the model, and analyzes the direct component, scattering component, and rice factors on the influence of channel capacity. With the increase of rice factor value, channel capacity of MIMO system reduces under low-rank channel matrix of direct component.
Finally, V-BLAST (Vertical Bell Laboratories Layered Space-Time coding) system is introduced, which is the most representative in MIMO system, and this paper analyzes several detection algorithm performance by Matlab simulation. Assuming that under ideal channel estimation, Maximum likelihood (ML) algorithm has optimal detection performance, but it also has high algorithm complexity, so it is difficult for the application in practice. Although algorithm complexity based on zero forcing (ZF) and minimum mean square error (MMSE) rule is lower, but their detection performance is poor. And performance and complexity of detection algorithm based on serial interference cancellation (SIC) thought are moderate. When the number of sending and receiving antenna is four, the performance of this algorithm is better than the number of sending and receiving antenna is two.
首先,本文基于相关矩阵法建立了一种MIMO信道空间相关模型,该模型主要考虑了两种空间信道参数,一个是以角度功率谱来描述的角度扩展,另一个是天线间距。从仿真结果可以得出,在瑞利衰落信道下,天线之间的相关系数与天线间距、到达波的角度扩展有着直接的关联,一般地,天线间距越大,达波角度扩展越宽,则相关系数越小,反之则相关系数越大,而较大的空间相关性会引起信道容量的损失。
其次,本文讨论了一种小尺度衰落的室内MIMO信道模型:直射路径与散射路径共存的莱斯衰落信道,通过仿真对该模型的性能进行了预测,分析了直射分量、散射分量、以及莱斯因子对信道容量的影响,得出在直射矩阵低秩的信道下,随着莱斯因子值的增大,MIMO系统的信道容量降低。
最后,对MIMO系统中最具代表性的垂直分层空时编码系统进行了介绍,并仿真分析了该系统几种检测算法性能。在假设理想信道估计下,得出最大似然算法检测性能最优,但其算法复杂度比较高,很难在实际中应用;基于迫零、最小均方误差准则算法的复杂度比较低,但它们的检测性能却较差;而基于串行干扰消除思想的迫零、最小均方误差算法的性能和复杂度就比较适中,而且当收发天线数都为4时,这两种算法的性能都要好于收发天线数为2的情况。
This paper studies on the spatial correlation between channel and channel capacity in MIMO wireless system, analyzes the relationship between spatial correlation and several parameters, such as angle spread, antenna spacing. And these conclusions have guiding significance for better application of MIMO technology in indoor environment. This paper has also covered the performance simulation analysis of the receiver detection algorithm in MIMO system, this provides theoretical basis to further put forward the high efficient and low complexity algorithm.
First, this paper establishes a kind of MIMO spatial correlation channel model based on correlation matrix method. The model considers the two main space channel parameters, one is angle spread (AS) that is described with power azimuth spectrum (PAS), the other is antenna spacing. From the simulation results can conclude, under Rayleigh fading channel, the correlation coefficient between antennas is directly related to antenna spacing and angle spread. Generally, the greater angle spread and antenna spacing, the smaller correlation coefficient, in contrast, the greater correlation coefficient, and the larger spatial correlativity can cause channel capacity loss.
Secondly, the paper discusses a small scale decline indoor MIMO channel models: Rice fading channel, which includes LOS (line-of-sight) and NLOS (non line-of-sight) propagation environment. Through the simulation predicts the performance of the model, and analyzes the direct component, scattering component, and rice factors on the influence of channel capacity. With the increase of rice factor value, channel capacity of MIMO system reduces under low-rank channel matrix of direct component.
Finally, V-BLAST (Vertical Bell Laboratories Layered Space-Time coding) system is introduced, which is the most representative in MIMO system, and this paper analyzes several detection algorithm performance by Matlab simulation. Assuming that under ideal channel estimation, Maximum likelihood (ML) algorithm has optimal detection performance, but it also has high algorithm complexity, so it is difficult for the application in practice. Although algorithm complexity based on zero forcing (ZF) and minimum mean square error (MMSE) rule is lower, but their detection performance is poor. And performance and complexity of detection algorithm based on serial interference cancellation (SIC) thought are moderate. When the number of sending and receiving antenna is four, the performance of this algorithm is better than the number of sending and receiving antenna is two.
引文
[1]林云,何丰. MIMO技术原理及应用.北京:人民邮电出版社,2010
[2] Stefania Sesia, Issam Toufik, Matthew Baker. LTE—The UMTS Long Term Evolution from Theory to Practice. 2009
[3]沈嘉,索士强等. 3GPP长期演进(LTE)技术原理与系统设计.北京:人民邮电出版社,2008
[4]张传福,彭灿等. TD-SCDMA通信网络规划与设计.北京:人民邮电出版社,2009
[5]鲍欣欣. MIMO无线信道建模与仿真研究:[学位论文].西安:西安电子科技大学,2009
[6]朱敏. MIMO-OFDM系统中的信道估计及信号检测技术研究:[学位论文].南京:东南大学,2005
[7]刘宇畅. MIMO信道关键技术研究与建模:[学位论文].成都:电子科技大学,2008
[8]徐晓军. MIMO无线信道建模与仿真:[学位论文].成都:电子科技大学,2006
[9]孙岩.无线通信系统中的MIMO信道建模及其空时相关特性研究:[学位论文].西安:西安电子科技大学,2008
[10] A.Abdi, M.Kaveh. A space-time correlation model for multilement antenna systems in mobile fading channels[J]. IEEE Journal on Selected Areas in Communications, 2002,20(3):550-560
[11] K.Yu, M.Bengtsson, B.Ottersten,et al. Second order statistics of NLOS indoors MIMO channels based on 5.2GHz measurements. Proc. IEEE Global Telecommun,Con.f. Nov.2001,156-160
[12] D.Chizhik, F.R.Farroklli, J.Li,et al. Effect of antenna separation on the capacity of BLAST in correlated channels[J]. IEEE Commun Letters, Apri 4(11):337-339
[13] D.Gesbert, H.Bolcskei, D.A.Gore,et al. Outdoor MIMO wireless channels models and Performance Prediction[J]. IEEE Trans Commum,Dec,2002,50(12):1926-1934
[14] 3GPP Technical Specification 25.996. Spatial Channel Model for Multiple Input Multiple Output (MIMO) Simulations (Release 6). www.3gpp.org
[15] D.S.Baum, J.Salo, G..Del Galdo,et al. An Interim Channel Model for Beyond-3G Systems. IEEE Vehicular Technology Conference (Stockholm, Sweden), 2005(5)
[16] Commission of the European Communities. IST-WINNERⅡproject deliverable D1.1.2, WINNERⅡChannel Models. www.ist-winner.org
[17] Agilent Technologies,‘R4-071318: LTE MIMO Correlation Matrices’, 2007(8)
[18] Stefania Sesia, Lssam Toufik, Matthew Baker.马霓,邬钢,张晓博,张学军译. LTE—UMTS长期演进理论与实践.北京:人民邮电出版社,2009
[19]刘蕾蕾,洪伟. LOS环境下散射体对MIMO信道特性的影响.通信学报,Vol.30,No. 2,2009
[20]孙艳华.无线通信中多天线系统检测技术研究:[学位论文].北京:北京邮电大学,2006
[21]李忻.新一代无线通信系统中的MIMO信道建模与多天线设计研究:[学位论文].成都:电子科技大学,2005
[22] K.I.Pederson, P.E.Mogensen, B.H.Fleury. Spatial channel characteristics in outdoor environments and their impact on BS antenna system performance. Proceedings of IEEE VTC1998, Vol.2:719-723
[23] Ericsson, Elektrobit, Nokia, Motorola, Siemens. R4-060334: LTE Channel Models and Simulations. www.3gpp.org, 3GPP TSG RAN WG4, meeting 38, Denver, USA,2006(2)
[24] Jean P, Kermoal, Measurement. Modeling and Performance Evaluation of the MIMO Radio Channel. [Ph.D thesis]. Aalborg University, Denmark,2002
[25] M.Patzold. Mobile Fading Channels. John Wiley&Sons. Ltd,2002
[26] J.P.Kermoal, L.Schumacher, K.I.Pedersen,et al. A stochastic MIMO radio channel model with experimental validation. IEEE Journal on Selected Areas in Communications, August 2002,20(6):1211-1226
[27]黄滔. MIMO信道模型的研究:[学位论文].无锡:江南大学,2005
[28] LIU L L, HONG W. Characterization of line-of-sight MIMO channel for fixed wireless communications[J].IEEE Antennas and Wireless Propagation Letters.2007,6:36-39
[29]赵谦.无线MIMO系统的容量及信道估计算法的研究:[学位论文].西安:西安科技大学,2005
[30] G.D.Golden, C.J.Foschini,et al. Detection algorithm and initial laboratory results using V-BLAST space-time communication architecture[J]. IEEE lec. Letters, 1999, 35(1): 6-7
[31] Branka Vucetic, Jinhong Yuan,王晓海等译.空时编码技术.北京:机械工业出版社,2004
[32] Tarokh V, Jafarkhani H, Calderbank A.R. Space-time block codes from orthogonal designs[J]. IEEE Trans Inform Theory, 1998, 45: 1456-1467
[33] Vahid Tarokh, Nambi Seshadri, A.R.Calderbank. Space-Time Codes for High Data Rate Wireless Communications: Performance Criterion and Code Construction. IEEE Transactions on Information Theory, vol.44,Mar.1998,pp.744-765
[34]王文博,郑侃.宽带无线通信OFDM技术.北京:人民邮电出版社,2003
[35]周燕琳.频率选择性信道下MIMO检测和预编码技术的研究:[学位论文].成都:电子科技大学,2006
[36] Paulraj A,et al. Introduction to space-time wireless communications. Cambridge University Press,2003
[37]朱彦军. MIMO信道中分层空时信号检测技术研究:[学位论文].昆明:昆明理工大学,2007
[38] S.Haykin. Adaptive Filter Theory. Prentice-Hall,Inc., Englewood Clifs, NJ, USA,4th edition,2001
[39] W.H.Chin, A.G.Constantinides and D.B.Ward. Parallel multistage detection for multiple antenna wireless systems[J]. Electronics Letters, Vol.38, June 2002, pp.597-598
[40]郑珊珊,陈霞,谈振辉. V-BLAST系统检测算法的比较.无线通信技术,2006(4)
[41] P.W.Wolniansky, G.J.Foschini, G.D.Golden,et al. V-BLAST: An Architecture for Realizing Very High Data Rates Over the Rich-Scattering Wireless Channel. Italy: in Proc.ISSE,Pisa,Sepetember 1998
[42] D.Wubben, J.Rohnke. Efficient Algorithm for Decoding Layered Space-Time Codes[J]. IEEE Electronic Letters, October 2001,37(22):1348-1350
[43] S.Baro, G.Bauch, A.Pavlic,et, al. Improving BLAST Performance using Space-Time Block Codes and Turbo Decoding. San Francisco: in Proc, IEEE Globecom 2000,CA, November 2000
[44]王利勇. MIMO检测算法的研究与实现:[学位论文].西安:西安电子科技大学,2010
[45]贾芬. MIMO信道容量和检测算法研究:[学位论文].太原:太原理工大学,2009
[46]李丹. MIMO检测算法研究及其在WIMAX系统中的应用:[学位论文].西安:西安电子科技大学,2009
[2] Stefania Sesia, Issam Toufik, Matthew Baker. LTE—The UMTS Long Term Evolution from Theory to Practice. 2009
[3]沈嘉,索士强等. 3GPP长期演进(LTE)技术原理与系统设计.北京:人民邮电出版社,2008
[4]张传福,彭灿等. TD-SCDMA通信网络规划与设计.北京:人民邮电出版社,2009
[5]鲍欣欣. MIMO无线信道建模与仿真研究:[学位论文].西安:西安电子科技大学,2009
[6]朱敏. MIMO-OFDM系统中的信道估计及信号检测技术研究:[学位论文].南京:东南大学,2005
[7]刘宇畅. MIMO信道关键技术研究与建模:[学位论文].成都:电子科技大学,2008
[8]徐晓军. MIMO无线信道建模与仿真:[学位论文].成都:电子科技大学,2006
[9]孙岩.无线通信系统中的MIMO信道建模及其空时相关特性研究:[学位论文].西安:西安电子科技大学,2008
[10] A.Abdi, M.Kaveh. A space-time correlation model for multilement antenna systems in mobile fading channels[J]. IEEE Journal on Selected Areas in Communications, 2002,20(3):550-560
[11] K.Yu, M.Bengtsson, B.Ottersten,et al. Second order statistics of NLOS indoors MIMO channels based on 5.2GHz measurements. Proc. IEEE Global Telecommun,Con.f. Nov.2001,156-160
[12] D.Chizhik, F.R.Farroklli, J.Li,et al. Effect of antenna separation on the capacity of BLAST in correlated channels[J]. IEEE Commun Letters, Apri 4(11):337-339
[13] D.Gesbert, H.Bolcskei, D.A.Gore,et al. Outdoor MIMO wireless channels models and Performance Prediction[J]. IEEE Trans Commum,Dec,2002,50(12):1926-1934
[14] 3GPP Technical Specification 25.996. Spatial Channel Model for Multiple Input Multiple Output (MIMO) Simulations (Release 6). www.3gpp.org
[15] D.S.Baum, J.Salo, G..Del Galdo,et al. An Interim Channel Model for Beyond-3G Systems. IEEE Vehicular Technology Conference (Stockholm, Sweden), 2005(5)
[16] Commission of the European Communities. IST-WINNERⅡproject deliverable D1.1.2, WINNERⅡChannel Models. www.ist-winner.org
[17] Agilent Technologies,‘R4-071318: LTE MIMO Correlation Matrices’, 2007(8)
[18] Stefania Sesia, Lssam Toufik, Matthew Baker.马霓,邬钢,张晓博,张学军译. LTE—UMTS长期演进理论与实践.北京:人民邮电出版社,2009
[19]刘蕾蕾,洪伟. LOS环境下散射体对MIMO信道特性的影响.通信学报,Vol.30,No. 2,2009
[20]孙艳华.无线通信中多天线系统检测技术研究:[学位论文].北京:北京邮电大学,2006
[21]李忻.新一代无线通信系统中的MIMO信道建模与多天线设计研究:[学位论文].成都:电子科技大学,2005
[22] K.I.Pederson, P.E.Mogensen, B.H.Fleury. Spatial channel characteristics in outdoor environments and their impact on BS antenna system performance. Proceedings of IEEE VTC1998, Vol.2:719-723
[23] Ericsson, Elektrobit, Nokia, Motorola, Siemens. R4-060334: LTE Channel Models and Simulations. www.3gpp.org, 3GPP TSG RAN WG4, meeting 38, Denver, USA,2006(2)
[24] Jean P, Kermoal, Measurement. Modeling and Performance Evaluation of the MIMO Radio Channel. [Ph.D thesis]. Aalborg University, Denmark,2002
[25] M.Patzold. Mobile Fading Channels. John Wiley&Sons. Ltd,2002
[26] J.P.Kermoal, L.Schumacher, K.I.Pedersen,et al. A stochastic MIMO radio channel model with experimental validation. IEEE Journal on Selected Areas in Communications, August 2002,20(6):1211-1226
[27]黄滔. MIMO信道模型的研究:[学位论文].无锡:江南大学,2005
[28] LIU L L, HONG W. Characterization of line-of-sight MIMO channel for fixed wireless communications[J].IEEE Antennas and Wireless Propagation Letters.2007,6:36-39
[29]赵谦.无线MIMO系统的容量及信道估计算法的研究:[学位论文].西安:西安科技大学,2005
[30] G.D.Golden, C.J.Foschini,et al. Detection algorithm and initial laboratory results using V-BLAST space-time communication architecture[J]. IEEE lec. Letters, 1999, 35(1): 6-7
[31] Branka Vucetic, Jinhong Yuan,王晓海等译.空时编码技术.北京:机械工业出版社,2004
[32] Tarokh V, Jafarkhani H, Calderbank A.R. Space-time block codes from orthogonal designs[J]. IEEE Trans Inform Theory, 1998, 45: 1456-1467
[33] Vahid Tarokh, Nambi Seshadri, A.R.Calderbank. Space-Time Codes for High Data Rate Wireless Communications: Performance Criterion and Code Construction. IEEE Transactions on Information Theory, vol.44,Mar.1998,pp.744-765
[34]王文博,郑侃.宽带无线通信OFDM技术.北京:人民邮电出版社,2003
[35]周燕琳.频率选择性信道下MIMO检测和预编码技术的研究:[学位论文].成都:电子科技大学,2006
[36] Paulraj A,et al. Introduction to space-time wireless communications. Cambridge University Press,2003
[37]朱彦军. MIMO信道中分层空时信号检测技术研究:[学位论文].昆明:昆明理工大学,2007
[38] S.Haykin. Adaptive Filter Theory. Prentice-Hall,Inc., Englewood Clifs, NJ, USA,4th edition,2001
[39] W.H.Chin, A.G.Constantinides and D.B.Ward. Parallel multistage detection for multiple antenna wireless systems[J]. Electronics Letters, Vol.38, June 2002, pp.597-598
[40]郑珊珊,陈霞,谈振辉. V-BLAST系统检测算法的比较.无线通信技术,2006(4)
[41] P.W.Wolniansky, G.J.Foschini, G.D.Golden,et al. V-BLAST: An Architecture for Realizing Very High Data Rates Over the Rich-Scattering Wireless Channel. Italy: in Proc.ISSE,Pisa,Sepetember 1998
[42] D.Wubben, J.Rohnke. Efficient Algorithm for Decoding Layered Space-Time Codes[J]. IEEE Electronic Letters, October 2001,37(22):1348-1350
[43] S.Baro, G.Bauch, A.Pavlic,et, al. Improving BLAST Performance using Space-Time Block Codes and Turbo Decoding. San Francisco: in Proc, IEEE Globecom 2000,CA, November 2000
[44]王利勇. MIMO检测算法的研究与实现:[学位论文].西安:西安电子科技大学,2010
[45]贾芬. MIMO信道容量和检测算法研究:[学位论文].太原:太原理工大学,2009
[46]李丹. MIMO检测算法研究及其在WIMAX系统中的应用:[学位论文].西安:西安电子科技大学,2009