MIMO无线信道建模与仿真
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摘要
多入多出(MIMO)技术被认为是现代通信技术中的重大突破之一,越来越成为无线通信领域的研究热点。MIMO技术是未来无线通信系统中实现高数据速率传输、改善传输质量、提高系统容量的重要途径。目前,MIMO技术已经在宽带无线接入、3G、B3G等无线通信系统中得到了广泛的应用。然而,MIMO无线系统大容量的实现和其它性能的提高极大地依赖于MIMO无线信道的特性;同时,研究基于MIMO的各种关键技术和处理算法也需要建立MIMO信道的模型,进行相应的仿真,以便评估各种处理算法的优劣和系统性能的好坏。基于上述原因,本文研究了现有应用环境下MIMO无线通信系统的信道建模理论与方法,综合了一个宽带统计MIMO无线信道模型,可以作为研究MIMO无线通信系统的一个通用空时信道模型。分别建立了3GPP、IEEE802.16、IEEE802.11n和分布式MIMO系统的MIMO信道基于Synopsys’COSSAP?的仿真平台,进行了大量的计算机仿真,得出了一批有用的仿真结果,对仿真结果进行了分析比较。本文的主要内容概括如下:
在绪论中,简述了本文的研究背景和意义,总结了MIMO无线信道建模的研究现状,指出了还存在的问题,指明了本文的研究动机和出发点。
在本文的前半部分(第二章),进一步总结了现有的MIMO无线衰落信道模型和建模方法。并在此基础上,根据发射端和接收端天线的阵列结构、发射信号的离开角与角度扩展、接收信号的到达角与角度扩展、角度功率谱、多普勒功率谱和信道的功率时延分布等参数,综合了一个统计MIMO无线信道模型。讨论了对相关性建模的等效形式和对视距路径传播的建模方法。还详细描述了基于三种常见的角度功率谱计算信道相关系数的问题。最后,基于该统计MIMO信道模型,提出了一种分布式MIMO系统的信道模型,该信道模型综合考虑了小尺度衰落、大尺度路径损耗和阴影效应,同时也考虑了天线元之间的空间相关性,能够比较全面的反映分布式MIMO系统的信道特性,符合实际的应用环境。
本文的后半部分(第三章和第四章)详细阐述了对所提出的统计MIMO信道模型进行计算机仿真的问题。首先详细讨论了仿真设计的思路、方法、仿真处理流程和相关衰落系数的产生,并针对3GPP、IEEE802.16、IEEE802.11n以及分布式
The Multiple-Input Multiple-Output (MIMO) technology is considered as one of the most promising breakthrough technology to improve system performance, enhance the capacity and spectrum efficiency. The MIMO technology has been already used in such systems as 3G, B3G and broadband wireless access. Although, the high performance promised by MIMO technology is highly dependent on the propagation channels. Meanwhile, we need to establish MIMO radio channel models and corresponding simulations to research key technologies and algorithms in MIMO systems and to evaluate the system performance. Based on such reasons, in this dissertation, some research on MIMO radio channel modeling was done, and we proposed a stochastic MIMO channel model which could serve as a generalized MIMO radio channel model in MIMO technology research. The computer-aided simulation models of MIMO radio channels in 3GPP, IEEE802.16, IEEE802.11n and distributed MIMO systems were established. A lot of simulation results were obtained based on these simulation models, and some analyses and comparison of the results were made. The main contents of this dissertation are expressed as follows:
In the first chapter, we introduced the background and the significance of the research in this dissertation as well as the state-of-the-art in MIMO radio channel modeling. Some concentrated problems and fundamental questions were also pointed out.
In the former part (chapter two) of the dissertation, further conclusions on MIMO radio channel modeling were made. Then, based on the existing methods of MIMO wireless channel modeling and a variety of present MIMO wireless channel models, we integrated a wideband MIMO channel model. It’s of stochastic type and uses the angle of arrival, angle of departure, azimuth spread, the topology of both transmitter and receiver, the Doppler spectrum, the power delay profile, etc. as its parameters. And we discussed an equivalent method to model the spatial correlation of MIMO channel. We also described the definition and the calculation of spatial correlation coefficient of MIMO channel based on three common power azimuth spectrums in detail. At the end
在绪论中,简述了本文的研究背景和意义,总结了MIMO无线信道建模的研究现状,指出了还存在的问题,指明了本文的研究动机和出发点。
在本文的前半部分(第二章),进一步总结了现有的MIMO无线衰落信道模型和建模方法。并在此基础上,根据发射端和接收端天线的阵列结构、发射信号的离开角与角度扩展、接收信号的到达角与角度扩展、角度功率谱、多普勒功率谱和信道的功率时延分布等参数,综合了一个统计MIMO无线信道模型。讨论了对相关性建模的等效形式和对视距路径传播的建模方法。还详细描述了基于三种常见的角度功率谱计算信道相关系数的问题。最后,基于该统计MIMO信道模型,提出了一种分布式MIMO系统的信道模型,该信道模型综合考虑了小尺度衰落、大尺度路径损耗和阴影效应,同时也考虑了天线元之间的空间相关性,能够比较全面的反映分布式MIMO系统的信道特性,符合实际的应用环境。
本文的后半部分(第三章和第四章)详细阐述了对所提出的统计MIMO信道模型进行计算机仿真的问题。首先详细讨论了仿真设计的思路、方法、仿真处理流程和相关衰落系数的产生,并针对3GPP、IEEE802.16、IEEE802.11n以及分布式
The Multiple-Input Multiple-Output (MIMO) technology is considered as one of the most promising breakthrough technology to improve system performance, enhance the capacity and spectrum efficiency. The MIMO technology has been already used in such systems as 3G, B3G and broadband wireless access. Although, the high performance promised by MIMO technology is highly dependent on the propagation channels. Meanwhile, we need to establish MIMO radio channel models and corresponding simulations to research key technologies and algorithms in MIMO systems and to evaluate the system performance. Based on such reasons, in this dissertation, some research on MIMO radio channel modeling was done, and we proposed a stochastic MIMO channel model which could serve as a generalized MIMO radio channel model in MIMO technology research. The computer-aided simulation models of MIMO radio channels in 3GPP, IEEE802.16, IEEE802.11n and distributed MIMO systems were established. A lot of simulation results were obtained based on these simulation models, and some analyses and comparison of the results were made. The main contents of this dissertation are expressed as follows:
In the first chapter, we introduced the background and the significance of the research in this dissertation as well as the state-of-the-art in MIMO radio channel modeling. Some concentrated problems and fundamental questions were also pointed out.
In the former part (chapter two) of the dissertation, further conclusions on MIMO radio channel modeling were made. Then, based on the existing methods of MIMO wireless channel modeling and a variety of present MIMO wireless channel models, we integrated a wideband MIMO channel model. It’s of stochastic type and uses the angle of arrival, angle of departure, azimuth spread, the topology of both transmitter and receiver, the Doppler spectrum, the power delay profile, etc. as its parameters. And we discussed an equivalent method to model the spatial correlation of MIMO channel. We also described the definition and the calculation of spatial correlation coefficient of MIMO channel based on three common power azimuth spectrums in detail. At the end
引文
[1] 尤肖虎, 曹淑敏, 傅学群. 我国未来移动通信研究开发展望. 电信科学,2002 年 08 期:26-29
[2] W. W. Lu. 4G research in Asia. IEEE Communications Magazine, March 2003:104-106
[3] 陈如明. 3G 新发展及 3G/3G 演进策略思考. 中国无线电,2005 年 01 期:2-8
[4] 朱近康. 对 3G 和后 3G 发展的思考. 移动通信,2003 年 7 月:42-45
[5] 张平. 第四代移动通信系统的关键技术及分析. 电信科学,2002 年 08 期:30-34
[6] 李少谦,王军. 宽带无线接入技术发展展望. 通讯世界,2002 年 12 期:61-64
[7] T. S. Rappaport, A. Annamalai, R. M. Buehre, et al. Wireless Communications: Past Events and a Future Perspective. IEEE Communications Magazine, May 2002, Vol.40, Issue 5:148-161
[8] A. C. Chen. Overview of code division multiple access technology for wireless communications. IEEE IECON1998 September, Vol.1:T15-T24
[9] F. B. Frederiksen, R. Prasad. An overview of OFDM and related techniques towards development of future wireless multimedia communications. IEEE RAWCON2002 August:19-22
[10] R. H. Roy. An overview of smart antenna technology: the next wave in wireless communications. IEEE Proceedings of Aerospace Conference, March 1998, Vol.3:339-345
[11] Liuqing Yang, Georgios B. Giannakis. Ultra-Wideband Communications-An Idea Whose Time Has Come. IEEE Signal Processing Magazine, November 2004, Vol.21, Issue 6:26-54
[12] D. Gesbert, M. Shafi, Da-shan Shiu, et al. From theory to practice: an overview of MIMO space-time coded wireless systems. IEEE Journal on Selected Areas in Communications, April 2003, Vol.21, No.3:281-302
[13] A. J. Paulraj, D. A. Gore, R. U. Nabar, et al. An overview of MIMO communications-A key to gigabit wireless. Proceedings of IEEE, February 2004, Vol.92, No.2:198-218
[14] J. Mitola. The software radio architecture. IEEE Communications Magazine, May 1995, Vol.33, Issue 5:26-38
[15] Simon Haykin. Cognitive Radio: Brain-Empowered Wireless Communications. IEEE Journal on Selected Areas in Communications, February 2005, Vol.23, No.2:201-220
[16] A. J. Paulraj, R. U. Nabar, D. A. Gore. Introduction to space-time wireless communications, Cambridge University Press, 2002
[17] S. Alamouti. Space block coding: a simple transmitter diversity technique for wireless communications. IEEE Journal on Selected Areas in Communications, October 1998, Vol.16:1451-1458
[18] G. J. Foschini. Layered space-time architecture for wireless communications in a fading environment when using multi-element antennas. Bell Labs Technical Journal, Autumn 1996:41-59
[19] L. Zheng, and D. N. C. Tse, Diversity and multiplexing: A fundamental tradeoff in multiple-antenna channels, IEEE Transactions on Information Theory, 2003, Vol.49, No.5:1073~1096
[20] 武刚. 多入多出无线通信中的信道模型、空时编码及关键技术研究: [博士学位论文], 成都: 电子科技大学 2004
[21] 3GPP TSG R1-01-1305. MIMO channel measurement and modeling results., Qualcomm, November, 2001
[22] 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, Vol.20, No.6:1211~1226
[23] J.W. Wallace, M.A. Jensen, A. L. Swindlehurst, et al. Experimental characterization of the MIMO wireless channel: Data acquisition and analysis. IEEE Transactions on Wireless Communications, 2003, Vol.2, No.2:335~343
[24] T. Zwick, D. Hampicke, J. Maurer, et al. Results of double-directional channel sounding measurements. Procedings of IEEE 51th VTC2001. Spring:2497~2503
[25] R. Stridh and B. Ottersten. Spatial characterization of indoor radio channel measurements at 5GHz. Proceedings of 1st IEEE Sensor Array and Multichannel Signal Processing Workshop, Boston, MA, USA, 2000
[26] C. C. Martin, J. H. Winters, N. R. Sollenberg. Multiple-input multiple-output (MIMO) radio channel measurements. Proceedings of IEEE VTC2000, Fall, Boston, USA: 774~779
[27] D. Chizhik, J. Ling, P. W. Wolniansky, et al. Multiple-input-multiple-output measurements and modeling in Manhattan. IEEE Journal on Selected Areas in Communications, 2003, Vol.21, No.3:321~331
[28] Kai Yu, B. Ottersten. Models for MIMO propagation channels - A review. Wiley Journal on Wireless Communications and Mobile Computing, 2002, Vol.2, No.7:653~666.
[29] A. F. Molisch. A generic model for MIMO wireless propagation channels in macro- and microcells. IEEE Transactions on Signal Processing, January 2004, Vol.52, No.1:61-71
[30] Hao Xu, Dmitry Chizhik, Howard Huang, et al. A generalized space-time multiple-input multiple-output(MIMO) channel model. IEEE Transactions on Wireless Communications, May 2004, Vol.3, No.3:966-975
[31] M. Patzold. Mobile Fading Channels. John Wiley & Sons, Ltd., 2002
[32] 杨大成. 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
[33] A. G. Burr. Evaluation of capacity of indoor wireless MIMO channel using ray tracing. Proceedings of Inter. Zurich Seminar, Zurich, Switzerland, 2002: 281~286
[34] C. Oestges, V. Erceg, A. J. Paulraj. A physical scattering model for MIMO macrocellular broadband wireless channels, IEEE Journal on Selected Areas in Communications, 2003,Vol.21, No.5:721~729
[35] D. Chizhik, G. J. Foschini, M. J. Gans et al. Keyholes, correlations, capacities of multielement transmit and receive antennas. IEEE Transactions on Wireless Communications, 2002, Vol.1, No.2:361~368
[36] A. Abdi and M. Kaveh. A space-time correlation model for multielement antenna systems in mobile fading channels. IEEE Journal on Selected Areas in Communications,2002, Vol.20, No.3:550~560
[37] M. Steinbauer, A. F. Molisch, E. Bonek. The Double-Directional Channel Model. IEEE Antennas and Propagation Magazine, 2001,Vol.43, Issue 8:51~63
[38] M. Stege, J. Jelitto, M. Bronzel, G. Fettweis. A multiple-input multiple-output channel model for simulation of Tx- and Rx-diversity wireless systems. in Proc. IEEE VTC2000, Fall, Boston, MA, USA:833~839
[39] C. Chuah, D. Tse, J. Kahn, et al. Capacity scaling in MIMO wireless systems under correlated fading. IEEE Transactions on Information Theory, 2002, Vol.48, No.3:637~650
[40] Theodore S. Rappaport. 无线通信原理与应用(蔡涛,李旭,杜振民 译). 北京:电子工业出版社,1999
[41] Gregory D. Durgin. 空—时无线信道(朱世华,任品毅,王磊, 等译). 西安:西安交通大学出版社,2004
[42] R. B. Ertel, P. Cardieri, K. W. Sowerby, T.S. Rappapor, et al. Overview of Spatial channel models for antenna array communications systems. IEEE Personal Communications Magazine, 1998, Vol.5, Issue1:10~22
[43] D. Shiu, G. Foschini, M. Gans, et al. Fading correlation and its effect on the capacity of multi-element antenna systems. IEEE Transactions on Communications, 2000, Vol.48, No.3:502~513
[44] 3GPP. Micro-cell wideband directional channel model. 3GPP TSG R1-01-0992, 2001
[45] J. Salz, J. Winters. Effect of fading correlation on adaptive arrays in digital mobile radio. IEEE Transactions on Vehicular Technology, Nov. 1994, Vol.43:1049-1057
[46] 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
[47] K. I. Pederson, P. E. Mogensen, B.H. Fleury. A stochastic model of the temporal and azimuthal dispersion seen at the base station in outdoor propagation environments. IEEE Transactions on Vehicular Technology, Mar. 2000, Vol.49:437-447
[48] 3GPP. Spatial Channel Model for MIMO Simulations. 3GPP TR 25.996 V6.1.0, 2003
[49] Q.H. Spencer, et al. Modeling the statistical time and angle of arrival characteristics of an indoor environment. IEEE Journal on Selected Areas in Communications, March 2000, Vol.18, No.3:347-360
[50] IEEE802. TGn Channel Models. IEEE 802.11-03/940r4, 2004
[51] Laurent Schumacher, K. I. Pedersen, P. E. Mogensen. From antenna spacings to theoretical capacities—guidelines for simulating MIMO systems. IEEE PIMRC2002 Sept. Vol.2:587-592
[52] K. I. Pedersen, J. B. Andersen, J. P. Kermoal, et al. A Stochastic Multiple-Input-Multiple-Output Radio Channel Model for Evaluation of Space-Time Coding Algorithms. IEEE VTC2000, Vol.2:893-897
[53] ITU. Recommendation ITU-R M.1225 - Guidelines for Evaluation of Radio Transmission Technologies for IMT-2000. 1997
[54] COST 207. Digital land mobile radio communications. Office for Official Publications of the European Communities, Final Report, Luxembourg. 1989
[55] P. Soma, D.S. Baum, V. Erceg. Analysis and modeling of multiple-input multiple-output (MIMO) radio channel based on outdoor measurements conducted at 2.5 GHz for fixed BWA applications. Proceedings of IEEE ICC2002, Vol.1:272-276
[56] 3GPP. MIMO conference call summary. 3GPP R1-02-0141, January 2002
[57] Jean P. Kermoal. Measurement, Modeling and Performance Evaluation of the MIMO Radio Channel: [Ph.D thesis], Aalborg University, Denmark, 2002
[58] W. C. Y. Lee. Effects on Correlation between Two Mobile Radio Base-Station Antennas. IEEE Transactions on Vehicular Technology, November 1973, Vol.22, No. 4:130–140
[59] F. Adachi, M.T. Feeney, A.G. Williamson, et al. Cross correlation Between the Envelopes of 900 MHz Signals Received at a Mobile Radio Base Station Site. IEE Proceedings, October 1986, Vol.133, No.6:506–512
[60] A.A.M. Saleh, R. A. Valenzuela. A statistical model for indoor multipath propagation. IEEE Journal on Selected Areas in Communications, 1987, Vol.5:128-137
[61] Shidong Zhou, Ming Zhao, Xibin Xu, et al. Distributed wireless communication system: a new architecture for future public wireless access. IEEE Communications Magazine, March 2000, Vol.41, Issue 3:108-113
[62] V. Nikolopoulos, M. Fiacco, S. Stavrou, et al. Narrowband fading analysis of indoor distributed antenna systems. IEEE Antennas and Wireless Propagation Letters, 2003, Vol.2, Issue 1:89-92
[63] Wonil Roh, A. J. Paulraj. MIMO Channel Capacity for the Distributed Antenna Systems. VTC2002 September, Vol.2:24-28
[64] 徐晓军,罗涛,王军, 等. 分布式 MIMO 系统的信道建模. 2005 中国西部青年通信学术会议论文集:321-326
[65] Hongyuan Zhang, Huaiyu Dai. On the Capacity of Distributed MIMO Systems. Conference on Information Sciences and Systems, Princeton University, March 2004
[66] M. Patzold, U. Killat, F. Laue. A deterministic digital simulation model for Suzuki processes with application to a shadowed Rayleigh land mobile radio channel. IEEE Trans. Veh. Technol., 1996, Vol.45, No.2:318~331
[67] M. Patzold, R. Garcia, F. Laue. Design of high-speed simulation models for mobile fading channels by using table look-up techniques, IEEE Trans. Veh. Technol., 2000, Vol.49, No.4:1178~1190
[68] M. Patzold, F. Laue. Level-crossing rate and average duration of fades of deterministic simulation models for Rice fading channels” IEEE Trans. Veh. Tech., 2000, Vol.48, No.4:1121~1129
[69] 3GPP. MIMO discussion summary. 3GPP TSG R1-02-0181, January 2002.
[70] 3GPP. A standardized set of MIMO radio propagation channels. 3GPP TSG R1-01-1179.
[71] IEEE802. Air interface for fixed broadband wireless access systems. IEEE802.16-2004 standard, June 2004
[72] IEEE802. Air interface for fixed and mobile broadband wireless access systems: Amendment for physical and medium access control layers for combined fixed and mobile operation in licensed bands. IEEE P802.16e/D7, April 2005
[73] IEEE802. Channel models for fixed wireless applications IEEE802.16.3c-01/29r4
[74] IEEE802. TGn functional requirements. IEEE802 11-03/813
[75] IEEE802. Sync proposal technical specification. IEEE802.11-04/889r1
[76] P. Melancon, J. Lebel. Effects of fluorescent lights on signal fading characteristics for indoor radio channel. IEEE Electronics Letters, August 1992, Vol.28, No.18:1740-1741
[77] IEEE802. Fluorescent Light-Bulb Interaction with Electromagnetic Signals. IEEE 802.11-03/718r4
[78] G. J. Foschini, M.J. Gans. On limits of wireless communication in a fading environment when using multiple antennas. Wireless Personal Communications, March 1998, Vol.6:311-335
[79] IEEE802. 802.11n channel model validation. IEEE 802.11-03/894r1, November 2003
[2] W. W. Lu. 4G research in Asia. IEEE Communications Magazine, March 2003:104-106
[3] 陈如明. 3G 新发展及 3G/3G 演进策略思考. 中国无线电,2005 年 01 期:2-8
[4] 朱近康. 对 3G 和后 3G 发展的思考. 移动通信,2003 年 7 月:42-45
[5] 张平. 第四代移动通信系统的关键技术及分析. 电信科学,2002 年 08 期:30-34
[6] 李少谦,王军. 宽带无线接入技术发展展望. 通讯世界,2002 年 12 期:61-64
[7] T. S. Rappaport, A. Annamalai, R. M. Buehre, et al. Wireless Communications: Past Events and a Future Perspective. IEEE Communications Magazine, May 2002, Vol.40, Issue 5:148-161
[8] A. C. Chen. Overview of code division multiple access technology for wireless communications. IEEE IECON1998 September, Vol.1:T15-T24
[9] F. B. Frederiksen, R. Prasad. An overview of OFDM and related techniques towards development of future wireless multimedia communications. IEEE RAWCON2002 August:19-22
[10] R. H. Roy. An overview of smart antenna technology: the next wave in wireless communications. IEEE Proceedings of Aerospace Conference, March 1998, Vol.3:339-345
[11] Liuqing Yang, Georgios B. Giannakis. Ultra-Wideband Communications-An Idea Whose Time Has Come. IEEE Signal Processing Magazine, November 2004, Vol.21, Issue 6:26-54
[12] D. Gesbert, M. Shafi, Da-shan Shiu, et al. From theory to practice: an overview of MIMO space-time coded wireless systems. IEEE Journal on Selected Areas in Communications, April 2003, Vol.21, No.3:281-302
[13] A. J. Paulraj, D. A. Gore, R. U. Nabar, et al. An overview of MIMO communications-A key to gigabit wireless. Proceedings of IEEE, February 2004, Vol.92, No.2:198-218
[14] J. Mitola. The software radio architecture. IEEE Communications Magazine, May 1995, Vol.33, Issue 5:26-38
[15] Simon Haykin. Cognitive Radio: Brain-Empowered Wireless Communications. IEEE Journal on Selected Areas in Communications, February 2005, Vol.23, No.2:201-220
[16] A. J. Paulraj, R. U. Nabar, D. A. Gore. Introduction to space-time wireless communications, Cambridge University Press, 2002
[17] S. Alamouti. Space block coding: a simple transmitter diversity technique for wireless communications. IEEE Journal on Selected Areas in Communications, October 1998, Vol.16:1451-1458
[18] G. J. Foschini. Layered space-time architecture for wireless communications in a fading environment when using multi-element antennas. Bell Labs Technical Journal, Autumn 1996:41-59
[19] L. Zheng, and D. N. C. Tse, Diversity and multiplexing: A fundamental tradeoff in multiple-antenna channels, IEEE Transactions on Information Theory, 2003, Vol.49, No.5:1073~1096
[20] 武刚. 多入多出无线通信中的信道模型、空时编码及关键技术研究: [博士学位论文], 成都: 电子科技大学 2004
[21] 3GPP TSG R1-01-1305. MIMO channel measurement and modeling results., Qualcomm, November, 2001
[22] 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, Vol.20, No.6:1211~1226
[23] J.W. Wallace, M.A. Jensen, A. L. Swindlehurst, et al. Experimental characterization of the MIMO wireless channel: Data acquisition and analysis. IEEE Transactions on Wireless Communications, 2003, Vol.2, No.2:335~343
[24] T. Zwick, D. Hampicke, J. Maurer, et al. Results of double-directional channel sounding measurements. Procedings of IEEE 51th VTC2001. Spring:2497~2503
[25] R. Stridh and B. Ottersten. Spatial characterization of indoor radio channel measurements at 5GHz. Proceedings of 1st IEEE Sensor Array and Multichannel Signal Processing Workshop, Boston, MA, USA, 2000
[26] C. C. Martin, J. H. Winters, N. R. Sollenberg. Multiple-input multiple-output (MIMO) radio channel measurements. Proceedings of IEEE VTC2000, Fall, Boston, USA: 774~779
[27] D. Chizhik, J. Ling, P. W. Wolniansky, et al. Multiple-input-multiple-output measurements and modeling in Manhattan. IEEE Journal on Selected Areas in Communications, 2003, Vol.21, No.3:321~331
[28] Kai Yu, B. Ottersten. Models for MIMO propagation channels - A review. Wiley Journal on Wireless Communications and Mobile Computing, 2002, Vol.2, No.7:653~666.
[29] A. F. Molisch. A generic model for MIMO wireless propagation channels in macro- and microcells. IEEE Transactions on Signal Processing, January 2004, Vol.52, No.1:61-71
[30] Hao Xu, Dmitry Chizhik, Howard Huang, et al. A generalized space-time multiple-input multiple-output(MIMO) channel model. IEEE Transactions on Wireless Communications, May 2004, Vol.3, No.3:966-975
[31] M. Patzold. Mobile Fading Channels. John Wiley & Sons, Ltd., 2002
[32] 杨大成. 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
[33] A. G. Burr. Evaluation of capacity of indoor wireless MIMO channel using ray tracing. Proceedings of Inter. Zurich Seminar, Zurich, Switzerland, 2002: 281~286
[34] C. Oestges, V. Erceg, A. J. Paulraj. A physical scattering model for MIMO macrocellular broadband wireless channels, IEEE Journal on Selected Areas in Communications, 2003,Vol.21, No.5:721~729
[35] D. Chizhik, G. J. Foschini, M. J. Gans et al. Keyholes, correlations, capacities of multielement transmit and receive antennas. IEEE Transactions on Wireless Communications, 2002, Vol.1, No.2:361~368
[36] A. Abdi and M. Kaveh. A space-time correlation model for multielement antenna systems in mobile fading channels. IEEE Journal on Selected Areas in Communications,2002, Vol.20, No.3:550~560
[37] M. Steinbauer, A. F. Molisch, E. Bonek. The Double-Directional Channel Model. IEEE Antennas and Propagation Magazine, 2001,Vol.43, Issue 8:51~63
[38] M. Stege, J. Jelitto, M. Bronzel, G. Fettweis. A multiple-input multiple-output channel model for simulation of Tx- and Rx-diversity wireless systems. in Proc. IEEE VTC2000, Fall, Boston, MA, USA:833~839
[39] C. Chuah, D. Tse, J. Kahn, et al. Capacity scaling in MIMO wireless systems under correlated fading. IEEE Transactions on Information Theory, 2002, Vol.48, No.3:637~650
[40] Theodore S. Rappaport. 无线通信原理与应用(蔡涛,李旭,杜振民 译). 北京:电子工业出版社,1999
[41] Gregory D. Durgin. 空—时无线信道(朱世华,任品毅,王磊, 等译). 西安:西安交通大学出版社,2004
[42] R. B. Ertel, P. Cardieri, K. W. Sowerby, T.S. Rappapor, et al. Overview of Spatial channel models for antenna array communications systems. IEEE Personal Communications Magazine, 1998, Vol.5, Issue1:10~22
[43] D. Shiu, G. Foschini, M. Gans, et al. Fading correlation and its effect on the capacity of multi-element antenna systems. IEEE Transactions on Communications, 2000, Vol.48, No.3:502~513
[44] 3GPP. Micro-cell wideband directional channel model. 3GPP TSG R1-01-0992, 2001
[45] J. Salz, J. Winters. Effect of fading correlation on adaptive arrays in digital mobile radio. IEEE Transactions on Vehicular Technology, Nov. 1994, Vol.43:1049-1057
[46] 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
[47] K. I. Pederson, P. E. Mogensen, B.H. Fleury. A stochastic model of the temporal and azimuthal dispersion seen at the base station in outdoor propagation environments. IEEE Transactions on Vehicular Technology, Mar. 2000, Vol.49:437-447
[48] 3GPP. Spatial Channel Model for MIMO Simulations. 3GPP TR 25.996 V6.1.0, 2003
[49] Q.H. Spencer, et al. Modeling the statistical time and angle of arrival characteristics of an indoor environment. IEEE Journal on Selected Areas in Communications, March 2000, Vol.18, No.3:347-360
[50] IEEE802. TGn Channel Models. IEEE 802.11-03/940r4, 2004
[51] Laurent Schumacher, K. I. Pedersen, P. E. Mogensen. From antenna spacings to theoretical capacities—guidelines for simulating MIMO systems. IEEE PIMRC2002 Sept. Vol.2:587-592
[52] K. I. Pedersen, J. B. Andersen, J. P. Kermoal, et al. A Stochastic Multiple-Input-Multiple-Output Radio Channel Model for Evaluation of Space-Time Coding Algorithms. IEEE VTC2000, Vol.2:893-897
[53] ITU. Recommendation ITU-R M.1225 - Guidelines for Evaluation of Radio Transmission Technologies for IMT-2000. 1997
[54] COST 207. Digital land mobile radio communications. Office for Official Publications of the European Communities, Final Report, Luxembourg. 1989
[55] P. Soma, D.S. Baum, V. Erceg. Analysis and modeling of multiple-input multiple-output (MIMO) radio channel based on outdoor measurements conducted at 2.5 GHz for fixed BWA applications. Proceedings of IEEE ICC2002, Vol.1:272-276
[56] 3GPP. MIMO conference call summary. 3GPP R1-02-0141, January 2002
[57] Jean P. Kermoal. Measurement, Modeling and Performance Evaluation of the MIMO Radio Channel: [Ph.D thesis], Aalborg University, Denmark, 2002
[58] W. C. Y. Lee. Effects on Correlation between Two Mobile Radio Base-Station Antennas. IEEE Transactions on Vehicular Technology, November 1973, Vol.22, No. 4:130–140
[59] F. Adachi, M.T. Feeney, A.G. Williamson, et al. Cross correlation Between the Envelopes of 900 MHz Signals Received at a Mobile Radio Base Station Site. IEE Proceedings, October 1986, Vol.133, No.6:506–512
[60] A.A.M. Saleh, R. A. Valenzuela. A statistical model for indoor multipath propagation. IEEE Journal on Selected Areas in Communications, 1987, Vol.5:128-137
[61] Shidong Zhou, Ming Zhao, Xibin Xu, et al. Distributed wireless communication system: a new architecture for future public wireless access. IEEE Communications Magazine, March 2000, Vol.41, Issue 3:108-113
[62] V. Nikolopoulos, M. Fiacco, S. Stavrou, et al. Narrowband fading analysis of indoor distributed antenna systems. IEEE Antennas and Wireless Propagation Letters, 2003, Vol.2, Issue 1:89-92
[63] Wonil Roh, A. J. Paulraj. MIMO Channel Capacity for the Distributed Antenna Systems. VTC2002 September, Vol.2:24-28
[64] 徐晓军,罗涛,王军, 等. 分布式 MIMO 系统的信道建模. 2005 中国西部青年通信学术会议论文集:321-326
[65] Hongyuan Zhang, Huaiyu Dai. On the Capacity of Distributed MIMO Systems. Conference on Information Sciences and Systems, Princeton University, March 2004
[66] M. Patzold, U. Killat, F. Laue. A deterministic digital simulation model for Suzuki processes with application to a shadowed Rayleigh land mobile radio channel. IEEE Trans. Veh. Technol., 1996, Vol.45, No.2:318~331
[67] M. Patzold, R. Garcia, F. Laue. Design of high-speed simulation models for mobile fading channels by using table look-up techniques, IEEE Trans. Veh. Technol., 2000, Vol.49, No.4:1178~1190
[68] M. Patzold, F. Laue. Level-crossing rate and average duration of fades of deterministic simulation models for Rice fading channels” IEEE Trans. Veh. Tech., 2000, Vol.48, No.4:1121~1129
[69] 3GPP. MIMO discussion summary. 3GPP TSG R1-02-0181, January 2002.
[70] 3GPP. A standardized set of MIMO radio propagation channels. 3GPP TSG R1-01-1179.
[71] IEEE802. Air interface for fixed broadband wireless access systems. IEEE802.16-2004 standard, June 2004
[72] IEEE802. Air interface for fixed and mobile broadband wireless access systems: Amendment for physical and medium access control layers for combined fixed and mobile operation in licensed bands. IEEE P802.16e/D7, April 2005
[73] IEEE802. Channel models for fixed wireless applications IEEE802.16.3c-01/29r4
[74] IEEE802. TGn functional requirements. IEEE802 11-03/813
[75] IEEE802. Sync proposal technical specification. IEEE802.11-04/889r1
[76] P. Melancon, J. Lebel. Effects of fluorescent lights on signal fading characteristics for indoor radio channel. IEEE Electronics Letters, August 1992, Vol.28, No.18:1740-1741
[77] IEEE802. Fluorescent Light-Bulb Interaction with Electromagnetic Signals. IEEE 802.11-03/718r4
[78] G. J. Foschini, M.J. Gans. On limits of wireless communication in a fading environment when using multiple antennas. Wireless Personal Communications, March 1998, Vol.6:311-335
[79] IEEE802. 802.11n channel model validation. IEEE 802.11-03/894r1, November 2003