宽带无线通信多用户调度与分集技术
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摘要
现代科技发展突飞猛进,无线通信的发展以及人们对无线通信的需求与过去的十年相比已经不可同日而语,无线通信从以往的传输文字和声音为主渐渐的转移向视频直播和图像传输为主的下一代通信系统。而相应的频谱资源并没有增加,如果需要提供更高的速率和更好的服务质量就需要提高频谱的利用率。其次,无线信道的衰落,多径和时变特性对信号的可靠性有很大的影响。而空时处理技术,尤其是多输入多输出(MIMO)技术作为4G或B3G的核心技术之一,能够大幅度提升系统速率,改善无线通信的可靠性,可以很好的解决这些问题。采用空时编码的MIMO系统能够提升系统的可靠性,增加系统的覆盖范围,很好的适应未来无线通信的需求。本文研究了未来通信系统中的关键技术:多用户MIMO系统下行广播信道的传输技术和多用户通信系统中的多用户调度机制。
在多用户MIMO系统下行广播信道的研究中,本文研究了多用户特征模式传输(MET),MET在线性预编码系统中有着最好的性能表现,可以达到近乎于脏纸编码的效果。MET可以同时发送几个空间复用的流给多个用户,极大的提升系统的容量。由于基站发送天线和用户接收天线数的限制,MET同一时刻服务用户的数量也是有限制的,需要进行用户选择,而穷举搜索算法的高复杂度限制了它的应用。本文介绍了一种新的递归用户选择算法,降低了用户选择的复杂性,算法复杂度得到了降低。
针对多用户MIMO系统下行广播信道的资源分配和用户调度,本文提出了一种新的基于多用户比例公平调度的自适应算法。基站端采用MET来消除用户间干扰,增加系统吞吐量,在保证用户传输速率的情况下使用比例公平调度和本文提出的自适应比例公平调度算法提高系统的公平性,在同一时刻选择最优用户集来传输。仿真与分析表明本文提出自适应算法不仅保证了系统的速率,还提高了系统的公平性。
Technology has developed so fast in last decade and people’s requirement also can not compare with ten years ago, wireless communications, and multimedia services, the requirement of wireless communications increases rapidly. The services on wireless communication are changing from text and voice to live broadcast video and image in next generation communication network. However the spectrum resources are not increasing accordingly. If we want higher speed and better service we should improve the spectrum efficiency. Secondly, the signals transmitted in wireless channel are badly polluted because of the wireless channel character. The space-time processing techniques, especially MIMO, as one of core techniques for 4G/B3G systems, can improve system capacity significantly. MIMO technology increases the systems coverage area, at the same time it can also enhance system reliability. At those circumstance we research in the areas of multi-users downlink broadcast channel transmit scheme and multi-users scheduling algorithm.
In the research of MIMO downlink broadcast system, we study Multiuser Eigenmode Transmission (MET), is by far the best performing linear transmitter precoding scheme for one-to-multiple-point broadcast channels. It can improve system capacity significantly. In this paper, we analyze the structure of MET and study a low-complexity implementation.
For the MIMO downlink broadcast system’s resource allocating and users scheduling, we propose a new adaptive scheduling scheme based on proportional fair scheduling algorithm. The base station use MET to eliminate users interference and increase system capacity, at the same time, we use our adaptive proportional fair scheduling algorithm to ensure system’s fairness.
在多用户MIMO系统下行广播信道的研究中,本文研究了多用户特征模式传输(MET),MET在线性预编码系统中有着最好的性能表现,可以达到近乎于脏纸编码的效果。MET可以同时发送几个空间复用的流给多个用户,极大的提升系统的容量。由于基站发送天线和用户接收天线数的限制,MET同一时刻服务用户的数量也是有限制的,需要进行用户选择,而穷举搜索算法的高复杂度限制了它的应用。本文介绍了一种新的递归用户选择算法,降低了用户选择的复杂性,算法复杂度得到了降低。
针对多用户MIMO系统下行广播信道的资源分配和用户调度,本文提出了一种新的基于多用户比例公平调度的自适应算法。基站端采用MET来消除用户间干扰,增加系统吞吐量,在保证用户传输速率的情况下使用比例公平调度和本文提出的自适应比例公平调度算法提高系统的公平性,在同一时刻选择最优用户集来传输。仿真与分析表明本文提出自适应算法不仅保证了系统的速率,还提高了系统的公平性。
Technology has developed so fast in last decade and people’s requirement also can not compare with ten years ago, wireless communications, and multimedia services, the requirement of wireless communications increases rapidly. The services on wireless communication are changing from text and voice to live broadcast video and image in next generation communication network. However the spectrum resources are not increasing accordingly. If we want higher speed and better service we should improve the spectrum efficiency. Secondly, the signals transmitted in wireless channel are badly polluted because of the wireless channel character. The space-time processing techniques, especially MIMO, as one of core techniques for 4G/B3G systems, can improve system capacity significantly. MIMO technology increases the systems coverage area, at the same time it can also enhance system reliability. At those circumstance we research in the areas of multi-users downlink broadcast channel transmit scheme and multi-users scheduling algorithm.
In the research of MIMO downlink broadcast system, we study Multiuser Eigenmode Transmission (MET), is by far the best performing linear transmitter precoding scheme for one-to-multiple-point broadcast channels. It can improve system capacity significantly. In this paper, we analyze the structure of MET and study a low-complexity implementation.
For the MIMO downlink broadcast system’s resource allocating and users scheduling, we propose a new adaptive scheduling scheme based on proportional fair scheduling algorithm. The base station use MET to eliminate users interference and increase system capacity, at the same time, we use our adaptive proportional fair scheduling algorithm to ensure system’s fairness.
引文
[1] Ming, J. and L. Hanzo (2007). "Multiuser MIMO-OFDM for Next-Generation Wireless Systems." Proceedings of the IEEE 95(7): 1430-1469.
[2] Rivera-Alvarez, V., D. Torres-Roman, et al. (2005). On MIMO space-time coded systems: unleashing the spatial domain. Electrical and Electronics Engineering, 2005 2nd International Conference on.
[3] Kaiser, T., Z. Feng, et al. (2009). "An Overview of Ultra-Wide-Band Systems With MIMO." Proceedings of the IEEE 97(2): 285-312.
[4] Guangyi L., Jianhua Z., Ping Z., et al. Evolution map from TD-SCDMA to FuTURE B3G TDD. Communications Magazine, IEEE, 2006, 44(3): 54-61
[5] Diggavi S. N., Al-Dhahir N., Stamoulis A., et al. Great expectations: the value of spatial diversity in wireless networks. Proceedings of the IEEE, 2004, 92(2): 219-270
[6] Chiani, M., M. Z. Win, et al. "MIMO networks: the effects of interference." IEEE Transactions on Information Theory 56(1): 336-49.
[7] Tarokh V., Jafarhani H., Calderbank A. R. Space-Time Codes Block Coding from Orthogonal Designs. IEEE JSAC, 1999, 48: 1456-1467
[8] Tarokh V., Seshadri N., Calderbank A. R. Space-time codes for high data rate wireless communication: performance criterion and code construction. Information Theory, IEEE Transactions on, 1998, 44(2): 744-765
[9] Foschini G. J. Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas. Bell Labs Technical Journal, 1996, 1(2): 41-59
[10] Paulraj A. J., Gore D. A., Nabar R. U., et al. An overview of MIMO communications - a key to gigabit wireless. Proceedings of the IEEE, 2004, 92(2): 198-218
[11] TSG-RAN TR 21.905. Vocabulary for 3GPP Specifications. 3GPP, 2008: 6-55
[12] Wang, H.-j., M. Lu, et al. (2009). "Research on Field Experiment of MIMO Radar Imaging." Signal Processing 25(11): 1814-19.
[13] Goldsmith A., Jafar S. A., Jindal N., et al. Capacity limits of MIMO channels. IEEE Journal on Selected Areas in Communications, 2003, 21(5): 684-702
[14] Hermosilla, C., R. Feick, et al. (2009). "Improving MIMO capacity with directive antennas for outdoor-indoor scenarios." IEEE Transactions on Wireless Communications 8(5): 2177-81.
[15] Chalise, B. K. and L. Vandendorpe (2009). "MIMO relay design for multipoint-to-multipoint communications with imperfect channel state information." IEEE Transactions on Signal Processing 57(7): 2785-96.
[16] Psaltopoulos, G. K. and A. Wittneben "Nonlinear MIMO: affordable MIMO technology for wireless sensor networks." IEEE Transactions on Wireless Communications 9(2): 824-32.
[17] Hermosilla, C., R. Feick, et al. (2009). "Improving MIMO capacity with directive antennas for outdoor-indoor scenarios." IEEE Transactions on WirelessCommunications 8(5): 2177-81.
[18] Browne, J. "Measuring MIMO Performance Levels." Microwaves & RF 49(7): 102.
[19] Hassanien, A. and S. A. Vorobyov "Phased-MIMO Radar: A Tradeoff Between Phased-Array and MIMO Radars." IEEE Transactions on Signal Processing 58(6): 3137-51.
[20] Rupp, M., A. I. Perez-Neira, et al. (2008). "MIMO transmission with limited feedback." EURASIP Journal on Advances in Signal Processing: 518950 (2 pp.).
[21] El-Hajjar, M. and L. Hanzo "Multifunctional MIMO systems: a combined diversity and multiplexing design perspective." IEEE Wireless Communications 17(2): 73-9.
[22] Bhagavatula, R., R. W. Heath, Jr., et al. (2008). "Sizing up MIMO arrays." IEEE Vehicular Technology Magazine 3(4): 31-8.
[23] Pei, X., W. Jinsong, et al. "MIMO Detection Schemes with Interference and Noise Estimation Enhancement." IEEE Transactions on Communications 59(1): 26-32.
[24] Xiao, H., Z. Nie, et al. (2008). "Analysis for MIMO correlated frequency-selective channel in the presence of interference." Journal of Systems Engineering and Electronics 19(4): 679-82.
[25] Ruiyuan, T., V. Plicanic, et al. "A Compact Six-Port Dielectric Resonator Antenna Array: MIMO Channel Measurements and Performance Analysis." IEEE Transactions on Antennas and Propagation 58(4): 1369-79.
[26] Xiao Peng, Y., C. Qiang, et al. (2007). "Numerical investigation of channel capacity of indoor MIMO system." IEICE Transactions on Communications E90(9): 2338-43.
[27] Garcia-Garcia, L., B. Lindmark, et al. (2007). "MIMO capacity of antenna arrays evaluated using radio channel measurements, reverberation chamber and radiation patterns." IET Microwaves, Antennas & Propagation 1(6): 1160-9.
[28] Jun, T., L. Ning, et al. (2009). "On detection performance of MIMO radar: a relative entropy-based study." IEEE Signal Processing Letters 16(3): 184-7.
[29] Fischer, R. F. H. and M. Hoch (2006). "Directed selected mapping for peak-to-average power ratio reduction in MIMO OFDM." Electronics Letters 42(22): 1289-90.
[30] Migliore, M. D. (2006). "An intuitive electromagnetic approach to MIMO communication systems." IEEE Antennas and Propagation Magazine 48(3): 128-37.
[31] Tarokh V., Naguib A., Seshadri N., et al. Space-time codes for high data rate wireless communication: performance criteria in the presence of channel estimation errors, mobility, and multiple paths. IEEE Transactions on Communications, 1999, 47(2): 199-207
[32] Da-Shan S., Kahn M. Layered space-time codes for wireless communications using multiple transmit antennas. in: Communications, 1999. IEEE International Conference on ICC 99', 1999. 436-440 vol.431
[33]尤肖虎,赵新胜.分布式无线电和蜂窝移动通信网络结构.电子学报, 2004, (S1): 20-25
[34] V. Bharghavan, S. Lu and T. Nandagopal,“Fair queuing in wireless networks: Issues and approaches”, IEEE Personal Communications, pp. 44-53, Feb. 1999.
[35] J. C. Bennett and H. Zhang,“WF2Q: Worst-case fair weighted fair queuing”. InIEEE Infocom, vol. 1, pp. 120-128, 1996.
[36] P. Bender et.al.,“CDMA/HDR: A bandwidth-efficient high-speed wireless data service for nomadic users”, IEEE Communications Magazine, vol. 38, pp. 70-77, July 2000.
[37] J.M. Holtzman,“Asymptotic analysis of proportional fair algorithm”, Proc. IEEE PIMRC, pp. F33-F27, 2001.
[38] S. Shakkottai and A.L. Stolnyar,“Scheduling algorithms for a mixture of real-time and non-real-time data in HDR”, Sept 2001.
[39] T. Bonald,“A score-based opportunistic scheduler for fading radio channels”, European Wireless Conference, Barcelona, Feb. 2004.
[40] G. Barriac and J. Holtzman,“Introducing delay sensitivity into the proportional fair algorithm for CDMA downlink scheduling”, IEEE International Symposium on Spread Spectrum Techniques and Applications, vol 3, pp. 652-656, 2002.
[41] M. Andrews, K. Kumaran, K. Ramanan, S. Stolyar, P. Whiting, and R. Vijaykumar,“Providing quality of service over a shared wireless link”, IEEE Communications Magazine, pp. 150-154, Feb. 2001.
[42] M. Andrews, K. Kumaran, K. Ramanan, S. Stolyar, R. Vijaykumar, and P. Whiting,“Scheduling a queuing system with asynchronously varying service rates”, Probability in Engineering and Information Sciences, 2004, to appear.
[43] N.C. Ericsson, Revenue Maximization in Resource Allocation: Applications in Wireless Communication Networks. Ph.D. Thesis, Signals and Systems, Uppsala Univ., Oct. 2004. http://www.signal.uu.se/Publications/abstracts/a043.html.
[44] J. M. Holtzman,“Asymptotic Analysis of Proportional Fair Algorithm”, Proc. PIMRC’2001, San Diego, CA, Sept. 30- Oct. 3, 2001.
[45] S. Shakkottai and A. L. Stolyar,“A Study of Scheduling Algorithms for a Mixture of Real and Non-real Time Data in HDR”, 17th Intl. Teletraffic Congress (ITC-17), Brazil, Sept. 2001.
[46] T.Bonald,“A Score-based Opportunistic Scheduler for Fading Radio Channels”, In European Wireless Conference, Barcelona, Feb. 2004.
[47] Boal A., Soares A., Silva J. C., et al. Distributed Antenna Cellular System for Transmission of Broadcast/Multicast Services. in: Vehicular Technology Conference, 2007. VTC2007-Spring. 2007. 1307-1311
[48] Honglin H., Weckerle M., Luo J. Adaptive transmission mode selection scheme for distributed wireless communication systems. IEEE Communications Letters , 2006, 10(7): 573-575
[49] F. Boccardi and H. Huang, \A near-optimum technique using linear precoding for the MIMO broadcast channel," in Proc. ICASSP 2007, (Hawaii, USA), pp. 17{20, April 2007.
[50] Z. Shi, C. Zhao, and Z. Ding, \Low complexity eigenmode selection for MIMObroadcast systems with block diagonalization," in Proc. ICC 2008, (Beijing,China), pp. 3976{3981, May 2008.1
[2] Rivera-Alvarez, V., D. Torres-Roman, et al. (2005). On MIMO space-time coded systems: unleashing the spatial domain. Electrical and Electronics Engineering, 2005 2nd International Conference on.
[3] Kaiser, T., Z. Feng, et al. (2009). "An Overview of Ultra-Wide-Band Systems With MIMO." Proceedings of the IEEE 97(2): 285-312.
[4] Guangyi L., Jianhua Z., Ping Z., et al. Evolution map from TD-SCDMA to FuTURE B3G TDD. Communications Magazine, IEEE, 2006, 44(3): 54-61
[5] Diggavi S. N., Al-Dhahir N., Stamoulis A., et al. Great expectations: the value of spatial diversity in wireless networks. Proceedings of the IEEE, 2004, 92(2): 219-270
[6] Chiani, M., M. Z. Win, et al. "MIMO networks: the effects of interference." IEEE Transactions on Information Theory 56(1): 336-49.
[7] Tarokh V., Jafarhani H., Calderbank A. R. Space-Time Codes Block Coding from Orthogonal Designs. IEEE JSAC, 1999, 48: 1456-1467
[8] Tarokh V., Seshadri N., Calderbank A. R. Space-time codes for high data rate wireless communication: performance criterion and code construction. Information Theory, IEEE Transactions on, 1998, 44(2): 744-765
[9] Foschini G. J. Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas. Bell Labs Technical Journal, 1996, 1(2): 41-59
[10] Paulraj A. J., Gore D. A., Nabar R. U., et al. An overview of MIMO communications - a key to gigabit wireless. Proceedings of the IEEE, 2004, 92(2): 198-218
[11] TSG-RAN TR 21.905. Vocabulary for 3GPP Specifications. 3GPP, 2008: 6-55
[12] Wang, H.-j., M. Lu, et al. (2009). "Research on Field Experiment of MIMO Radar Imaging." Signal Processing 25(11): 1814-19.
[13] Goldsmith A., Jafar S. A., Jindal N., et al. Capacity limits of MIMO channels. IEEE Journal on Selected Areas in Communications, 2003, 21(5): 684-702
[14] Hermosilla, C., R. Feick, et al. (2009). "Improving MIMO capacity with directive antennas for outdoor-indoor scenarios." IEEE Transactions on Wireless Communications 8(5): 2177-81.
[15] Chalise, B. K. and L. Vandendorpe (2009). "MIMO relay design for multipoint-to-multipoint communications with imperfect channel state information." IEEE Transactions on Signal Processing 57(7): 2785-96.
[16] Psaltopoulos, G. K. and A. Wittneben "Nonlinear MIMO: affordable MIMO technology for wireless sensor networks." IEEE Transactions on Wireless Communications 9(2): 824-32.
[17] Hermosilla, C., R. Feick, et al. (2009). "Improving MIMO capacity with directive antennas for outdoor-indoor scenarios." IEEE Transactions on WirelessCommunications 8(5): 2177-81.
[18] Browne, J. "Measuring MIMO Performance Levels." Microwaves & RF 49(7): 102.
[19] Hassanien, A. and S. A. Vorobyov "Phased-MIMO Radar: A Tradeoff Between Phased-Array and MIMO Radars." IEEE Transactions on Signal Processing 58(6): 3137-51.
[20] Rupp, M., A. I. Perez-Neira, et al. (2008). "MIMO transmission with limited feedback." EURASIP Journal on Advances in Signal Processing: 518950 (2 pp.).
[21] El-Hajjar, M. and L. Hanzo "Multifunctional MIMO systems: a combined diversity and multiplexing design perspective." IEEE Wireless Communications 17(2): 73-9.
[22] Bhagavatula, R., R. W. Heath, Jr., et al. (2008). "Sizing up MIMO arrays." IEEE Vehicular Technology Magazine 3(4): 31-8.
[23] Pei, X., W. Jinsong, et al. "MIMO Detection Schemes with Interference and Noise Estimation Enhancement." IEEE Transactions on Communications 59(1): 26-32.
[24] Xiao, H., Z. Nie, et al. (2008). "Analysis for MIMO correlated frequency-selective channel in the presence of interference." Journal of Systems Engineering and Electronics 19(4): 679-82.
[25] Ruiyuan, T., V. Plicanic, et al. "A Compact Six-Port Dielectric Resonator Antenna Array: MIMO Channel Measurements and Performance Analysis." IEEE Transactions on Antennas and Propagation 58(4): 1369-79.
[26] Xiao Peng, Y., C. Qiang, et al. (2007). "Numerical investigation of channel capacity of indoor MIMO system." IEICE Transactions on Communications E90(9): 2338-43.
[27] Garcia-Garcia, L., B. Lindmark, et al. (2007). "MIMO capacity of antenna arrays evaluated using radio channel measurements, reverberation chamber and radiation patterns." IET Microwaves, Antennas & Propagation 1(6): 1160-9.
[28] Jun, T., L. Ning, et al. (2009). "On detection performance of MIMO radar: a relative entropy-based study." IEEE Signal Processing Letters 16(3): 184-7.
[29] Fischer, R. F. H. and M. Hoch (2006). "Directed selected mapping for peak-to-average power ratio reduction in MIMO OFDM." Electronics Letters 42(22): 1289-90.
[30] Migliore, M. D. (2006). "An intuitive electromagnetic approach to MIMO communication systems." IEEE Antennas and Propagation Magazine 48(3): 128-37.
[31] Tarokh V., Naguib A., Seshadri N., et al. Space-time codes for high data rate wireless communication: performance criteria in the presence of channel estimation errors, mobility, and multiple paths. IEEE Transactions on Communications, 1999, 47(2): 199-207
[32] Da-Shan S., Kahn M. Layered space-time codes for wireless communications using multiple transmit antennas. in: Communications, 1999. IEEE International Conference on ICC 99', 1999. 436-440 vol.431
[33]尤肖虎,赵新胜.分布式无线电和蜂窝移动通信网络结构.电子学报, 2004, (S1): 20-25
[34] V. Bharghavan, S. Lu and T. Nandagopal,“Fair queuing in wireless networks: Issues and approaches”, IEEE Personal Communications, pp. 44-53, Feb. 1999.
[35] J. C. Bennett and H. Zhang,“WF2Q: Worst-case fair weighted fair queuing”. InIEEE Infocom, vol. 1, pp. 120-128, 1996.
[36] P. Bender et.al.,“CDMA/HDR: A bandwidth-efficient high-speed wireless data service for nomadic users”, IEEE Communications Magazine, vol. 38, pp. 70-77, July 2000.
[37] J.M. Holtzman,“Asymptotic analysis of proportional fair algorithm”, Proc. IEEE PIMRC, pp. F33-F27, 2001.
[38] S. Shakkottai and A.L. Stolnyar,“Scheduling algorithms for a mixture of real-time and non-real-time data in HDR”, Sept 2001.
[39] T. Bonald,“A score-based opportunistic scheduler for fading radio channels”, European Wireless Conference, Barcelona, Feb. 2004.
[40] G. Barriac and J. Holtzman,“Introducing delay sensitivity into the proportional fair algorithm for CDMA downlink scheduling”, IEEE International Symposium on Spread Spectrum Techniques and Applications, vol 3, pp. 652-656, 2002.
[41] M. Andrews, K. Kumaran, K. Ramanan, S. Stolyar, P. Whiting, and R. Vijaykumar,“Providing quality of service over a shared wireless link”, IEEE Communications Magazine, pp. 150-154, Feb. 2001.
[42] M. Andrews, K. Kumaran, K. Ramanan, S. Stolyar, R. Vijaykumar, and P. Whiting,“Scheduling a queuing system with asynchronously varying service rates”, Probability in Engineering and Information Sciences, 2004, to appear.
[43] N.C. Ericsson, Revenue Maximization in Resource Allocation: Applications in Wireless Communication Networks. Ph.D. Thesis, Signals and Systems, Uppsala Univ., Oct. 2004. http://www.signal.uu.se/Publications/abstracts/a043.html.
[44] J. M. Holtzman,“Asymptotic Analysis of Proportional Fair Algorithm”, Proc. PIMRC’2001, San Diego, CA, Sept. 30- Oct. 3, 2001.
[45] S. Shakkottai and A. L. Stolyar,“A Study of Scheduling Algorithms for a Mixture of Real and Non-real Time Data in HDR”, 17th Intl. Teletraffic Congress (ITC-17), Brazil, Sept. 2001.
[46] T.Bonald,“A Score-based Opportunistic Scheduler for Fading Radio Channels”, In European Wireless Conference, Barcelona, Feb. 2004.
[47] Boal A., Soares A., Silva J. C., et al. Distributed Antenna Cellular System for Transmission of Broadcast/Multicast Services. in: Vehicular Technology Conference, 2007. VTC2007-Spring. 2007. 1307-1311
[48] Honglin H., Weckerle M., Luo J. Adaptive transmission mode selection scheme for distributed wireless communication systems. IEEE Communications Letters , 2006, 10(7): 573-575
[49] F. Boccardi and H. Huang, \A near-optimum technique using linear precoding for the MIMO broadcast channel," in Proc. ICASSP 2007, (Hawaii, USA), pp. 17{20, April 2007.
[50] Z. Shi, C. Zhao, and Z. Ding, \Low complexity eigenmode selection for MIMObroadcast systems with block diagonalization," in Proc. ICC 2008, (Beijing,China), pp. 3976{3981, May 2008.1