无线通信系统中的多用户分集及预编码研究
|
摘要
随着蜂窝无线通信、因特网和多媒体业务的迅速发展,世界范围内无线通信的容量需求在迅速增长。以多输入多输出(MIMO)系统为代表的空时处理技术被认为是4G或B3G的核心技术之一。采用空时编码的MIMO系统能适用于Internet和多媒体业务,并且可以动态地增加覆盖范围和可靠性。目前,用户对无线通信的速率和服务质量提出了越来越高的要求,而可利用的无线频谱是有限的,另一方面,无线信道的多径传播特性和时变特性会对其中传输的信号带来比较大的伤害。MIMO技术因为能大幅度提高无线通信系统的频谱效率和链路传输可靠性而得到了越来越多的关注。在此背景下,本论文以下行多用户MIMO系统和分布式MIMO系统为研究平台,研究了对应的系统模型和传输策略。
针对下行多用户多天线系统(MU-MIMO)的资源分配和用户调度,本文提出了一种基于遗传算法(GA)的多用户比例公平调度算法。并通过在初始群体中加入具有优秀基因的个体并保持其基因稳定性,加快了遗传算法的收敛性。基站端采用块对角化预编码机制来消除用户间干扰,并在保证用户间速率比例公平的前提下最大化系统吞吐量,在同一时刻选择最优用户集来传输。同时本文还分析了信道反馈错误对该系统的影响。仿真与分析表明本文提出的基本算法与改进算法在公平性和系统的吞吐量方面取得了较好的折中,同时算法复杂度比较低。
为了消除多用户MIMO下行系统的多用户间干扰以及改进系统的误码率性能,本文研究了块对角化预编码与几何均值分解的联合方案(BD-GMD)。针对BD-GMD系统的资源分配和用户调度,对比了等功率分配和注水算法对系统的影响,并基于系统容量最大化,提出了一种根据用户信道的子空间特性的低复杂度的用户调度算法。此外,对比分析了穷举搜索算法和传统的贪婪算法。数值仿真结果表明,本文所提出的基于正交投影的多用户调度算法充在保证系统容量的同时降低了算法复杂度。同时针对用户间的公平性,本文并提出了一种新的比例公平调度算法。该算法利用一个新的参数来表示用户过去的信道状态信息,根据当前和过去的信道状态信息可以更好的调度多用户并同时保证用户间公平性。
为了消除下行多用户MIMO系统中的共信道干扰,并且最大化和速率,提出了基于斜投影的预编码的系统模型,并在此系统模型上利用注水功率分配算法推导出了该系统容量的闭式表达式;通过仿真描述了在多用户MIMO系统中基于斜投影的预编码和基于正交投影的BD-GMD联合预编码的系统容量的差别。在低信噪比时,基于斜投影的预编码的容量性能要优于BD-GMD系统;而在高信噪比时,则正好相反,BD-GMD系统要优于基于斜投影的系统容量。通过仿真证明,当系统信道条件比较差时,基于斜投影的预编码可以提供更好的系统性能。
分布式天线系统(DAS)由于其具有更大的覆盖范围,较好的功率效率,以及更高的系统容量在近年来备受关注,而MIMO技术和分布式天线系统相结合的分布式MIMO系统更是成为研究热点,但很多文献都只是基于以上几个方面进行分析,而没有考虑多用户分集。本文将传统MIMO系统中的块对角化预编码应用到分布式MIMO系统中,以该算法为基础提出了一种新的多用户调度方案,从多用户分集的角度研究了下行分布式MIMO系统的容量性能。
With the rapid development of cellular wireless communications, Internet and multimedia servieces, the requirement of the system capacity of the wireless communications increases speedily. The space-time processing techniques, represented by MEMO, are considered as one of core techniques for 4G/B3G systems. MIMO systems with space-time coding could not just be fit for the Internet and multimedia services, but increase the coverage area and improve the system reliability. At present, users expect higher system capacity and better quality of services, but the available wireless Spectral resource is limited. On the other hand, the multi-path and time-varing characteristics of the wireless channel cause significant damage to transmit signals. MIMO techniques have attracted more and more attentions because it can tremendously increase the spectrum efficiency and improve the transmission reliability of wireless communication systems. Based on the platform of multiuser MIMO downlink system and distributd MIMO system, our research mainly focuses on the system model and transmission strategy.
For the resource allocation and scheduling of downlink multi-user multiple input multiple output (MU-MIMO) system, a multi-user proportional fair scheduling scheme based on genetic algorithms (GA) is proposed. By adding some good-gene individuals to the initial population and keeping its gene stable, the convergence of GA is accelerated. Specially, the base station exploits Block Diagonalization (BD) precoding technique to eliminate the inter-user interference. To guarantee the fairness of the user transmission speeed while maximizing the throughput performance, a subset of users is selected to serve at one time slot. Moreover, the impact of feedback error on the channel state information is analyzed. Simulation results show that both schemes can achieve a good tradeoff between fairness and throughput with low computational complexity compared to other scheduling schemes.
The combined Block Digonalization precoding and Geometric Mean Decomposition (BD-GMD) scheme is developed to eliminate the multi-user interference and improve the system performance of bit error rate (BER) in a multiuser multiple input multiple output (MU-MIMO). For the resource allocation and scheduling of BD-GMD system, the impacts of the system from the equal power allocation and water-filling algorithm are compared. According to the subspace characteristics, a multi-user scheduling scheme based on maximizing the system throughput with low computational complexity is proposed. At the meantime, the brute-force search algorithm and conventional greedy algorithm are analyzed and compared with the proposed algorithm. Simulation results show that the proposed algorithm based on the orthogonal projection can reduce the computational complexity while maintaining the system throughput. For the fairness among internal users, a novel proportional fair scheduling algorithm is proposed in this paper. This algorithm, inserting a new parameter to denote users' past channel status information, could schedule multi-user better and guarantee fairness among internal users by considering both current and past channel status information.
In order to mitigate co-channel interference and maximize the sum capacity in a multiuser MIMO downlink system, a novel system model based on oblique projection is presented and the expression of the system capacity with water-filling power algorithm is deduced. The simulation results have proved that, at the high signal-to-noise ratio (SNRs), the capacity performance of the system with oblique projection is better than that of BD-GMD system, but at low SNRs, the situation is opposite. The result obtained by system simulation means the system with oblique projection precoding could provide better capacity performance with a worse system channel.
In recent years, distributed antenna system has obtained more and more attention due to its promising improvement in coverage, power efficiency and channel capacity. And the distributed MIMO system, which combines MIMO technique and the distributed antenna system, becomes to be a hot research area. However, most of those papers are only concerned those aspects which are mentioned above, but no considering multiuser diversity. This paper, applying the BD pre-coding to the distributed MIMO system, proposes a novel multi-user scheduling algorithm, which researches the capacity performance of downlink distributed MIMO systems from the aspect of multi-user diversity.
针对下行多用户多天线系统(MU-MIMO)的资源分配和用户调度,本文提出了一种基于遗传算法(GA)的多用户比例公平调度算法。并通过在初始群体中加入具有优秀基因的个体并保持其基因稳定性,加快了遗传算法的收敛性。基站端采用块对角化预编码机制来消除用户间干扰,并在保证用户间速率比例公平的前提下最大化系统吞吐量,在同一时刻选择最优用户集来传输。同时本文还分析了信道反馈错误对该系统的影响。仿真与分析表明本文提出的基本算法与改进算法在公平性和系统的吞吐量方面取得了较好的折中,同时算法复杂度比较低。
为了消除多用户MIMO下行系统的多用户间干扰以及改进系统的误码率性能,本文研究了块对角化预编码与几何均值分解的联合方案(BD-GMD)。针对BD-GMD系统的资源分配和用户调度,对比了等功率分配和注水算法对系统的影响,并基于系统容量最大化,提出了一种根据用户信道的子空间特性的低复杂度的用户调度算法。此外,对比分析了穷举搜索算法和传统的贪婪算法。数值仿真结果表明,本文所提出的基于正交投影的多用户调度算法充在保证系统容量的同时降低了算法复杂度。同时针对用户间的公平性,本文并提出了一种新的比例公平调度算法。该算法利用一个新的参数来表示用户过去的信道状态信息,根据当前和过去的信道状态信息可以更好的调度多用户并同时保证用户间公平性。
为了消除下行多用户MIMO系统中的共信道干扰,并且最大化和速率,提出了基于斜投影的预编码的系统模型,并在此系统模型上利用注水功率分配算法推导出了该系统容量的闭式表达式;通过仿真描述了在多用户MIMO系统中基于斜投影的预编码和基于正交投影的BD-GMD联合预编码的系统容量的差别。在低信噪比时,基于斜投影的预编码的容量性能要优于BD-GMD系统;而在高信噪比时,则正好相反,BD-GMD系统要优于基于斜投影的系统容量。通过仿真证明,当系统信道条件比较差时,基于斜投影的预编码可以提供更好的系统性能。
分布式天线系统(DAS)由于其具有更大的覆盖范围,较好的功率效率,以及更高的系统容量在近年来备受关注,而MIMO技术和分布式天线系统相结合的分布式MIMO系统更是成为研究热点,但很多文献都只是基于以上几个方面进行分析,而没有考虑多用户分集。本文将传统MIMO系统中的块对角化预编码应用到分布式MIMO系统中,以该算法为基础提出了一种新的多用户调度方案,从多用户分集的角度研究了下行分布式MIMO系统的容量性能。
With the rapid development of cellular wireless communications, Internet and multimedia servieces, the requirement of the system capacity of the wireless communications increases speedily. The space-time processing techniques, represented by MEMO, are considered as one of core techniques for 4G/B3G systems. MIMO systems with space-time coding could not just be fit for the Internet and multimedia services, but increase the coverage area and improve the system reliability. At present, users expect higher system capacity and better quality of services, but the available wireless Spectral resource is limited. On the other hand, the multi-path and time-varing characteristics of the wireless channel cause significant damage to transmit signals. MIMO techniques have attracted more and more attentions because it can tremendously increase the spectrum efficiency and improve the transmission reliability of wireless communication systems. Based on the platform of multiuser MIMO downlink system and distributd MIMO system, our research mainly focuses on the system model and transmission strategy.
For the resource allocation and scheduling of downlink multi-user multiple input multiple output (MU-MIMO) system, a multi-user proportional fair scheduling scheme based on genetic algorithms (GA) is proposed. By adding some good-gene individuals to the initial population and keeping its gene stable, the convergence of GA is accelerated. Specially, the base station exploits Block Diagonalization (BD) precoding technique to eliminate the inter-user interference. To guarantee the fairness of the user transmission speeed while maximizing the throughput performance, a subset of users is selected to serve at one time slot. Moreover, the impact of feedback error on the channel state information is analyzed. Simulation results show that both schemes can achieve a good tradeoff between fairness and throughput with low computational complexity compared to other scheduling schemes.
The combined Block Digonalization precoding and Geometric Mean Decomposition (BD-GMD) scheme is developed to eliminate the multi-user interference and improve the system performance of bit error rate (BER) in a multiuser multiple input multiple output (MU-MIMO). For the resource allocation and scheduling of BD-GMD system, the impacts of the system from the equal power allocation and water-filling algorithm are compared. According to the subspace characteristics, a multi-user scheduling scheme based on maximizing the system throughput with low computational complexity is proposed. At the meantime, the brute-force search algorithm and conventional greedy algorithm are analyzed and compared with the proposed algorithm. Simulation results show that the proposed algorithm based on the orthogonal projection can reduce the computational complexity while maintaining the system throughput. For the fairness among internal users, a novel proportional fair scheduling algorithm is proposed in this paper. This algorithm, inserting a new parameter to denote users' past channel status information, could schedule multi-user better and guarantee fairness among internal users by considering both current and past channel status information.
In order to mitigate co-channel interference and maximize the sum capacity in a multiuser MIMO downlink system, a novel system model based on oblique projection is presented and the expression of the system capacity with water-filling power algorithm is deduced. The simulation results have proved that, at the high signal-to-noise ratio (SNRs), the capacity performance of the system with oblique projection is better than that of BD-GMD system, but at low SNRs, the situation is opposite. The result obtained by system simulation means the system with oblique projection precoding could provide better capacity performance with a worse system channel.
In recent years, distributed antenna system has obtained more and more attention due to its promising improvement in coverage, power efficiency and channel capacity. And the distributed MIMO system, which combines MIMO technique and the distributed antenna system, becomes to be a hot research area. However, most of those papers are only concerned those aspects which are mentioned above, but no considering multiuser diversity. This paper, applying the BD pre-coding to the distributed MIMO system, proposes a novel multi-user scheduling algorithm, which researches the capacity performance of downlink distributed MIMO systems from the aspect of multi-user diversity.
引文
[1] Qi B., Zysman G. L., Menkes H. Wireless mobile communications at the start of the 21st century. Communications Magazine, IEEE, 2001, 39(1): 110-116
[2] Ping Z., Xiaofeng T., Jianhua Z., et al. A vision from the future: beyond 3G TDD. Communications Magazine, IEEE, 2005,43(1): 38-44
[3] Xiao-Hu Y., Guoan C., Ming C., et al. The FuTURE Project in China. Communications Magazine, IEEE, 2005,43(1): 70-75
[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] TSG-RAN TR 21.905. Vocabulary for 3GPP Specifications. 3GPP, 2008: 6-55
[6] Telatar E. On the capacity of multi-antenna Gaussian channels. European Transactions on Telecommunications, 1999,10(6): 585-595
[7] 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
[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] Tarokh V., Jafarhani H., Calderbank A. R. Space-Time Codes Block Coding from Orthogonal Designs. IEEE JSAC, 1999,48: 1456-1467
[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] 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
[12] Gesbert D., Shafi M., Da-shan S., et al. From theory to practice: an overview of MIMO space-time coded wireless systems. IEEE Journal on Selected Areas in Communications, 2003, 21(3): 281-302
[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] Wolniansky P. W., Foschini G. J., Golden G. D., et al. V-BLAST: an architecture for realizing very high data rates over the rich-scattering wireless channel. 1998 URSI International Symposium on Signals, Systems, and Electronics.1998. 295-300
[15] 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
[16] Wubben D., Rinas J. Efficient Algorithm for Detecting Layered Space-Time Codes. ITG Conference on Source and Channel Coding, 2002: 399-405
[17] Kyu Jong H., Kwang Bok L. Transmit power allocation with small feedback overhead for a multiple antenna system. in: Vehicular Technology Conference, 2002. Proceedings. VTC 2002-Fall, 2002: 2158-2162 vol.2154
[18]Nam S.H.,Oh-Soon S.,Kwang Bok L.Transmit power allocation for a modified V-BLAST system.IEEE Transactions on Communications,2004,52(7):1074-1079
[19]Sellathurai M.,Haykin S.Turbo-BLAST for wireless communications:theory and experiments.IEEE Transactions on Signal Processing,2002,50(10):2538-2546
[20]Hermosilla C.,Szczecinski L.Iterative decoding and iterative detection in MIMO receivers:complexity and performance tradeoffs,in the proc.of Biennial Symposium on Communications,2004:254-256
[21]Tarokh V.,Jafarkhani H.,Calderbank A.R.Space-time block coding for wireless communications:performance results.IEEE Journal on Selected Areas in Communications,,1999,17(3):451-460
[22]Alamouti S.M.A simple transmit diversity technique for wireless communications.IEEE Journal on Selected Areas in Communications,1998,16(8):1451-1458
[23]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
[24]Rupp M.,Mecklenbrauker C.F.On extended alamouti schemes for space time coding.WPMC,2002:115-118
[25]Tarokh V.,Jafarkhani H.A differential detection scheme for transmit diversity.IEEE Journal on Selected Areas in Communications,2000,18(7):1169-1174
[26]Hughes B.L.Differential space-time modulation.IEEE Transactions on Information Theory,2000,46(7):2567-2578
[27]Lizhong Z.,Tse D.N.C.Diversity and multiplexing:a fundamental tradeoff in multiple-antenna channels.IEEE Transactions on Information Theory,2003,49(5):1073-1096
[28]Pedersen K.I.,Mogensen P.E.,Ramiro-Moreno J.Application and performance of downlink beamforming techniques in UMTS.IEEE Communications Magazine,2003,41(10):134-143
[29]Suard B.,Guanghan X.,Hui L.,et al.Uplink channel capacity of space-division-multiple-access schemes.IEEE Transactions on Information Theory,1998,44(4):1468-1476
[30]Spencer Q.H.,Peel C.B.,Swindlehurst A.L.,et al.An introduction to the multi-user MIMO downlink.IEEE Communications Magazine,2004,42(10):60-67
[31]Paulraj A.J.,Nabar R.U.,Gore D.A.Introduction to Space-Time Wireless Communications.Cambridge,2005,
[32]Boyd S.,Vandenberghe L.Convex Optimization.Cambridge University Press,2004,
[33]Wei Y.,Wonjong R.,Boyd S.,et al.Iterative water-filling for Gaussian vector multiple-access channels.IEEE Transactions on Information Theory,2004,50(1):145-152
[34]Cover T.M.,Thomas J.A.Elements of Information Theory.New York:Wiley,1991,
[35]Costa M.Writing on dirty paper.IEEE Transactions on Information Theory,1983,29(3):439-441
[36]Caire G.,Shamai S.On the achievable throughput of a multiantenna Gaussian broadcast channel.IEEE Transactions on Information Theory,2003,49(7):1691-1706
[37]Erez U.,Shamai S.,Zamir R.Capacity and lattice strategies for canceling known interference.IEEE Transactions on Information Theory,2005,51(11):3820-3833
[38]Viswanath P.,Tse D.N.C.Sum capacity of the vector Gaussian broadcast channel and uplink-downlink duality.IEEE Transactions on Information Theory,2003,49(8):1912-1921
[39]Schubert M.,Boche H.Solution of the multiuser downlink beamforming problem with individual SINR constraints.IEEE Transactions on Vehicular Technology,2004,53(1):18-28
[40]Saleh A.,Rustako A.,Roman R.Distributed Antennas for Indoor Radio Communications.IEEE Transactions on Communications,1987,35(12):1245-1251
[41]Wonil R.,Paulraj A.MIMO channel capacity for the distributed antenna,in:Vehicular Technology Conference,2002.Proceedings.VTC 2002-Fall,2002.706-709 vol.702
[42]Wonil R.,Paulraj A.Outage performance of the distributed antenna systems in a composite fading channel,in:Vehicular Technology Conference,2002.Proceedings.VTC 2002-Fall,2002.1520-1524 vol.1523
[43]Roh W.,Paulraj A.Performance of the distributed antenna systems in a multi-cell environment,in:Vehicular Technology Conference,2003.VTC 2003-Spring,2003.587-591 vol.581
[44]王京,姚彦,赵明,et al.分布式无线通信系统的概念平台.电子学报,2002,(07):2-5
[45]Jing W.,Yan Y.,Ming Z.,et al.Conceptual platform of distributed wireless communication system,in:Vehicular Technology Conference,2002.VTC Spring 2002.593-597 vol.592
[46]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
[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]Lin D.,Shidong Z.,Yah Y.Capacity analysis in CDMA distributed antenna systems.IEEE Transactions on Wireless Communications,,2005,4(6):2613-2620
[50]Liang X.,Lin D.,Hairuo Z.,et al.Information-theoretic capacity analysis in MIMO distributed antenna systems,in:Vehicular Technology Conference,2003.VTC 2003-Spring,2003.779-782 vol.771
[51]Zhi N.,Daoben L.Effect of fading correlation on capacity of distributed MIMO.in:Personal,Indoor and Mobile Radio Communications,2004.PIMRC 2004.15th IEEE International Symposium on.2004.1637-1641 Vol.1633
[52]Xiaofeng T.,Chao T.,Zuojun D.,et al.Capacity analyses for a generalized distributed antenna architecture for beyond 3G systems,in:Vehicular Technology Conference,2005.VTC 2005-Spring,2005.3193-3196 Vol.3195
[53]曾昆,唐友喜,田斌,et al.分布式发射天线V-BLAST信号的排序干扰抵消检测.电子与信息学报,2006,(01)
[54]Ying S.,Youxi T.,Ting K.,et al.Optimal antenna location for STBC-OFDM downlink with distributed transmit antennas in linear cells.IEEE Communications Letters,2007,11(5):387-389
[55]Han S.,Zhou S.,Wang J.,et al.Suboptimal Transmission of Orthogonal Space–Time Block Codes Over Correlated Distributed Antennas.IEEE Signal Processing Letters,2007,14(2):89-92
[56]郑海波,王京,周世东,et al.分布式天线系统的多用户分集.电子与信息学报,2007,(11)
[57]Yifan C.,Chau Y.,Yan Z.,et al.Diversity Gains of Generalized Distributed Antenna Systems with Cooperative Users.in:Wireless Communications and Networking Conference,2007.WCNC 2007.IEEE.2007.797-802
[58]Chen P.,Cheng R.-t.,Wu W.-1.Antenna dynamic selection strategies in CDMA distributed antenna systems,in:Advances in Wired and Wireless Communication,2005 IEEE/Sarnoff Symposium on.2005.1-4
[59]赵新胜,尤肖虎,朱定乾.分布式无线移动通信系统中远端天线单元动态选择方法研究.电子与信息学报,2006,(12)
[60]蒋占军,赵新胜,尤肖虎.一种分布式无线移动通信系统中远端天线单元动态选择模型.电子与信息学报,2007,(02)
[61]Heath R.W.,Jr.,Airy M.,Paulraj A.J.Multiuser diversity for MIMO wireless systems with linear receivers,in:Signals,Systems and Computers,2001.Conference Record of the Thirty-Fifth Asilomar Conference on.2001.1194-1199vol.1192
[62]Bender P.,Black P.,Grob M.,et al.CDMA/HDR:a bandwidth efficient high speed wireless data service for nomadic users.IEEE Communications Magazine,2000,38(7):70-77
[63]Viswanath P.,Tse D.N.C.,Laroia R.Opportunistic beamforming using dumb antennas.IEEE Transactions on Information Theory,2002,48(6):1277-1294
[64]Ajib W.,Haccoun D.An overview of scheduling algorithms in MIMO-based fourth-generation wireless systems.IEEE Network,2005,19(5):43-48
[65]Jing J.,Buehrer R.M.,Tranter W.H.Antenna diversity in multiuser data networks.IEEE Transactions on Communications,2004,52(3):490-497
[66]Wei Y.Spatial multiplex in downlink multiuser multiple-antenna wireless environments,in:Global Telecommunications Conference,2003.GLOBECOM'03.IEEE.2003.1887-1891 vol.1884
[67]Zamir R.,Shamai S.,Erez U.Nested linear/lattice codes for structured multiterminal binning.IEEE Transactions on Information Theory,2002,48(6):1250-1276
[68]Peel C.B.,Hochwald B.M.,Swindlehurst A.L.A vector-perturbation technique for near-capacity multiantenna multiuser communication-part Ⅰ:channel inversion and regularization.IEEE Transactions on Communications,2005,53(1):195-202
[69]Taesang Y.,Goldsmith A.On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming.IEEE Journal on Selected Areas in Communications,2006,24(3):528-541
[70]Spencer Q.H.,Swindlehurst A.L.,Haardt M.Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels.IEEE Transactions on Signal Processing,2004,52(2):461-471
[71]Zukang S.,Runhua C.,Andrews J.G.,et al.Sum Capacity of Multiuser MIMO Broadcast Channels with Block Diagonalization.IEEE Transactions on Wireless Communications,2007,6(6):2040-2045
[72]Jalali A.,Padovani R.,Pankaj R.Data throughput of CDMA-HDR a high efficiency-high data rate personal communication wireless system,in:Vehicular Technology Conference Proceedings,2000.VTC 2000-Spring Tokyo.2000 IEEE 51st.2000.1854-1858 vol.1853
[73]Rhee W.,Cioffi J.M.Increase in capacity of multiuser OFDM system using dynamic subchannel allocation,in:Vehicular Technology Conference Proceedings,2000.VTC 2000-Spring Tokyo.2000 IEEE 51st.2000.1085-1089 vol.1082
[74]Ying Jun Z.,Letaief K.B.Optimizing power and resource management for multiuser MIMO/OFDM systems,in:Global Telecommunications Conference,2003.GLOBECOM'03.IEEE.2003.179-183 Vol.171
[75]Meilong J.,Hui D.S.W.,Lau V.K.N.,et al.Cross-layer Downlink Scheduling of Multi-user Multi-Antenna Systems with Heterogeneous Delay Constraints.in:Information Theory,2006 IEEE International Symposium on.2006.2894-2898
[76]Dapeng W.,Negi R.Utilizing multiuser diversity for efficient support of quality of service over a fading channel.IEEE Transactions on Vehicular Technology,2005,54(3):1198-1206
[77]Zhang J.Traffic Meets Fading:A Cross-Layer Design Perspective.in:Proceeding of the 40th Allerton Conference on Communications.2002.1229-1238
[78]Oh-Soon S.,Kwang B.Antenna-assisted round robin scheduling for MIMO cellular systems.IEEE Communications Letters,2003,7(3):109-111
[79]Holtzman J.M.Asymptotic analysis of proportional fair algorithm,in:Personal,Indoor and Mobile Radio Communications,2001 12th IEEE International Symposium on.2001.F-33-F-37 vol.32
[80]Lau V.K.N.A Proportional Fair Space Time Scheduling for Wireless Communications.IEEE Transactions on Communications,2005,53(4):747-747
[81]Yu G.-d.,Zhang Z.-y.,Qiu P.-l.,et al.Fair resource scheduling algorithm for wireless OFDM systems,in:Communications,Circuits and Systems,2005.Proceedings.2005 International Conference on.2005.374-377 Vol.371
[82]Hoon K.,Youngnam H.A proportional fair scheduling for multicamer transmission systems.IEEE Communications Letters,2005,9(3):210-212
[83]Xiangping Q.,Berry R.Opportunistic splitting algorithms for wireless networks,in:INFOCOM 2004.Twenty-third Annual Joint Conference of the IEEE Computer and Communications Societies.2004.1662-1672 vol.1663
[84]Al-Harthi Y.,Tewfik A.,Alouini M.S.Opportunistic scheduling with quantized feedback in wireless networks,in:Information Technology:Coding and Computing,2005.ITCC 2005.International Conference on.2005.716-722 Vol.712
[85]Taiwen T.,Heath R.W.Opportunistic feedback for downlink multiuser diversity.IEEE Communications Letters,2005,9(10):948-950
[86]Svedman P.,Wilson S.K.,Cimini L.J.,Jr.,et al.A simplified opportunistic feedback and scheduling scheme for OFDM. in: Vehicular Technology Conference, 2004. VTC 2004-Spring. 2004 IEEE 59th.2004. 1878-1882 Vol.1874
[87] Koorapaty H., Krasny L., Ramesh R. Delta modulation for channel feedback in transmit diversity systems. in: Vehicular Technology Conference, 2005. VTC 2005-Spring. 2005 IEEE 61st.2005. 644-648 Vol. 641
[88] Sharif M., Hassibi B. A Comparison of Time-Sharing, DPC, and Beamforming for MIMO Broadcast Channels With Many Users. IEEE Transactions on Communications, 2007, 55(1): 11-15
[89] Vishwanath S., Jindal N., Goldsmith A. Duality, achievable rates, and sum-rate capacity of Gaussian MIMO broadcast channels. IEEE Transactions on Information Theory, 2003, 49(10): 2658-2668
[90] Bergmans P. Random coding theorem for broadcast channels with degraded components. IEEE Transactions on Information Theory, 1973,19(2): 197-207
[91] Wei Y., Cioffi J. M. Sum capacity of Gaussian vector broadcast channels. IEEE Transactions on Information Theory, 2004, 50(9): 1875-1892
[92] Weingarten H., Steinberg Y., Shamai S. The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel. IEEE Transactions on Information Theory, 2006, 52(9): 3936-3964
[93] Jindal N., Rhee W., Vishwanath S., et al. Sum power iterative water-filling for multi-antenna Gaussian broadcast channels. IEEE Transactions on Information Theory, 2005, 51(4): 1570-1580
[94] Hochwald B. M., Peel C. B., Swindlehurst A. L. A vector-perturbation technique for near-capacity multiantenna multiuser communication-part II: perturbation. IEEE Transactions on Communications, 2005, 53(3): 537-544
[95] Tomlinson M. New automatic equaliser employing modulo arithmetic. Electronics Letters, 1971, 7(5): 138-139
[96] Harashima H., Miyakawa H. Matched-Transmission Technique for Channels With Intersymbol Interference. IEEE Transactions on Communications, 1972, 20(4): 774-780
[97] Hunger R., Joham M., Utschick W. Extension of linear and nonlinear transmit filters for decentralized receivers. in: Proc. European Wireless Conf.2005. 40-46
[98] Kusume K., Joham M., Utschick W., et al. Efficient Tomlinson-Harashima precoding for spatial multiplexing on flat MIMO channel. in: Communications, 2005. ICC 2005. 2005 IEEE International Conference on.2005. 2021-2025 Vol. 2023
[99] Windpassinger C., Fischer R. F. H., Vencel T., et al. Precoding in multiantenna and multiuser communications. IEEE Transactions on Wireless Communications, 2004, 3(4): 1305-1316
[100] Chen R., Andrews J. G., Heath R. W., Jr. Transmit selection diversity for multiuser spatial multiplexing systems. in: Global Telecommunications Conference, 2004. GLOBECOM '04. IEEE.2004. 2625-2629 Vol.2624
[101] Chae C. B., Mazzarese D. J., Jr R. W. H. Coordinated beamforming for multiuser MIMO systems with limited feedforward. in: Asilomar Conf. on Sign., Syst, and Computers.2006.
[102] Zhengang P., Kai-Kit W., Tung-Sang N. Generalized multiuser orthogonal space-division multiplexing. IEEE Transactions on Wireless Communications, 2004,3(6):1969-1973
[103]3GPP R1-071044.Ericsson,Precoding Considerations in LTE MIMO Downlink.3GPP TSG RAN WG1 Meeting #48,
[104]3GPP R1-051314.Texas Instruments,Performance of pre-coded MIMO and per group rate control for OFDMA E-UTRA.3GPP TSG RAN WG1 Meeting #43,
[105]3GPP R1-050889.Samsung,MIMO for Long Term Evolution.3GPP TSG RAN WG1 Meeting #42,
[106]王德胜,朱光喜,刘应状,et al.基于虚拟MIMO子信道的多用户分集资源调度算法.计算机科学,2008,(06)
[107]Gesbert D.,Kountouris M.,Heath R.W.,et al.From Single user to Multiuser Communications:Shifting the MIMO paradigm.IEEE Signal Processing Magazine,2007,24(5):36-46
[108]Lai U.C.,Murch R.D.A transmit preprocessing technique for multiuser MIMO systems using a decomposition approach.IEEE Transactions on Wireless Communications,2004,3(1):20-24
[109]Taesang Y.,Goldsmith A.Optimality of zero-forcing beamforming with multiuser diversity,in:Communications,2005.ICC 2005.2005 IEEE International Conference on.2005.542-546 Vol.541
[110]Man K.F.,Tang K.S.,Kwong S.Genetic algorithms:concepts and applications.IEEE Transactions on Industrial Electronics,1996,43(5):519-534
[111]Bertsekas D.,Gallagar R.,Data Networks,1992:Prentice-Hall.
[112]Yanwu D.,Davidson T.N.,Zhi-Quan L.,et al.Minimum BER block precoders for zero-forcing equalization.IEEE Transactions on Signal Processing,2003,51(9):2410-2423
[113]Wengerter C.,Ohlhorst J.,von Elbwart A.G.E.Faimess and throughput analysis for generalized proportional fair frequency scheduling in OFDMA.in.2005.1903-1907 Vol.1903
[114]Holland J.H.,Adaptation in nature and artificial systems,1992,MIT press:Massachusetts.p.
[115]Yoo T.,Goldsmith A.Capacity and power allocation for fading MIMO channels with channel estimation error.IEEE Transactions on Information Theory,2006,52(5):2203-2214
[116]Foschini G J.,Gans M.J.On Limits of Wireless Communications in a Fading Environment when using Multiple Antennas.Wireless personal commnunications,1998,6(311-335)
[117]Yi J.,Hager W.W.,Jian L.The geometric mean decomposition.Linear algebra and its applications,2004,396:373-384
[118]Yi J.,Jian L.,Hager W.W.Joint transceiver design for MIMO communications using geometric mean decomposition.IEEE Transactions on Signal Processing,2005,53(10):3791-3803
[119]张贤达.矩阵分析与应用.清华大学出版社,2004,
[120]Samsung.Downlink MIMO for EUTRA.3GPP TSG RAN WG1 Meeting #43,2005,11:R1-051353
[121]Behrens R.T.,Scharf L.L.Signal processing applications of oblique projection operators.IEEE Transactions on Signal Processing,1994,42(6):1413-1424
[122]Xiang Y.,Lang T.Joint channel and symbol estimation by oblique projections.IEEE Transactions on Signal Processing,2001,49(12):3074-3083
[123]McCloud M.L.,Scharf L.L.A new subspace identification algorithm for high-resolution DOA estimation.IEEE Transactions on Antennas and Propagation,2002,50(10):1382-1390
[124]彭春翌,朱孝龙,张贤达.基于斜投影的卷积信道盲信号分离.清华大学学报(自然科学版),2005,(04):87-90
[125]Murray F.J.On complementary manifolds and projections in L_p and l_p.Trans Amer Math Soc,1937,43:138-152
[126]Lorch E.R.On a calculus of operators in reflexive vector spaces.Trans Amer Math Soc,1939,45:217-234
[127]Afriat S.N.Orthogonal and oblique projectors and the characteristics of pairs of vector spaces.Math PROC Cambridge Philos Soc,1957,53:800-816
[128]Takeuchi K.,Yanai H.,Mukherjee B.N.,The Foundations of Multivariante Analysis,in Wiley,1982:New York.p.
[129]Kayalar S.,Weinert H.L.Oblique projections:Formulas,algorithms,and error bounds.Math of Control,Signals,and Systems,1989,2(1):33-45
[130]Vandaele P.,Moonen M.Two deterministic blind channel estimation algorithms Based on Oblique Projections.Signal Processing,2000,80:481-495
[131]Kerpez K.J.A radio access system with distributed antennas.IEEE Transactions on Vehicular Technology,1996,45(2):265-275
[132]Josiam K.,Rajan D.Multiuser Diversity in Wireless Networks:A Diversity-Multiplexing Perspective.in:Information Sciences and Systems,2007.CISS'07.41 st Annual Conference on.2007.419-419
[133]Gradshteyn I.,Ryzhik I.Table of Integrals,Series,and Products.Academic Press,2003:London
[2] Ping Z., Xiaofeng T., Jianhua Z., et al. A vision from the future: beyond 3G TDD. Communications Magazine, IEEE, 2005,43(1): 38-44
[3] Xiao-Hu Y., Guoan C., Ming C., et al. The FuTURE Project in China. Communications Magazine, IEEE, 2005,43(1): 70-75
[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] TSG-RAN TR 21.905. Vocabulary for 3GPP Specifications. 3GPP, 2008: 6-55
[6] Telatar E. On the capacity of multi-antenna Gaussian channels. European Transactions on Telecommunications, 1999,10(6): 585-595
[7] 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
[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] Tarokh V., Jafarhani H., Calderbank A. R. Space-Time Codes Block Coding from Orthogonal Designs. IEEE JSAC, 1999,48: 1456-1467
[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] 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
[12] Gesbert D., Shafi M., Da-shan S., et al. From theory to practice: an overview of MIMO space-time coded wireless systems. IEEE Journal on Selected Areas in Communications, 2003, 21(3): 281-302
[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] Wolniansky P. W., Foschini G. J., Golden G. D., et al. V-BLAST: an architecture for realizing very high data rates over the rich-scattering wireless channel. 1998 URSI International Symposium on Signals, Systems, and Electronics.1998. 295-300
[15] 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
[16] Wubben D., Rinas J. Efficient Algorithm for Detecting Layered Space-Time Codes. ITG Conference on Source and Channel Coding, 2002: 399-405
[17] Kyu Jong H., Kwang Bok L. Transmit power allocation with small feedback overhead for a multiple antenna system. in: Vehicular Technology Conference, 2002. Proceedings. VTC 2002-Fall, 2002: 2158-2162 vol.2154
[18]Nam S.H.,Oh-Soon S.,Kwang Bok L.Transmit power allocation for a modified V-BLAST system.IEEE Transactions on Communications,2004,52(7):1074-1079
[19]Sellathurai M.,Haykin S.Turbo-BLAST for wireless communications:theory and experiments.IEEE Transactions on Signal Processing,2002,50(10):2538-2546
[20]Hermosilla C.,Szczecinski L.Iterative decoding and iterative detection in MIMO receivers:complexity and performance tradeoffs,in the proc.of Biennial Symposium on Communications,2004:254-256
[21]Tarokh V.,Jafarkhani H.,Calderbank A.R.Space-time block coding for wireless communications:performance results.IEEE Journal on Selected Areas in Communications,,1999,17(3):451-460
[22]Alamouti S.M.A simple transmit diversity technique for wireless communications.IEEE Journal on Selected Areas in Communications,1998,16(8):1451-1458
[23]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
[24]Rupp M.,Mecklenbrauker C.F.On extended alamouti schemes for space time coding.WPMC,2002:115-118
[25]Tarokh V.,Jafarkhani H.A differential detection scheme for transmit diversity.IEEE Journal on Selected Areas in Communications,2000,18(7):1169-1174
[26]Hughes B.L.Differential space-time modulation.IEEE Transactions on Information Theory,2000,46(7):2567-2578
[27]Lizhong Z.,Tse D.N.C.Diversity and multiplexing:a fundamental tradeoff in multiple-antenna channels.IEEE Transactions on Information Theory,2003,49(5):1073-1096
[28]Pedersen K.I.,Mogensen P.E.,Ramiro-Moreno J.Application and performance of downlink beamforming techniques in UMTS.IEEE Communications Magazine,2003,41(10):134-143
[29]Suard B.,Guanghan X.,Hui L.,et al.Uplink channel capacity of space-division-multiple-access schemes.IEEE Transactions on Information Theory,1998,44(4):1468-1476
[30]Spencer Q.H.,Peel C.B.,Swindlehurst A.L.,et al.An introduction to the multi-user MIMO downlink.IEEE Communications Magazine,2004,42(10):60-67
[31]Paulraj A.J.,Nabar R.U.,Gore D.A.Introduction to Space-Time Wireless Communications.Cambridge,2005,
[32]Boyd S.,Vandenberghe L.Convex Optimization.Cambridge University Press,2004,
[33]Wei Y.,Wonjong R.,Boyd S.,et al.Iterative water-filling for Gaussian vector multiple-access channels.IEEE Transactions on Information Theory,2004,50(1):145-152
[34]Cover T.M.,Thomas J.A.Elements of Information Theory.New York:Wiley,1991,
[35]Costa M.Writing on dirty paper.IEEE Transactions on Information Theory,1983,29(3):439-441
[36]Caire G.,Shamai S.On the achievable throughput of a multiantenna Gaussian broadcast channel.IEEE Transactions on Information Theory,2003,49(7):1691-1706
[37]Erez U.,Shamai S.,Zamir R.Capacity and lattice strategies for canceling known interference.IEEE Transactions on Information Theory,2005,51(11):3820-3833
[38]Viswanath P.,Tse D.N.C.Sum capacity of the vector Gaussian broadcast channel and uplink-downlink duality.IEEE Transactions on Information Theory,2003,49(8):1912-1921
[39]Schubert M.,Boche H.Solution of the multiuser downlink beamforming problem with individual SINR constraints.IEEE Transactions on Vehicular Technology,2004,53(1):18-28
[40]Saleh A.,Rustako A.,Roman R.Distributed Antennas for Indoor Radio Communications.IEEE Transactions on Communications,1987,35(12):1245-1251
[41]Wonil R.,Paulraj A.MIMO channel capacity for the distributed antenna,in:Vehicular Technology Conference,2002.Proceedings.VTC 2002-Fall,2002.706-709 vol.702
[42]Wonil R.,Paulraj A.Outage performance of the distributed antenna systems in a composite fading channel,in:Vehicular Technology Conference,2002.Proceedings.VTC 2002-Fall,2002.1520-1524 vol.1523
[43]Roh W.,Paulraj A.Performance of the distributed antenna systems in a multi-cell environment,in:Vehicular Technology Conference,2003.VTC 2003-Spring,2003.587-591 vol.581
[44]王京,姚彦,赵明,et al.分布式无线通信系统的概念平台.电子学报,2002,(07):2-5
[45]Jing W.,Yan Y.,Ming Z.,et al.Conceptual platform of distributed wireless communication system,in:Vehicular Technology Conference,2002.VTC Spring 2002.593-597 vol.592
[46]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
[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]Lin D.,Shidong Z.,Yah Y.Capacity analysis in CDMA distributed antenna systems.IEEE Transactions on Wireless Communications,,2005,4(6):2613-2620
[50]Liang X.,Lin D.,Hairuo Z.,et al.Information-theoretic capacity analysis in MIMO distributed antenna systems,in:Vehicular Technology Conference,2003.VTC 2003-Spring,2003.779-782 vol.771
[51]Zhi N.,Daoben L.Effect of fading correlation on capacity of distributed MIMO.in:Personal,Indoor and Mobile Radio Communications,2004.PIMRC 2004.15th IEEE International Symposium on.2004.1637-1641 Vol.1633
[52]Xiaofeng T.,Chao T.,Zuojun D.,et al.Capacity analyses for a generalized distributed antenna architecture for beyond 3G systems,in:Vehicular Technology Conference,2005.VTC 2005-Spring,2005.3193-3196 Vol.3195
[53]曾昆,唐友喜,田斌,et al.分布式发射天线V-BLAST信号的排序干扰抵消检测.电子与信息学报,2006,(01)
[54]Ying S.,Youxi T.,Ting K.,et al.Optimal antenna location for STBC-OFDM downlink with distributed transmit antennas in linear cells.IEEE Communications Letters,2007,11(5):387-389
[55]Han S.,Zhou S.,Wang J.,et al.Suboptimal Transmission of Orthogonal Space–Time Block Codes Over Correlated Distributed Antennas.IEEE Signal Processing Letters,2007,14(2):89-92
[56]郑海波,王京,周世东,et al.分布式天线系统的多用户分集.电子与信息学报,2007,(11)
[57]Yifan C.,Chau Y.,Yan Z.,et al.Diversity Gains of Generalized Distributed Antenna Systems with Cooperative Users.in:Wireless Communications and Networking Conference,2007.WCNC 2007.IEEE.2007.797-802
[58]Chen P.,Cheng R.-t.,Wu W.-1.Antenna dynamic selection strategies in CDMA distributed antenna systems,in:Advances in Wired and Wireless Communication,2005 IEEE/Sarnoff Symposium on.2005.1-4
[59]赵新胜,尤肖虎,朱定乾.分布式无线移动通信系统中远端天线单元动态选择方法研究.电子与信息学报,2006,(12)
[60]蒋占军,赵新胜,尤肖虎.一种分布式无线移动通信系统中远端天线单元动态选择模型.电子与信息学报,2007,(02)
[61]Heath R.W.,Jr.,Airy M.,Paulraj A.J.Multiuser diversity for MIMO wireless systems with linear receivers,in:Signals,Systems and Computers,2001.Conference Record of the Thirty-Fifth Asilomar Conference on.2001.1194-1199vol.1192
[62]Bender P.,Black P.,Grob M.,et al.CDMA/HDR:a bandwidth efficient high speed wireless data service for nomadic users.IEEE Communications Magazine,2000,38(7):70-77
[63]Viswanath P.,Tse D.N.C.,Laroia R.Opportunistic beamforming using dumb antennas.IEEE Transactions on Information Theory,2002,48(6):1277-1294
[64]Ajib W.,Haccoun D.An overview of scheduling algorithms in MIMO-based fourth-generation wireless systems.IEEE Network,2005,19(5):43-48
[65]Jing J.,Buehrer R.M.,Tranter W.H.Antenna diversity in multiuser data networks.IEEE Transactions on Communications,2004,52(3):490-497
[66]Wei Y.Spatial multiplex in downlink multiuser multiple-antenna wireless environments,in:Global Telecommunications Conference,2003.GLOBECOM'03.IEEE.2003.1887-1891 vol.1884
[67]Zamir R.,Shamai S.,Erez U.Nested linear/lattice codes for structured multiterminal binning.IEEE Transactions on Information Theory,2002,48(6):1250-1276
[68]Peel C.B.,Hochwald B.M.,Swindlehurst A.L.A vector-perturbation technique for near-capacity multiantenna multiuser communication-part Ⅰ:channel inversion and regularization.IEEE Transactions on Communications,2005,53(1):195-202
[69]Taesang Y.,Goldsmith A.On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming.IEEE Journal on Selected Areas in Communications,2006,24(3):528-541
[70]Spencer Q.H.,Swindlehurst A.L.,Haardt M.Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels.IEEE Transactions on Signal Processing,2004,52(2):461-471
[71]Zukang S.,Runhua C.,Andrews J.G.,et al.Sum Capacity of Multiuser MIMO Broadcast Channels with Block Diagonalization.IEEE Transactions on Wireless Communications,2007,6(6):2040-2045
[72]Jalali A.,Padovani R.,Pankaj R.Data throughput of CDMA-HDR a high efficiency-high data rate personal communication wireless system,in:Vehicular Technology Conference Proceedings,2000.VTC 2000-Spring Tokyo.2000 IEEE 51st.2000.1854-1858 vol.1853
[73]Rhee W.,Cioffi J.M.Increase in capacity of multiuser OFDM system using dynamic subchannel allocation,in:Vehicular Technology Conference Proceedings,2000.VTC 2000-Spring Tokyo.2000 IEEE 51st.2000.1085-1089 vol.1082
[74]Ying Jun Z.,Letaief K.B.Optimizing power and resource management for multiuser MIMO/OFDM systems,in:Global Telecommunications Conference,2003.GLOBECOM'03.IEEE.2003.179-183 Vol.171
[75]Meilong J.,Hui D.S.W.,Lau V.K.N.,et al.Cross-layer Downlink Scheduling of Multi-user Multi-Antenna Systems with Heterogeneous Delay Constraints.in:Information Theory,2006 IEEE International Symposium on.2006.2894-2898
[76]Dapeng W.,Negi R.Utilizing multiuser diversity for efficient support of quality of service over a fading channel.IEEE Transactions on Vehicular Technology,2005,54(3):1198-1206
[77]Zhang J.Traffic Meets Fading:A Cross-Layer Design Perspective.in:Proceeding of the 40th Allerton Conference on Communications.2002.1229-1238
[78]Oh-Soon S.,Kwang B.Antenna-assisted round robin scheduling for MIMO cellular systems.IEEE Communications Letters,2003,7(3):109-111
[79]Holtzman J.M.Asymptotic analysis of proportional fair algorithm,in:Personal,Indoor and Mobile Radio Communications,2001 12th IEEE International Symposium on.2001.F-33-F-37 vol.32
[80]Lau V.K.N.A Proportional Fair Space Time Scheduling for Wireless Communications.IEEE Transactions on Communications,2005,53(4):747-747
[81]Yu G.-d.,Zhang Z.-y.,Qiu P.-l.,et al.Fair resource scheduling algorithm for wireless OFDM systems,in:Communications,Circuits and Systems,2005.Proceedings.2005 International Conference on.2005.374-377 Vol.371
[82]Hoon K.,Youngnam H.A proportional fair scheduling for multicamer transmission systems.IEEE Communications Letters,2005,9(3):210-212
[83]Xiangping Q.,Berry R.Opportunistic splitting algorithms for wireless networks,in:INFOCOM 2004.Twenty-third Annual Joint Conference of the IEEE Computer and Communications Societies.2004.1662-1672 vol.1663
[84]Al-Harthi Y.,Tewfik A.,Alouini M.S.Opportunistic scheduling with quantized feedback in wireless networks,in:Information Technology:Coding and Computing,2005.ITCC 2005.International Conference on.2005.716-722 Vol.712
[85]Taiwen T.,Heath R.W.Opportunistic feedback for downlink multiuser diversity.IEEE Communications Letters,2005,9(10):948-950
[86]Svedman P.,Wilson S.K.,Cimini L.J.,Jr.,et al.A simplified opportunistic feedback and scheduling scheme for OFDM. in: Vehicular Technology Conference, 2004. VTC 2004-Spring. 2004 IEEE 59th.2004. 1878-1882 Vol.1874
[87] Koorapaty H., Krasny L., Ramesh R. Delta modulation for channel feedback in transmit diversity systems. in: Vehicular Technology Conference, 2005. VTC 2005-Spring. 2005 IEEE 61st.2005. 644-648 Vol. 641
[88] Sharif M., Hassibi B. A Comparison of Time-Sharing, DPC, and Beamforming for MIMO Broadcast Channels With Many Users. IEEE Transactions on Communications, 2007, 55(1): 11-15
[89] Vishwanath S., Jindal N., Goldsmith A. Duality, achievable rates, and sum-rate capacity of Gaussian MIMO broadcast channels. IEEE Transactions on Information Theory, 2003, 49(10): 2658-2668
[90] Bergmans P. Random coding theorem for broadcast channels with degraded components. IEEE Transactions on Information Theory, 1973,19(2): 197-207
[91] Wei Y., Cioffi J. M. Sum capacity of Gaussian vector broadcast channels. IEEE Transactions on Information Theory, 2004, 50(9): 1875-1892
[92] Weingarten H., Steinberg Y., Shamai S. The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel. IEEE Transactions on Information Theory, 2006, 52(9): 3936-3964
[93] Jindal N., Rhee W., Vishwanath S., et al. Sum power iterative water-filling for multi-antenna Gaussian broadcast channels. IEEE Transactions on Information Theory, 2005, 51(4): 1570-1580
[94] Hochwald B. M., Peel C. B., Swindlehurst A. L. A vector-perturbation technique for near-capacity multiantenna multiuser communication-part II: perturbation. IEEE Transactions on Communications, 2005, 53(3): 537-544
[95] Tomlinson M. New automatic equaliser employing modulo arithmetic. Electronics Letters, 1971, 7(5): 138-139
[96] Harashima H., Miyakawa H. Matched-Transmission Technique for Channels With Intersymbol Interference. IEEE Transactions on Communications, 1972, 20(4): 774-780
[97] Hunger R., Joham M., Utschick W. Extension of linear and nonlinear transmit filters for decentralized receivers. in: Proc. European Wireless Conf.2005. 40-46
[98] Kusume K., Joham M., Utschick W., et al. Efficient Tomlinson-Harashima precoding for spatial multiplexing on flat MIMO channel. in: Communications, 2005. ICC 2005. 2005 IEEE International Conference on.2005. 2021-2025 Vol. 2023
[99] Windpassinger C., Fischer R. F. H., Vencel T., et al. Precoding in multiantenna and multiuser communications. IEEE Transactions on Wireless Communications, 2004, 3(4): 1305-1316
[100] Chen R., Andrews J. G., Heath R. W., Jr. Transmit selection diversity for multiuser spatial multiplexing systems. in: Global Telecommunications Conference, 2004. GLOBECOM '04. IEEE.2004. 2625-2629 Vol.2624
[101] Chae C. B., Mazzarese D. J., Jr R. W. H. Coordinated beamforming for multiuser MIMO systems with limited feedforward. in: Asilomar Conf. on Sign., Syst, and Computers.2006.
[102] Zhengang P., Kai-Kit W., Tung-Sang N. Generalized multiuser orthogonal space-division multiplexing. IEEE Transactions on Wireless Communications, 2004,3(6):1969-1973
[103]3GPP R1-071044.Ericsson,Precoding Considerations in LTE MIMO Downlink.3GPP TSG RAN WG1 Meeting #48,
[104]3GPP R1-051314.Texas Instruments,Performance of pre-coded MIMO and per group rate control for OFDMA E-UTRA.3GPP TSG RAN WG1 Meeting #43,
[105]3GPP R1-050889.Samsung,MIMO for Long Term Evolution.3GPP TSG RAN WG1 Meeting #42,
[106]王德胜,朱光喜,刘应状,et al.基于虚拟MIMO子信道的多用户分集资源调度算法.计算机科学,2008,(06)
[107]Gesbert D.,Kountouris M.,Heath R.W.,et al.From Single user to Multiuser Communications:Shifting the MIMO paradigm.IEEE Signal Processing Magazine,2007,24(5):36-46
[108]Lai U.C.,Murch R.D.A transmit preprocessing technique for multiuser MIMO systems using a decomposition approach.IEEE Transactions on Wireless Communications,2004,3(1):20-24
[109]Taesang Y.,Goldsmith A.Optimality of zero-forcing beamforming with multiuser diversity,in:Communications,2005.ICC 2005.2005 IEEE International Conference on.2005.542-546 Vol.541
[110]Man K.F.,Tang K.S.,Kwong S.Genetic algorithms:concepts and applications.IEEE Transactions on Industrial Electronics,1996,43(5):519-534
[111]Bertsekas D.,Gallagar R.,Data Networks,1992:Prentice-Hall.
[112]Yanwu D.,Davidson T.N.,Zhi-Quan L.,et al.Minimum BER block precoders for zero-forcing equalization.IEEE Transactions on Signal Processing,2003,51(9):2410-2423
[113]Wengerter C.,Ohlhorst J.,von Elbwart A.G.E.Faimess and throughput analysis for generalized proportional fair frequency scheduling in OFDMA.in.2005.1903-1907 Vol.1903
[114]Holland J.H.,Adaptation in nature and artificial systems,1992,MIT press:Massachusetts.p.
[115]Yoo T.,Goldsmith A.Capacity and power allocation for fading MIMO channels with channel estimation error.IEEE Transactions on Information Theory,2006,52(5):2203-2214
[116]Foschini G J.,Gans M.J.On Limits of Wireless Communications in a Fading Environment when using Multiple Antennas.Wireless personal commnunications,1998,6(311-335)
[117]Yi J.,Hager W.W.,Jian L.The geometric mean decomposition.Linear algebra and its applications,2004,396:373-384
[118]Yi J.,Jian L.,Hager W.W.Joint transceiver design for MIMO communications using geometric mean decomposition.IEEE Transactions on Signal Processing,2005,53(10):3791-3803
[119]张贤达.矩阵分析与应用.清华大学出版社,2004,
[120]Samsung.Downlink MIMO for EUTRA.3GPP TSG RAN WG1 Meeting #43,2005,11:R1-051353
[121]Behrens R.T.,Scharf L.L.Signal processing applications of oblique projection operators.IEEE Transactions on Signal Processing,1994,42(6):1413-1424
[122]Xiang Y.,Lang T.Joint channel and symbol estimation by oblique projections.IEEE Transactions on Signal Processing,2001,49(12):3074-3083
[123]McCloud M.L.,Scharf L.L.A new subspace identification algorithm for high-resolution DOA estimation.IEEE Transactions on Antennas and Propagation,2002,50(10):1382-1390
[124]彭春翌,朱孝龙,张贤达.基于斜投影的卷积信道盲信号分离.清华大学学报(自然科学版),2005,(04):87-90
[125]Murray F.J.On complementary manifolds and projections in L_p and l_p.Trans Amer Math Soc,1937,43:138-152
[126]Lorch E.R.On a calculus of operators in reflexive vector spaces.Trans Amer Math Soc,1939,45:217-234
[127]Afriat S.N.Orthogonal and oblique projectors and the characteristics of pairs of vector spaces.Math PROC Cambridge Philos Soc,1957,53:800-816
[128]Takeuchi K.,Yanai H.,Mukherjee B.N.,The Foundations of Multivariante Analysis,in Wiley,1982:New York.p.
[129]Kayalar S.,Weinert H.L.Oblique projections:Formulas,algorithms,and error bounds.Math of Control,Signals,and Systems,1989,2(1):33-45
[130]Vandaele P.,Moonen M.Two deterministic blind channel estimation algorithms Based on Oblique Projections.Signal Processing,2000,80:481-495
[131]Kerpez K.J.A radio access system with distributed antennas.IEEE Transactions on Vehicular Technology,1996,45(2):265-275
[132]Josiam K.,Rajan D.Multiuser Diversity in Wireless Networks:A Diversity-Multiplexing Perspective.in:Information Sciences and Systems,2007.CISS'07.41 st Annual Conference on.2007.419-419
[133]Gradshteyn I.,Ryzhik I.Table of Integrals,Series,and Products.Academic Press,2003:London