Rician信道下基于信道均值信息的自适应反馈方案

杨亥娟; 邱玲

doi:10.3724/SP.J.1146.2008.01213

Rician信道下基于信道均值信息的自适应反馈方案

doi: 10.3724/SP.J.1146.2008.01213

杨亥娟,
邱玲

基金项目:

国家863计划项目(2006AA01Z266)和国家973计划项目(2007CB310602)资助课题

计量
- 文章访问数: 3218
- HTML全文浏览量: 83
- PDF下载量: 855
- 被引次数: 0
出版历程
- 收稿日期: 2008-09-25
- 修回日期: 2009-04-23
- 刊出日期: 2009-08-19

Adaptive Feedback for Rician Channel Exploiting Channel Mean Information

摘要

摘要: 在多天线多用户下行系统中，当信道为莱斯(Rician)衰落时，基于瑞利(Rayleigh)信道假设设计出的有限反馈方法将会导致系统反馈开销的浪费。该文提出了一种适用于Rician信道的自适应反馈方案。该方案根据各用户信道的均值信息计算出相应的信道方向分布函数，然后利用其函数设计判决门限来调整各用户的量化反馈码本，使各用户量化码本中的码字矢量更加集中在用户信道矢量方向周围。另外，该方案可以自适应于不同的信道分布，在保证一定的量化误差下，根据信道均值的大小自适应调节各用户的反馈比特数，显著减少了用户的反馈量。仿真结果表明，与基于Rayleigh信道假设的有限反馈方案相比，该文提出的自适应反馈方案在不降低系统的吞吐率性能的前提下显著降低了用户的反馈开销。
- 下行多天线多用户系统;Rician信道;有限反馈;随机向量量化;量化误差
Abstract: In multi-user multi-antenna downlink system, when the channels are Rician channels, the performance of those limited feedback strategies designed for uncorrelated Rayleigh Channels will result to the waste of feedback overhead. To solve this problem, a new adaptive feedback strategy is proposed in Rician channels. First, a new concept of the angle distance distribution in the Rician channel is introduced. Based on this theory and using the channel mean information at the transmitter, the proposed strategy can design a special threshold to adjust users codebook, which is closer to the channel direction. Moreover, this strategy can still adjust its number of feedback bits adaptively according to different channel distributions without increasing the quantized error of channel direction. The simulation shows that, compared to those strategies proposed for Rayleigh systems, the strategy can reduce feedback overhead greatly without decreasing system sum-rate.

HTML全文

参考文献(1)

Costa M. Writing on dirty paper[J].IEEE Transactions onInformation Theory.1983, 29(3):439-441[2]Spencer Q, Swindlehurst A L, and Haardt M. Zero-forcingmethods for downlink spatial multiplexing in multiuserMIMO channels[J].IEEE Transactions on SignalProcessing.2004, 52(2):461-471[3]Sharif M and Hassibi B. Scaling laws of sum rate usingtime-sharing, DPC, and beamforming for MIMO broadcastchannels[C]. IEEE International Symposium InformationTheory, Chicago, 2004: 175.[4]Jindal N. MIMO broadcast channels with finite ratefeedback[C]. IEEE GLOBECOM, MN, USA, 2005:1520-1524.[5]Yoo T, Jindal N, and Goldsmith A. Multi-antenna downlinkchannels with limited feedback and user selection[J].IEEEJournal Selected Areas in Communication.2007, 25(7):1478-1491[6]Hammarwall D, Bengtsson M, and Ottersten B. Acquiringpartial CSI for spatially selective transmission byinstantaneous channel norm feedback[J].IEEETransactions on Signal Processing.2008, 56(3):1188-1204[7]Oteri O, Yoon E, and Paulraj A. Linear precoding forhigh-K-factor channels exploiting channel mean andcovariance information[J]. IEEE Transactions on VehicularTechnology, 2007, 56(5): 2581-2589.[8]Kim I M, Yi Zhihang, and Kim D, et al.. Improvedopportunistic beamforming in Ricean channels[J].IEEETransactions on Communication.2006, 54(12):2199-2211[9]Yoo T and Goldsmith A. On the optimality of multiantennabroadcast scheduling using zero-forcing beamforming[J].IEEE Journal Selected Areas in Communication.2006, 24(3):528-541[10]Yeung C A and Love D J. On the performance of randomvector quantization limited feedback beamforming in a MISOsystem[J].IEEE Transactions on Wireless Communication.2007, 6(2):458-462[11]Mukkavilli K K, Sabharwal A, and Erkip E, et al.. Onbeamforming with finite rate feedback in multiple-antennasystems[J].IEEE Transactions on Information Theory.2003,49(10):2562-2579[12]李博纳, 赵新泉. 概率论与数理统计[M]. 北京: 高等教育出版社, 2006: 257-258.

施引文献

资源附件(0)

访问统计