期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

基于MF预编码的大规模MIMO网络SINR概率密度分析 被引量：2

Probability Density Analysis of SINR in Massive MIMO Downlink Using Matched Filter Beamformer
下载PDF
导出
摘要 大规模MIMO系统中,相对于其他基于信道矩阵分解的波束成形算法,如迫零、最小均方误差算法等,匹配滤波(Matched filter,MF)具有复杂度极低的优点,从而成为一种极具实用潜力的波束成形算法。鉴于此,本文推导了基站采用MF波束成形算法时,用户端信干噪比(Signal-to-interferenceand-noise ratio,SINR)的近似概率密度函数(Probability density function,PDF)。该函数对于推导与分析系统性能,如和速率、中断概率等至关重要。仿真表明:当基站天线数趋于大规模时,SINR公式的PDF曲线趋近于通过纯仿真得到的PDF曲线。 In massive MIMO systems, the matched filter （MF） beamformer is an attractive technique due to its extremely low complexity compared with the high-complexity decomposition-based beamforming techniques, such as zero forcing and minimum mean square error. An approximate formula is derived for probability density function （PDF） of the signal-to-interference-and-noise ratio （SINR） at user terminal when multiple antennas and the MF beamformer are used at the base station. The formula is important in calculating or analyzing system performance such as sum-rate and outage probability. Simulations exhibit that the difference between the derived approximate formula for PDF and the simulated PDF approaches zero while the number of antennas at the base station tends to large-scale.
作者 束锋 李隽 顾晨 王进 周叶 徐彦青 钱玉文
机构地区 南京理工大学电子工程与光电技术学院 东南大学移动通信国家重点实验室 南京理工大学近程高速目标探测技术国防重点学科实验室
出处 《数据采集与处理》 CSCD 北大核心 2015年第3期496-503,共8页 Journal of Data Acquisition and Processing
基金 国家自然科学基金(61271230 61472190)资助项目 中央高校基本科研业务费专项资金(30920130122004)资助项目 东南大学移动通信国家重点实验室开放课题(2013D02)资助项目
关键词 大规模多天线系统 匹配滤波 信干噪比 概率密度函数 massive MIMO matched filter signal-to-interference-and-noise ratio~ probability densityfunction
分类号 TN929.5 [电子电信—通信与信息系统]
  • 相关文献

参考文献2

二级参考文献23

  • 1Caire G, Shamai (Shitz) S. On the achievable throughput of a multiantenna Gaussian broadcast channel [J]. IEEE Transactions Information Theo- ry, 2003, 49(7): 1691-1706.
  • 2Sharif M, Hassibi B. A comparsion of time-sharing, DPC and beamforming for MIMO broadcast channels with many users [J]. IEEE Transaction on Commu- nication, 2007, 55(1): 11-15.
  • 3Yoo T, Goldsmith A, On the optimality of multi- antenna broadcast scheduling using zero-forcing beamformirig [J]. IEEE Journal on Selected Areas in Communications, 2006, 24(3): 528-541.
  • 4Choi L, Murch R D. A transmit preprocessing tech- nique for multiuser MIMO systems using a decompo- sition approach [J]. IEEE Transaction on Wireless Communication, 2004, 3(1): 20-24.
  • 5Sharif M, Hassibi B. On the capacity of MIMO broadcast channels with partial side information [J]. IEEE Transactions on Information Theory, 2005, 51 (2) : 506-522.
  • 6Vucetic B, Yuan J. Space-time coding [M]. Chieh- ester England:John Wiley : Sons Ltd, 2003 : 55-59.
  • 7Jindal N. Antenna combining for the MIMO down- link channel [J]. IEEE Transactions on Wireless Communications, 2008, 7(10): 3834-3844.
  • 8Trivellato M, Huang H. Antenna combining and codebook design for the MIMO broadcast channel with limited feedback [C]//Asilomar Conference on Signals, Systems, Computers 2007. Pacific Grove, USA : [s. n. ], 2007 : 302-308.
  • 9Kim J, Kim H, Park C S,et al. On the performance of multiuser MIMO system in WCDMA/HSDPA: Beamforming, feedback and user diversity[J]. IE- ICE Transaction on Communication, 2006, E89-B (8) : 2161-2169.
  • 10Hassibi ]3, Marzetta T L. Multiple-antennas and isotropically random unitary inputs: the received sig- nal density in closed form[J]. IEEE Transaction on Information Theory, 2002, 48(6): 1473-1484.

共引文献6

同被引文献20

  • 1Rusek F, Persson D, Lau B K, et al. Scaling up MIMO: Opportunities and challenges with very large arrays[J]. IEEE Sig- nal Processing Magazine, 2013,30 (1) : 40-60.
  • 2Marzetta T L. Noncooperative cellular wireless with unlimited numbers of base station antennas[J]. IEEE Transactions on Wireless Communication, 2010,9(11) : 3590-3600.
  • 3Larsson E G, Tufvesson F, Edfors O, et at. Massive MIMO for next generation wireless systems[J]. IEEE Communication Magazine, 2014,52(2) :186-195.
  • 4Hoydis J, Brin S T, Debbah M. Massive MIMO in the UL/DL of cellular networks: How many antennas do we need[J]. IEEE Journal Selected Areas Communications, 2013,31 (2) : 160-171.
  • 5Spencer Q H, Swindlehust A L, Haardt M. Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels[J]. IEEE Transactions Signal Processing, 2004,52 (2) : 461-471.
  • 6Wiesel A, Eldar Y C, Shamai S. Zero-forcing precoding and generalized inverses[J]. IEEE Transactions Signal Processing, 2008,56(9) :4409-4418.
  • 7Choi L U, Mureh R D. A transmit preproeessing technique for muhiuser MIMO systems using a decomposition approach[J]. IEEE Transactions Wireless Communication, 2004,3 (1) : 20-24.
  • 8. Sadek M, Tarighat A, Sayed A H. A leakage-based precoding scheme for downlink multi-user MIMO channels[J]. IEEE.Transactions Wireless Communication, 2007,6(5):1711-1721.
  • 9Liu W, Yang L L, Hanzo L. SVD-assisted multiuser transmitter and multiuser detector design for MIMO systems[J]. IEEE Transactions Vehicle Technology, 2009,58(2) :1016-1021.
  • 10Peel C B, Hochwald B M, Swindlehurst A L. A vector-perturbation technique for near-capacity multi-antenna multiuser communication-part I : Channel inversion and regularization[J]. IEEE Transactions Communication, 2005,53( 1 ) : 195-202.

引证文献2

二级引证文献2

数据采集与处理
2015年 第3期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部