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作 者:Hongyun CHU Wei FENG Maoqi LI Zhichao ZHU Guilu WU
机构地区:[1]School of Communications and Information Engineering,Xi'an University of Posts and Telecommunications,Xi’an 710121,China [2]National Mobile Communications Research Laboratory,Southeast University,Nanjing 211189,China [3]School of Internet of Things Engineering.Jiangnan University,Wuxi 214122,China
出 处:《Science China(Information Sciences)》2021年第11期241-242,共2页中国科学(信息科学)(英文版)
基 金:supported by IoT Innovation Team for Talent Promotion Plan of Shaanxi Province(Grant No.2019TD-028);XUPT New Doctor Startup Funds(Grant No.101/205020044);Open Research Fund of National Mobile Communications Research Laboratory,Southeast University(Grant No.2020D17)。
摘 要:Dear editor,The acquirement of the channel state information(CSI) is indispensable for designing efficient beamformers [1]. Unfortunately, estimating CSI is extremely challenging in the mm Wave/THz systems where the number of antennas is super-large and the receive signal-to-noise ratio(SNR) is relatively low. Most of the existing estimators are based on the direct applications of inherent channel sparsity and generic compressive sensing(CS) techniques, which cannot lead to fine enough performances in channel estimation because it puts strict requirements on the channel sparsity or the data measurements [2–7].
关 键 词:channel estimation Wave
分 类 号:TN925[电子电信—通信与信息系统]
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