CSIT estimation and feedback for FDD multi-user massive MIMO systems

ICASSP(2014)

引用 25|浏览15
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摘要
To fully utilize the spatial multiplexing gains or array gains of massive MIMO, the channel state information must be obtained at the transmitter side (CSIT). However, conventional CSIT estimation approaches are not suitable for FDD massive MIMO systems because of the overwhelming training and feedback overhead. In this paper, we consider multi-user massive MIMO systems and deploy the compressive sensing (CS) technique to reduce the training as well as the feedback overhead in the CSIT estimation. We propose a distributed compressive CSIT estimation and feedback scheme to exploit the hidden joint sparsity structure in the user channel matrices and we obtain simple insights into how the joint channel sparsity can be exploited to improve the CSIT recovery performance.
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关键词
multiuser channels,channel state information,fdd multiuser massive mimo systems,csit estimation and feedback,user channel matrices,radio transmitters,distributed compressive csit estimation-and- feedback scheme,compressive sensing (cs),fading channels,csit recovery performance improvement,matrix algebra,space division multiplexing,array gains,overwhelming training,massive mimo,compressed sensing,mimo communication,spatial multiplexing gains,flat block-fading multiuser massive multiinput multioutput system,transmitter side,hidden joint sparsity structure,training reduction,feedback overhead,compressive sensing technique,wireless communication,sparse matrices,mimo,estimation
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