An overview of limited feedback in wireless communication systems

By D. J. Love, Robert W. Heath, Vincent Kin Nang Lau, David Gesbert, Bhaskar D. Rao, Matthew Andrews. IEEE Journal on Selected Areas in Communications, 2008

1,546 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/47fdb5fbb423eb9a0853b52fa26dc1619dfea6cd

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Citations in the corpus

Machine Learning in the Air (2019, methodology): “CSI feedback reduction techniques based on vector quantization [38] are also limited, particularly for massive MIMO systems, as the codebook size, and thus, grow proportionally with the number of transmit antennas.”
Communication-Efficient Edge AI: Algorithms and Systems (2020, background): “In wireless communication systems, limited feedback [22] from a receiver to a transmitter is critical to reducing the information bits for realizing channel agile techniques that require channel knowledge at the transmitter.”
Outage Constrained Robust Transmit Optimization for Multiuser MISO Downlinks: Tractable Approximations by Conic Optimization (2011, background): “Tr( A ) and λ max ( A ) denote the trace and maximum eigenvalue of A , respectively. vec( A ) stands for the vector obtained by stacking the column vectors of A .”
Multi-Panel MIMO in 5G (2018, methodology): “To characterize the channel directional information, the codebook and related feedback mechanism are usually designed for CSI acquisition, especially for frequency-division duplex (FDD) systems [7].”
Design Guidelines for Spatial Modulation (2015, methodology): “onalizing the channel matrix [39], which may jeopardize the”
Frequency Selective Hybrid Precoding for Limited Feedback Millimeter Wave Systems (2015, background): “Further, they normally offer a close performance to the total power constraint [37].”
High-Dimensional Stochastic Gradient Quantization for Communication-Efficient Edge Learning (2020, background): “Inwireless communication, Grassmannian quantization is widely adopted in one particular area, limited feedback, for efﬁcient feedback of a quantized beamformer/precoder from a receiver to a transmitter to enable adaptive multi-antenna transmission [15]–[20].”
Communications and Signals Design for Wireless Power Transmission (2016, methodology): “In principle, CSIT in WPT systems could be acquired with similar techniques as those developed in wireless communication systems [119].”
Simultaneous Information and Power Transfer for Broadband Wireless Systems (2012, methodology): “Note that transmit beamforming is particularly suitable for cellular systems where feedback methods have been implemented for acquiring transmit CSI [13].”
Multi-Cell MIMO Cooperative Networks: A New Look at Interference (2010, methodology): “Since a rich body of literature already exists for this problem, we simply refer the reader to past special journal issues on this topic such as [16], [145].”
Convolutional Neural Network-Based Multiple-Rate Compressive Sensing for Massive MIMO CSI Feedback: Design, Simulation, and Analysis (2019, background): “To address this issue, the CSI matrix should be efficiently compressed [10], [11], which can be based on compressive sensing (CS) or deep learning (DL).”
Limited Feedback Hybrid Precoding for Multi-User Millimeter Wave Systems (2014, methodology): “RVQ simplifies the analytical performance analysis of the proposed algorithm and allows leveraging some results from the limited feedback MIMO literature [25], [28], [34].”
Compressive sensing based channel feedback protocols for spatially-correlated massive antenna arrays (2012, neutral): “Conventional CSI feedback reduction methods, such as vector quantization or codebook-based approaches [5], may not be suitable for Massive-MIMO as the codebook size has to be expanded extensively (which leads to heavier feedback overhead) to capture fine-grain spatial channel structures.”
High-Dimensional Stochastic Gradient Quantization for Communication-Efficient Edge Learning (2019, neutral): “Vector quantization has been widely applied in limited feedback [11]–[14].”
MIMO over Satellite: A Review (2011, background): “ited feedback in wireless MIMO has seen an explosive growth lately [56] due to the need of setting MIMO onto a more”
Large System Analysis of Linear Precoding in Correlated MISO Broadcast Channels Under Limited Feedback (2009, background): “For this reason, a lot of research has been carried out to understand the impact of imperfect CSIT on the system behavior; see [14] for a recent survey.”
Massive Access for 5G and Beyond (2020, methodology): “In frequency division duplex (FDD) systems, the devices first obtain the CSI by channel estimation and then feed back the quantized CSI to the BTS [102].”