Algorithms for simultaneous sparse approximation: part I: Greedy pursuit
Signal Processing - Sparse approximations in signal and image processing
Algorithms for simultaneous sparse approximation: part II: Convex relaxation
Signal Processing - Sparse approximations in signal and image processing
Compressive data gathering for large-scale wireless sensor networks
Proceedings of the 15th annual international conference on Mobile computing and networking
Sum-rate analysis of multiuser MIMO system with zero-forcing transmit beamforming
IEEE Transactions on Communications
Generalized reconstruction algorithm for compressed sensing
Computers and Electrical Engineering
Theoretical Results on Sparse Representations of Multiple-Measurement Vectors
IEEE Transactions on Signal Processing
Reduce and Boost: Recovering Arbitrary Sets of Jointly Sparse Vectors
IEEE Transactions on Signal Processing - Part I
Sparse solutions to linear inverse problems with multiple measurement vectors
IEEE Transactions on Signal Processing
On beamforming with finite rate feedback in multiple-antenna systems
IEEE Transactions on Information Theory
Decoding by linear programming
IEEE Transactions on Information Theory
MIMO Broadcast Channels With Finite-Rate Feedback
IEEE Transactions on Information Theory
Multi-Antenna Downlink Channels with Limited Feedback and User Selection
IEEE Journal on Selected Areas in Communications
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In multiple-input-multiple-output (MIMO) broadcast channel the throughput can be enhanced by channel state information (CSI) feedback, but it is resources and feedback expensive. We propose a compressed sensing (CS) feedback scheme for zero-forcing beamforming (ZFBF) in MIMO broadcast channel, which can reduce the feedback load and resource consumption. The feedback channels are shared and opportunistically accessed by users who are self pre-selected based on their channel vectors' norm and correlation. Multiple measurement vectors (MMV) CS is used for the CSI feedback. Orthogonal matching pursuit and reduced MMV and boost algorithms are applied for CS recovery to get the CSI. Semi-orthogonal user selection and ZFBF are implemented at the base station to achieve spatial multiplexing gain. Both the analog and digital CS feedback schemes are analyzed. Simulations show that the proposed CS feedback has good performances compared with traditional feedback schemes in points of feedback load and throughput due to user self pre-selection algorithm and CS feedback.