2021
DOI: 10.1016/j.sigpro.2021.108132
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Coordinated versus uncoordinated channel tracking for high-rate internet of things in multiuser massive MIMO: Algorithms and performance

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Cited by 8 publications
(3 citation statements)
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“…As Appendix A proves, for large scale antenna arrays, this boils down to selecting the N U i eigenvectors associated to the N U i eigenvalues that are closest to 1. Each of them tends to the MV beamformer (22) in the direction of the terminal that is targeted. The beauty of the proposed beamforming technique is that the terminals can be distinguished and separated, as long as they are not located in the same spot, without estimating the channel nor making a beam scan.…”
Section: Resource Sharing Beamforming Accessmentioning
confidence: 99%
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“…As Appendix A proves, for large scale antenna arrays, this boils down to selecting the N U i eigenvectors associated to the N U i eigenvalues that are closest to 1. Each of them tends to the MV beamformer (22) in the direction of the terminal that is targeted. The beauty of the proposed beamforming technique is that the terminals can be distinguished and separated, as long as they are not located in the same spot, without estimating the channel nor making a beam scan.…”
Section: Resource Sharing Beamforming Accessmentioning
confidence: 99%
“…Hence, for large scale antenna array systems, any vector that belongs to {h k |k ∈ N i } solves (21). Closely analyzing (22) we can also resolve that, under the orthogonality conditions, the MV beamformer is proportional to the array vector (8) in the direction of the user of interest. The immediate consequence that results from the orthogonality is that the vector that fulfils ( 16) is proportional to the MV beamformer.…”
Section: Conflicts Of Interestmentioning
confidence: 99%
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