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On Linearly Precoded Rate Splitting for Gaussian MIMO Broadcast Channels

On linearly precoded rate splitting for Gaussian MIMO broadcast channels
descriptionPublicationkeyboard_double_arrow_right Article , Preprint 01 Jul 2021Embargo end date: 01 Jan 2018Publisher:Institute of Electrical and Electronics Engineers (IEEE)Journal:IEEE Transactions on Information Theory, volume 67, pages 4,693-4,709 (issn: 0018-9448, eissn: 1557-9654, Copyright policy )Funded by:EC | CloudRadioNet
Authors: Zheng Li; Sheng Yang 0001; Shlomo Shamai;

doi: 10.1109/tit.2021.3076888 , 10.5281/zenodo.4998636 , 10.5281/zenodo.4998637 , 10.48550/arxiv.1808.01810

arXiv: 1808.01810

On Linearly Precoded Rate Splitting for Gaussian MIMO Broadcast Channels

Abstract

IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 67, NO. 7, JULY 2021

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Keywords

FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT), many user Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC), Channel models (including quantum) in information and communication theory, linearly precoded transmission schemes

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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13
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Average
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5
14
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