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- W4205248879 abstract "A machine learning enabled link adaption (LA) and scheduling framework is presented for Industrial Internet of Things (IIoT), leveraging quasi-periodicity of traffic in IIoT. The following steps are introduced: i) a reduced complexity link establishment accounting jointly for beamforming and load management; ii) interference prediction using long short-term memory neural networks; iii) semi-coordinated scheduling based on node grouping for interference avoidance. Through numerical evaluation it is demonstrated that the proposed approach can substantially improve average spectral efficiency by as much as 62% in a realistic IIoT scenario at negligible overhead." @default.
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- W4205248879 date "2022-03-01" @default.
- W4205248879 modified "2023-10-06" @default.
- W4205248879 title "Smart Link Adaptation and Scheduling for IIoT" @default.
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- W4205248879 doi "https://doi.org/10.1109/lnet.2022.3144733" @default.
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