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Article Dans Une Revue IEEE Networking Letters Année : 2022

Smart Link Adaptation and Scheduling for IIoT

Résumé

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.
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Dates et versions

hal-04273900 , version 1 (07-11-2023)

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Miroslav Mitev, M. Majid Butt, Philippe Sehier, Arsenia Chorti, Luca Rose, et al.. Smart Link Adaptation and Scheduling for IIoT. IEEE Networking Letters, 2022, 4 (1), pp.6-10. ⟨10.1109/LNET.2022.3144733⟩. ⟨hal-04273900⟩
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