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Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
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Scheduling for Downlink Non-Orthogonal Multiple Access in Wi-Fi Networks

P. 1–6.
Тутельян С. А., Khorov E.

Non-orthogonal multiple access (NOMA) is a radio access technology that allows significantly improving network performance in scenarios with high heterogeneity. While being typically studied for cellular networks, NOMA can also be used in Wi-Fi networks. This paper proposes a scheduling approach for NOMA-aware resource scheduling in Wi-Fi. This approach is implemented to design NOMA-aware downlink schedulers which follow such wide-spread strategies as max-rate, proportional-fair and shortest-remaining-processing-time.

Language: English
DOI
Keywords: Wi-FiNOMA

In book

2018 International Scientific and Technical Conference Modern Computer Network Technologies (MoNeTeC)
IEEE, 2018.
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