Machine Learning Techniques for Non-Terrestrial Networks
نویسندگان
چکیده
Traditionally, non-terrestrial networks (NTNs) are used for a limited set of applications, such as TV broadcasting and communication support during disaster relief. Nevertheless, due to their technological improvements integration in the 5G 3GPP standards, NTNs have been gaining importance last years will provide further applications services. standardization is integrating low-Earth orbit (LEO) satellites, high-altitude platform stations (HAPSs) unmanned aerial systems (UASs) elements (NTEs) within terrestrial standard. Considering NTE characteristics (e.g., traffic congestion, processing capacity, oscillation, altitude, pitch), it difficult dynamically optimal connection based also on required service properly steer antenna beam or schedule UE. To this aim, machine learning (ML) can be helpful. In paper, we present novel services supported by architectures standards. Then, ML techniques proposed managing NTN connectivity well improve performance.
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ژورنال
عنوان ژورنال: Electronics
سال: 2023
ISSN: ['2079-9292']
DOI: https://doi.org/10.3390/electronics12030652