During this year’s EuCNC & 6G Summit that took place from June 8-10, 2022, in Grenoble, DYNASAT presented its paper entitled “Location-assisted precoding in 5G LEO systems: architectures and performances”. The paper, presented by DYNASAT team member Carla Amatetti from the University of Bologna, focuses on advanced system-level techniques to increase the capacity offered by the satellite in order to meet the 5G and B5G requirements.
“Precoding techniques for single and multiple satellite, as those designed in DYNASAT, enable non-terrestrial networks (NTN) based on Low Earth Orbit (LEO) constellation to meet the requirements of 5G/B5G by not only complementing and extending the terrestrial coverage, but also offering new services, improving the system flexibility, adaptability, and resilience” said Carla Amatetti concluding the presentation.
About the paper
Satellite communication systems are a fundamental component in support of Europe’s ambition to deploy smart and sustainable networks and services for the success of its digital economy. To cope with the 5G and beyond ever increasing demand for larger throughput, aggressive frequency reuse schemes i.e., full frequency reuse), with the implementation of precoding/beamforming to cope with the massive co-channel interference, are recognised as one of the key technologies. While the best performance can be obtained with the knowledge of the Channel State Information (CSI) at the transmitter, this also poses some technical challenges related to signalling and synchronisation. In this paper, we focus on precoding solutions that only needs the knowledge of the users’ positions at the transmitter side, namely the recently introduced Switchable Multi-Beam (MB) and Spatially Sampled MMSE (SS-MMSE) precoding. Compared to the vast majority of the studies in the literature, we take into account both the users’ and the satellite movement in a Low Earth Orbit (LEO) mega-constellation, also proposing two system architectures. The extensive numerical assessment provides a valuable insight on the performance of these two precoding schemes compared to the optimal MMSE solution.
Authors: Alessandro Guidotti, Carla Amatetti, Fabrice Arnal, Baptiste Chamaillard, and Alessandro Vanelli-Coralli.