In this paper, we study the user scheduling prob-lem in a Low Earth Orbit (LEO) Multi-User Multiple-Input-Multiple-Output (MIMO) system. We propose an iterative graph-based maximum clique scheduling approach, in which users are grouped together based on a dissimilarity measure and served by the satellite via space-division multiple access (SDMA) by means of Minimum Mean Square Error (MMSE) digital beamforming on a cluster basis. User groups are then served in different time slots via time-division multiple access (TDMA). As dissimilarity measure, we consider both the channel coefficient of correlation and the users' great circle distance. A heuristic optimization of the optimal cluster size is performed in order to maximize the system capacity. To further validate our analysis, we compare our proposed graph-based schedulers with the well-established algorithm known as Multiple Antenna Downlink Orthogonal clustering (MADOC). Results are presented in terms of achievable per-user capacity and show the superiority in performance of the proposed schedulers w.r.t. MADOC.

Graph-Based User Scheduling Algorithms for LEO-MIMO Non-Terrestrial Networks / Ahmad, B.; Riviello, D. G.; Guidotti, A.; Vanelli-Coralli, A.. - ELETTRONICO. - (2023), pp. 270-275. (Intervento presentato al convegno 2023 Joint European Conference on Networks and Communications and 6G Summit, EuCNC/6G Summit 2023 tenutosi a Gothenburg, Sweden nel 6-9 June 2023) [10.1109/EuCNC/6GSummit58263.2023.10188287].

Graph-Based User Scheduling Algorithms for LEO-MIMO Non-Terrestrial Networks

Riviello D. G.;
2023

Abstract

In this paper, we study the user scheduling prob-lem in a Low Earth Orbit (LEO) Multi-User Multiple-Input-Multiple-Output (MIMO) system. We propose an iterative graph-based maximum clique scheduling approach, in which users are grouped together based on a dissimilarity measure and served by the satellite via space-division multiple access (SDMA) by means of Minimum Mean Square Error (MMSE) digital beamforming on a cluster basis. User groups are then served in different time slots via time-division multiple access (TDMA). As dissimilarity measure, we consider both the channel coefficient of correlation and the users' great circle distance. A heuristic optimization of the optimal cluster size is performed in order to maximize the system capacity. To further validate our analysis, we compare our proposed graph-based schedulers with the well-established algorithm known as Multiple Antenna Downlink Orthogonal clustering (MADOC). Results are presented in terms of achievable per-user capacity and show the superiority in performance of the proposed schedulers w.r.t. MADOC.
2023
979-8-3503-1102-0
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2984029