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.
Ahmad B., Riviello D.G., Guidotti A., Vanelli-Coralli A. (2023). Graph-Based User Scheduling Algorithms for LEO-MIMO Non-Terrestrial Networks. 345 E 47TH ST, NEW YORK, NY 10017 USA : Institute of Electrical and Electronics Engineers Inc. [10.1109/EuCNC/6GSummit58263.2023.10188287].
Graph-Based User Scheduling Algorithms for LEO-MIMO Non-Terrestrial Networks
Ahmad B.Primo
;Riviello D. G.
Secondo
;Guidotti A.Penultimo
;Vanelli-Coralli A.Ultimo
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.