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Ben Yahia, O., Garroussi, Z., Sanso, B., Frigon, J.-F., Martel, S., Lesage-Landry, A., & Karabulut Kurt, G. (2024). A scalable architecture for future regenerative satellite payloads. (Rapport technique n° G-2024-40). Lien externe
Ben Yahia, O., Garroussi, Z., Sanso, B., Frigon, J.-F., Martel, S., Lesage-Landry, A., & Karabulut Kurt, G. (2024). A Scalable Architecture for Future Regenerative Satellite Payloads. IEEE Wireless Communications Letters, 1-1. Lien externe
Hojatian, H., Mlika, Z., Nadal, J., Frigon, J.-F., & Leduc-Primeau, F. (2024). Learning energy-efficient transmitter configurations for massive MIMO beamforming. IEEE Transactions on Machine Learning in Communications and Networking, 2, 939-955. Disponible
Karkan, A. H., Hojatian, H., Frigon, J.-F., & Leduc-Primeau, F. (mai 2024). SAGE-HB: Swift Adaptation and Generalization in Massive MIMO Hybrid Beamforming [Communication écrite]. 2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN 2024), Stockhom, Sweden. Lien externe
Mlika, Z., Do, T. N., Larabi, A., Vo, J. D., Frigon, J.-F., & Leduc-Primeau, F. (octobre 2024). Online energy-efficient beam bandwidth partitioning in mmwave mobile networks [Communication écrite]. IEEE 100th Vehicular Technology Conference (VTC2024-Fall), Washington, DC, USA (6 pages). Lien externe
Yahia, O. B., Garroussi, Z., Bélanger, O., Sanso, B., Frigon, J.-F., Martel, S., Lesage-Landry, A., & Karabulut Kurt, G. (2024). Evolution of High-Throughput Satellite Systems: A Vision of Programmable Regenerative Payload. IEEE Communications Surveys & Tutorials, 3450292 (34 pages). Lien externe
