| QoS prediction for 5G connected and automated driving A Kousaridas, RP Manjunath, J Perdomo, C Zhou, E Zielinski, S Schmitz, ... IEEE Communications Magazine 59 (9), 58-64, 2021 | 30 | 2021 |
| LSTM-based QoS prediction for 5G-enabled Connected and Automated Mobility applications S Barmpounakis, L Magoula, N Koursioumpas, R Khalili, JM Perdomo, ... 2021 IEEE 4th 5G World Forum (5GWF), 436-440, 2021 | 16 | 2021 |
| User performance in a 5G multi-connectivity ultra-dense network city scenario J Perdomo, M Ericsson, M Nordberg, K Andersson 2020 IEEE 45th Conference on Local Computer Networks (LCN), 195-203, 2020 | 10 | 2020 |
| QoS Prediction-based Radio Resource Management J Perdomo, MA Gutierrez-Estevez, A Kousaridas, C Zhou, JF Monserrat 2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall), 10.1109 …, 2022 | 4 | 2022 |
| Deep learning-based QoS prediction with innate knowledge of the radio access network J Perdomo, A Kousaridas, C Zhou, JF Monserrat 2021 IEEE Global Communications Conference (GLOBECOM), 1-6, 2021 | 4 | 2021 |
| UE performance in a 5G multi-connectivity UDN city scenario J Perdomo | 1 | 2019 |
| 6G & Robotics: A Methodology to Identify Potential Service Requirements for 6G-empowered Robotic Use Cases RPM Mohammad Shikh-Bahaei, Albena Dimitrova Mihovska, Nidhi N., Periklis ... https://one6g.org/resources/publications/, 2023 | | 2023 |
| Towards a Wireless Network Digital Twin Model: A Heterogeneous Graph Neural Network Approach J Perdomo, MA Gutierrez-Estevez, C Zhou, JF Monserrat 2023 IEEE International Conference on Communications Workshops (ICC …, 2023 | | 2023 |
