User Performance in a 5G Multi-connectivity Ultra-Dense Network City Scenario. - José Mauricio Perdomo; Mårten Ericson; Mats Nordberg; Karl Andersson 001 (LCN, 2020)

LSTM-based QoS prediction for 5G-enabled Connected and Automated Mobility applications. - Sokratis Barmpounakis; Lina Magoula; Nikolaos Koursioumpas; Ramin Khalili; José Mauricio Perdomo; Ramya Panthangi Manjunath (5GWF, 2021)

Deep Learning-based QoS Prediction with Innate Knowledge of the Radio Access Network. - José Mauricio Perdomo; Apostolos Kousaridas; Chan Zhou 001; José F. Monserrat (GLOBECOM, 2021)

QoS Prediction for 5G Connected and Automated Driving. - Apostolos Kousaridas; Ramya Panthangi Manjunath; José Mauricio Perdomo; Chan Zhou 001; Ernst Zielinski; Steffen Schmitz; Andreas Pfadler (IEEE Commun. Mag., 2021)

QoS Prediction-based Radio Resource Management. - José Mauricio Perdomo; Miguel Angel Gutierrez-Estevez; Apostolos Kousaridas; Chan Zhou 001; José F. Monserrat (VTC Fall, 2022)

Towards a Wireless Network Digital Twin Model: A Heterogeneous Graph Neural Network Approach. - José Mauricio Perdomo; Miguel Angel Gutierrez-Estevez; Chan Zhou 001; José F. Monserrat (ICC Workshops, 2023)

WirelessNet: An Efficient Radio Access Network Model Based on Heterogeneous Graph Neural Networks. - José Mauricio Perdomo; Miguel Angel Gutierrez-Estevez; Chan Zhou 001; José F. Monserrat (IEEE Access, 2025)