no code implementations • 14 Feb 2024 • Henk Wymeersch, Sharief Saleh, Ahmad Nimr, Rreze Halili, Rafael Berkvens, Mohammad H. Moghaddam, José Miguel Mateos-Ramos, Athanasios Stavridis, Stefan Wänstedt, Sokratis Barmpounakis, Basuki Priyanto, Martin Beale, Jaap van de Beek, Zi Ye, Marvin Manalastas, Apostolos Kousaridas, Gerhard P. Fettweis
As 6G emerges, cellular systems are envisioned to integrate sensing with communication capabilities, leading to multi-faceted communication and sensing (JCAS).
no code implementations • 5 Aug 2023 • Aneeqa Ijaz, Waseem Raza, Hasan Farooq, Marvin Manalastas, Ali Imran
Thus, the defense mechanism can provide the resilience and robustness for zero touch automation SON engines against the adversarial MDT attacks
no code implementations • 24 Apr 2023 • Haneya Naeem Qureshi, Usama Masood, Marvin Manalastas, Syed Muhammad Asad Zaidi, Hasan Farooq, Julien Forgeat, Maxime Bouton, Shruti Bothe, Per Karlsson, Ali Rizwan, Ali Imran
The extensive survey of training data scarcity addressing techniques combined with proposed framework to select a suitable technique for given type of data, can assist researchers and network operators in choosing appropriate methods to overcome the data scarcity challenge in leveraging AI to radio access network automation.
no code implementations • 6 Feb 2022 • Muhammad Umar Bin Farooq, Marvin Manalastas, Syed Muhammad Asad Zaidi, Adnan Abu-Dayya, Ali Imran
An XGBoost based model has the best performance for edge RSRP and HOSR while random forest outperforms others for load prediction.
no code implementations • 29 Sep 2020 • Syed Muhammad Asad Zaidi, Marvin Manalastas, Hasan Farooq, Ali Imran
The exponential rise in mobile traffic originating from mobile devices highlights the need for making mobility management in future networks even more efficient and seamless than ever before.
no code implementations • 4 May 2020 • Joel Shodamola, Usama Masood, Marvin Manalastas, Ali Imran
Hence, we propose a machine learning-based framework combined with a heuristic technique to discover the optimal combination of two pertinent COPs used in mobility, Cell Individual Offset (CIO) and Handover Margin (HOM), that maximizes a specific Key Performance Indicator (KPI) such as mean Signal to Interference and Noise Ratio (SINR) of all the connected users.