8 citations · 9 across the 8 of their papers we have counts for
8 papers
Domain Adaptation Under Wireless Network Constraints: When Does It Become Green?
Illyyne Saffar, Aurélie Boisbunon, Shruti Bothe
The deployment of data-driven models in 6G wireless networks is increasingly challenged by frequent distribution shifts that degrade performance over time. Unsupervised Domain Adap…
Optimizing Reinforcement Learning Training over Digital Twin Enabled Multi-fidelity Networks
Hanzhi Yu, Hasan Farooq, Julien Forgeat +4
In this paper, we investigate a novel digital network twin (DNT) assisted deep learning (DL) model training framework. In particular, we consider a physical network where a base st…
Through the telecom lens: Are all training samples important?
Shruti Bothe, Illyyne Saffar, Aurelie Boisbunon +3
The rise of AI in telecommunications, from optimizing Radio Access Networks to managing user experience, has sharply increased data volumes and training demands. Telecom data is of…
Towards Green AI-Native Networks: Evaluation of Neural Circuit Policy for Estimating Energy Consumption of Base Stations
Selim Ickin, Shruti Bothe, Aman Raparia +2
Optimization of radio hardware and AI-based network management software yield significant energy savings in radio access networks. The execution of underlying Machine Learning (ML)…
Multi-Task Learning as enabler for General-Purpose AI-native RAN
Hasan Farooq, Julien Forgeat, Shruti Bothe +2
The realization of data-driven AI-native architecture envisioned for 6G and beyond networks can eventually lead to multiple machine learning (ML) workloads distributed at the netwo…
Towards Addressing Training Data Scarcity Challenge in Emerging Radio Access Networks: A Survey and Framework
Haneya Naeem Qureshi, Usama Masood, Marvin Manalastas +8
The future of cellular networks is contingent on artificial intelligence (AI) based automation, particularly for radio access network (RAN) operation, optimization, and troubleshoo…
Coordinated Reinforcement Learning for Optimizing Mobile Networks
Maxime Bouton, Hasan Farooq, Julien Forgeat +3
Mobile networks are composed of many base stations and for each of them many parameters must be optimized to provide good services. Automatically and dynamically optimizing all the…
Neuromorphic AI Empowered Root Cause Analysis of Faults in Emerging Networks
Shruti Bothe, Usama Masood, Hasan Farooq +1
Mobile cellular network operators spend nearly a quarter of their revenue on network maintenance and management. A significant portion of that budget is spent on resolving faults d…