11 citations · 11 across the 4 of their papers we have counts for
5 papers
Meta-Learning-Based Handover Management in NextG O-RAN
Michail Kalntis, George Iosifidis, José Suárez-Varela +2
While traditional handovers (THOs) have served as a backbone for mobile connectivity, they increasingly suffer from failures and delays, especially in dense deployments and high-fr…
Radio Propagation Modelling: To Differentiate or To Deep Learn, That Is The Question
Stefanos Bakirtzis, Paul Almasan, José Suárez-Varela +5
Differentiable ray tracing has recently challenged the status quo in radio propagation modelling and digital twinning. Promising unprecedented speed and the ability to learn from r…
CHOMET: Conditional Handovers via Meta-Learning
Michail Kalntis, Fernando A. Kuipers, George Iosifidis
Handovers (HOs) are the cornerstone of modern cellular networks for enabling seamless connectivity to a vast and diverse number of mobile users. However, as mobile networks become…
Smooth Handovers via Smoothed Online Learning
Michail Kalntis, Andra Lutu, Jesús Omaña Iglesias +2
With users demanding seamless connectivity, handovers (HOs) have become a fundamental element of cellular networks. However, optimizing HOs is a challenging problem, further exacer…
Through the Telco Lens: A Countrywide Empirical Study of Cellular Handovers
Michail Kalntis, José Suárez-Varela, Jesús Omaña Iglesias +4
Cellular networks rely on handovers (HOs) as a fundamental element to enable seamless connectivity for mobile users. A comprehensive analysis of HOs can be achieved through data fr…