3 citations · 7 across the 5 of their papers we have counts for
5 papers
Toward Fully Autonomous 6G Networks: AI-driven Operational Efficiency and Optimization
David Reiss, Oriol Sallent, Miguel Catalan-Cid +1
Mobile networks evolution is characterized by a substantial increase in system complexity, driven by the need to accommodate a growing number of heterogeneous services on top of th…
Policy-Guided ML for Energy Savings: Cell On/Off Switching under Operator QoS Constraints in Real 5G Networks
D. Reiss, M. Catalan-Cid, D. Camps-Mur +1
Energy efficiency is a critical concern in the deployment and operation of 5G networks, particularly due to the low utilization of 4G and 5G carriers during off-peak hours. While c…
Quantifying the Energy-Saving and QoS Trade-Off in Traffic Offloading for Real 4G/5G Scenarios
D. Reiss, M. Catalan-Cid, D. Camps-Mur +1
Despite the potential for higher energy efficiency in 5G networks, current 5G Non-Standalone (NSA) deployments often operate suboptimally due to low utilization of 4G and 5G carrie…
A Practical AI-Driven Strategy for Cell On/Off Switching under Adaptable QoS Constraints
David Reiss, Miguel Catalan-Cid, Daniel Camps +1
The rapid expansion of 5G networks has intensified concerns over their sustainability, as denser Radio Access Network (RAN) deployments have increased overall power consumption. Al…
Demo: BeGREEN Intelligence Plane for AI-driven Energy Efficient O-RAN management
M. Catalan-Cid, D. Reiss, G. Castellanos +1
Cellular networks management is being enhanced by O-RAN architecture and AI/ML solutions, enabling automated intelligent control loops for RAN optimization across various use cases…