4 citations · 11 across the 8 of their papers we have counts for
9 papers
Role-Based Agentic AI for Intent-Driven Network and Service Orchestration
Juan Parra-Ullauri, Talha Ahmed Khan, Daniel McHugh +4
Telecommunication networks are increasingly complex due to heterogeneous technologies, diverse service requirements, and growing demands for resource efficiency and business agilit…
Federated Meta-Learning for Traffic Steering in O-RAN
Hakan Erdol, Xiaoyang Wang, Peizheng Li +7
The vision of 5G lies in providing high data rates, low latency (for the aim of near-real-time applications), significantly increased base station capacity, and near-perfect qualit…
Transmit Power Control for Indoor Small Cells: A Method Based on Federated Reinforcement Learning
Peizheng Li, Hakan Erdol, Keith Briggs +7
Setting the transmit power setting of 5G cells has been a long-term topic of discussion, as optimized power settings can help reduce interference and improve the quality of service…
Variational Autoencoder Assisted Neural Network Likelihood RSRP Prediction Model
Peizheng Li, Xiaoyang Wang, Robert Piechocki +3
Measuring customer experience on mobile data is of utmost importance for global mobile operators. The reference signal received power (RSRP) is one of the important indicators for…
Sim2real for Reinforcement Learning Driven Next Generation Networks
Peizheng Li, Jonathan Thomas, Xiaoyang Wang +8
The next generation of networks will actively embrace artificial intelligence (AI) and machine learning (ML) technologies for automation networks and optimal network operation stra…
Smart Interference Management xApp using Deep Reinforcement Learning
Mahdi Eskandari, Shipra Kapoor, Keith Briggs +3
Interference continues to be a key limiting factor in cellular radio access network (RAN) deployments. Effective, data-driven, self-adapting radio resource management (RRM) solutio…