4 citations · 11 across the 8 of their papers we have counts for
6 papers · 1 filter
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…
RLOps: Development Life-cycle of Reinforcement Learning Aided Open RAN
Peizheng Li, Jonathan Thomas, Xiaoyang Wang +8
Radio access network (RAN) technologies continue to evolve, with Open RAN gaining the most recent momentum. In the O-RAN specifications, the RAN intelligent controllers (RICs) are…
Self-play Learning Strategies for Resource Assignment in Open-RAN Networks
Xiaoyang Wang, Jonathan D Thomas, Robert J Piechocki +3
Open Radio Access Network (ORAN) is being developed with an aim to democratise access and lower the cost of future mobile data networks, supporting network services with various Qo…