8 citations · 8 across the 10 of their papers we have counts for
10 papers
EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN
Lingyan Bao, Jemin Lee, Tony Q. S. Quek
Despite recent advances in applying artificial intelligence (AI) techniques to radio access network (RAN), critical challenges remain: traditional machine learning (ML) algorithms…
LLM-Based Net Analyzer rApp for Explainable and Safe Automation in O-RAN Non-RT RIC
Tuan V. Ngo, Mao V. Ngo, Binbin Chen +3
Modern 5G/6G radio access networks are increasingly programmable through O-RAN, yet their operational complexity has grown with disaggregation, open interfaces, and fine-grained co…
Adaptive AI Model Partitioning over 5G Networks
Tam Thanh Nguyen, Tuan Van Ngo, Long Thanh Le +4
Mobile devices increasingly rely on deep neural networks (DNNs) for complex inference tasks, but running entire models locally drains the device battery quickly. Offloading computa…
INA-Infra: An Open and Extensible Infrastructure for Intent-driven Network Automation Research
Nguyen-Bao-Long Tran, Tuan V. Ngo, Mao V. Ngo +3
As telecommunications systems progress to support diverse use cases with heterogeneous and dynamic Quality of Service (QoS) requirements, it becomes an increasingly complex task to…
Consistent and Repeatable Testing of mMIMO O-RU across labs: A Japan-Singapore Experience
Thanh-Tam Nguyen, Mao V. Ngo, Binbin Chen +6
Open Radio Access Networks (RAN) aim to bring a paradigm shift to telecommunications industry, by enabling an open, intelligent, virtualized, and multi-vendor interoperable RAN eco…
Consistent and Repeatable Testing of O-RAN Distributed Unit (O-DU) across Continents
Tuan V. Ngo, Mao V. Ngo, Binbin Chen +6
Open Radio Access Networks (O-RAN) are expected to revolutionize the telecommunications industry with benefits like cost reduction, vendor diversity, and improved network performan…