42 citations · 48 across the 7 of their papers we have counts for
7 papers
HexRAN: A Programmable Approach to Open RAN Base Station System Design
Ahan Kak, Van-Quan Pham, Huu-Trung Thieu +1
In recent years, the radio access network (RAN) domain has witnessed a sea change with increasing levels of virtualization and softwarization driven by emerging paradigms such as t…
RoNet: Toward Robust Neural Assisted Mobile Network Configuration
Yuru Zhang, Yongjie Xue, Qiang Liu +2
Automating configuration is the key path to achieving zero-touch network management in ever-complicating mobile networks. Deep learning techniques show great potential to automatic…
Atlas: Automate Online Service Configuration in Network Slicing
Qiang Liu, Nakjung Choi, Tao Han
Network slicing achieves cost-efficient slice customization to support heterogeneous applications and services. Configuring cross-domain resources to end-to-end slices based on ser…
Deep Reinforcement Learning for End-to-End Network Slicing: Challenges and Solutions
Qiang Liu, Nakjung Choi, Tao Han
5G and beyond is expected to enable various emerging use cases with diverse performance requirements from vertical industries. To serve these use cases cost-effectively, network sl…
Regenerative Particle Thompson Sampling
Zeyu Zhou, Bruce Hajek, Nakjung Choi +1
This paper proposes regenerative particle Thompson sampling (RPTS), a flexible variation of Thompson sampling. Thompson sampling itself is a Bayesian heuristic for solving stochast…
OnSlicing: Online End-to-End Network Slicing with Reinforcement Learning
Qiang Liu, Nakjung Choi, Tao Han
Network slicing allows mobile network operators to virtualize infrastructures and provide customized slices for supporting various use cases with heterogeneous requirements. Online…
Constraint-Aware Deep Reinforcement Learning for End-to-End Resource Orchestration in Mobile Networks
Qiang Liu, Nakjung Choi, Tao Han
Network slicing is a promising technology that allows mobile network operators to efficiently serve various emerging use cases in 5G. It is challenging to optimize the utilization…