A reinforcement learning agent for mixed-numerology interference-aware slice spectrum allocation with non-deterministic and deterministic traffic
M Zambianco, G Verticale - Computer Communications, 2022 - Elsevier
Abstract 5G RAN slicing is an essential tool to support the simultaneous coexistence of
enhanced mobile broadband (eMBB) and ultra-reliable low-latency communications …
enhanced mobile broadband (eMBB) and ultra-reliable low-latency communications …
Mixed-numerology interference-aware spectrum allocation for eMBB and URLLC network slices
M Zambianco, G Verticale - 2021 19th Mediterranean …, 2021 - ieeexplore.ieee.org
5G RAN slicing makes it possible to simultaneously support enhanced mobile broadband
(eMBB) and ultra-reliable low-latency communications (URLLC) services characterized by …
(eMBB) and ultra-reliable low-latency communications (URLLC) services characterized by …
Spectrum allocation for network slices with inter-numerology interference using deep reinforcement learning
M Zambianco, G Verticale - 2020 IEEE 31st Annual …, 2020 - ieeexplore.ieee.org
Network slicing and mixed-numerology schemes are essential technologies to efficiently
accommodate different services in 5G radio access networks (RAN). To fully take advantage …
accommodate different services in 5G radio access networks (RAN). To fully take advantage …
Intelligent multi-branch allocation of spectrum slices for inter-numerology interference minimization
M Zambianco, G Verticale - Computer Networks, 2021 - Elsevier
Network slicing and mixed-numerology access schemes cover a central role to enable the
flexible multi-service connectivity that characterizes 5G radio access networks (RAN) …
flexible multi-service connectivity that characterizes 5G radio access networks (RAN) …
Deep Reinforcement Learning for Optimization of RAN Slicing Relying on Control-and User-Plane Separation
The rapid development of radio access network (RAN) slicing and control-and user-plane
separation (CUPS) has created a new paradigm for future networks, namely, CUPS-based …
separation (CUPS) has created a new paradigm for future networks, namely, CUPS-based …
Resource slicing for eMBB and URLLC services in radio access network using hierarchical deep learning
M Setayesh, S Bahrami… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Network slicing is a promising technique for wireless service providers to support enhanced
mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC) services …
mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC) services …
RAN resource slicing in 5G using multi-agent correlated Q-learning
5G is regarded as a revolutionary mobile network, which is expected to satisfy a vast number
of novel services, ranging from remote health care to smart cities. However, heterogeneous …
of novel services, ranging from remote health care to smart cities. However, heterogeneous …
SAMUS: Slice-aware machine learning-based ultra-reliable scheduling
C Bektas, D Overbeck, C Wietfeld - ICC 2021-IEEE International …, 2021 - ieeexplore.ieee.org
Multiple service types such as Ultra-Reliable Low Latency Communication (uRLLC) and
Enhanced Mobile Broadband (eMBB) are envisioned to be incorporated into the next …
Enhanced Mobile Broadband (eMBB) are envisioned to be incorporated into the next …
Hierarchical deep reinforcement learning based dynamic RAN slicing for 5G V2X
Radio Access Network (RAN) slicing is getting increasing attention as a resource allocation
technique for satisfying diverse Quality-of-Service (QoS) requirements in 5G vehicular …
technique for satisfying diverse Quality-of-Service (QoS) requirements in 5G vehicular …
Coordinated slicing and admission control using multi-agent deep reinforcement learning
5G Cloud Radio Access Networks (C-RANs) facilitate new forms of flexible resource
management as dynamic RAN function splitting and placement. Virtualized RAN functions …
management as dynamic RAN function splitting and placement. Virtualized RAN functions …