Deep reinforcement learning-based joint user association and cu–du placement in o-ran
Open Radio Access Networks (O-RAN) architecture is based on disaggregation,
virtualization, openness, and intelligence. These features allow the RAN network functions …
virtualization, openness, and intelligence. These features allow the RAN network functions …
Energy-efficient virtual base station formation in optical-access-enabled cloud-RAN
In recent years, the increasing traffic demand in radio access networks (RANs) has led to
considerable growth in the number of base stations (BSs), posing a serious scalability issue …
considerable growth in the number of base stations (BSs), posing a serious scalability issue …
Building autonomic elastic optical networks with deep reinforcement learning
Conventional schemes for service provisioning in next-generation elastic optical networks
(EONs) rely on rule-based policies that suffer from scalability issues and can lead to poor …
(EONs) rely on rule-based policies that suffer from scalability issues and can lead to poor …
Assessment of a latency-aware routing and spectrum assignment mechanism based on deep reinforcement learning
C Hernández-Chulde, R Casellas… - 2021 European …, 2021 - ieeexplore.ieee.org
We present a solution based on deep reinforcement learning (DRL) that jointly addresses
spectrum allocation and latency constraint in EONs. The results show that using a simple …
spectrum allocation and latency constraint in EONs. The results show that using a simple …
A min-max fair resource allocation framework for optical x-haul and DU/CU in multi-tenant O-RANs
The recently proposed open-radio access network (O-RAN) architecture embraces
cloudification and network function virtualization techniques to perform the base-band …
cloudification and network function virtualization techniques to perform the base-band …
Resource allocation with edge-cloud collaborative traffic prediction in integrated radio and optical networks
By integrating communications in different domains, integrated radio and optical networks
can serve a wider range of applications and services. Integrated radio and optical network …
can serve a wider range of applications and services. Integrated radio and optical network …
Joint allocation of radio and fronthaul resources in multi-wavelength-enabled C-RAN based on reinforcement learning
A Mohammed Mikaeil, W Hu, L Li - Journal of Lightwave Technology, 2019 - opg.optica.org
Cloud radio access network (C-RAN) is a key technology for the new-generation mobile
network (5G). Multi-wavelength passive optical networks (PONs) such as wavelength …
network (5G). Multi-wavelength passive optical networks (PONs) such as wavelength …
Distributed deep reinforcement learning assisted resource allocation algorithm for space-air-ground integrated networks
To realize the Interconnection of Everything (IoE) in the 6G vision, the space-based, air-
based, and ground-based networks have shown a trend of integration. Compared with the …
based, and ground-based networks have shown a trend of integration. Compared with the …
Resource allocation for joint energy and spectral efficiency in cloud radio access network based on deep reinforcement learning
The rapid increase of user data traffic demand has promoted the telecommunication sector
toward adopting a new generation, that is, fifth‐generation (5G). Cloud radio access network …
toward adopting a new generation, that is, fifth‐generation (5G). Cloud radio access network …
An RL approach for radio resource management in the O-RAN architecture
F Mungari - 2021 18th Annual IEEE International Conference …, 2021 - ieeexplore.ieee.org
The new generation mobile network requires flexibility and efficiency in radio link
management (RRM), in order to support a wide range of services and applications with …
management (RRM), in order to support a wide range of services and applications with …