Resource allocation using Gradient boosting aided deep Q-Network for IoT in C-RANs
In this paper, we investigate dynamic resource allocation (DRA) problems for Internet of
Things (IoT) in real-time cloud radio access networks (C-RANs), by combining gradient …
Things (IoT) in real-time cloud radio access networks (C-RANs), by combining gradient …
Power consumption optimization using gradient boosting aided deep Q-network in C-RANs
Cloud Radio Access Networks (C-RANs) have the potential to enable growing data traffic in
5G networks. However, with the complex states, resource allocation in C-RANs is time …
5G networks. However, with the complex states, resource allocation in C-RANs is time …
Deep reinforcement learning based dynamic resource allocation in cloud radio access networks
Cloud radio access network (C-RAN) is a promising architecture to fulfill the ever-increasing
resource demand in telecommunication networks. In C-RAN, a base station is decoupled …
resource demand in telecommunication networks. In C-RAN, a base station is decoupled …
Double deep Q-network for power allocation in cloud radio access network
Cloud radio access network (CRAN) facilitates resource allocation (RA) by isolating remote
radio heads (RRHs) from baseband units (BBUs). Traditional RA algorithms save energy by …
radio heads (RRHs) from baseband units (BBUs). Traditional RA algorithms save energy by …
Double deep Q-network-based energy-efficient resource allocation in cloud radio access network
Cloud radio access network (CRAN) has been shown as an effective means to boost
network performance. Such gain stems from the intelligent management of remote radio …
network performance. Such gain stems from the intelligent management of remote radio …
Energy-and spectral-efficient optimization in cloud ran based on dueling double deep Q-network
Cloud radio access network (CRAN) has gained considerable attention for the upcoming
cellular network that can offload the mobile data traffic and reduce energy consumption by …
cellular network that can offload the mobile data traffic and reduce energy consumption by …
DRL based Energy-Efficient Radio Resource Allocation Algorithm in Internet of Robotic Things
Communications among user equipment (UE) play a pivotal role in the coordination and
information sharing in order to accomplish the predefined collaborative tasks of UE via the …
information sharing in order to accomplish the predefined collaborative tasks of UE via the …
Computation offloading and resource allocation for MEC in C-RAN: A deep reinforcement learning approach
X Jin, J Zhang, X Sun, P Zhang… - 2019 IEEE 19th …, 2019 - ieeexplore.ieee.org
Mobile edge computing (MEC) technology has become a promising example for cloud radio
access networks (CRAN) to provide close-range services, thereby reducing service delays …
access networks (CRAN) to provide close-range services, thereby reducing service delays …
ReCARL: resource allocation in cloud RANs with deep reinforcement learning
Cloud radio access networks (CRANs) have become a key enabling technique for the next
generation wireless communications. Resource allocation in CRANs still needs to be further …
generation wireless communications. Resource allocation in CRANs still needs to be further …
Deep reinforcement learning for resource allocation in 5G communications
The rapid growth of data traffic has pushed the mobile telecommunication industry towards
the adoption of fifth generation (5G) communications. Cloud radio access network (CRAN) …
the adoption of fifth generation (5G) communications. Cloud radio access network (CRAN) …