5G Multi-Slices Bi-Level Resource Allocation by Reinforcement Learning
As the centralized unit (CU)—distributed unit (DU) separation in the fifth generation mobile
network (5G), the multi-slice and multi-scenario, can be better applied in wireless …
network (5G), the multi-slice and multi-scenario, can be better applied in wireless …
Make smart decisions faster: Deciding D2D resource allocation via stackelberg game guided multi-agent deep reinforcement learning
Device-to-Device (D2D) communication enabling direct data transmission between two
mobile users has emerged as a vital component for 5G cellular networks to improve …
mobile users has emerged as a vital component for 5G cellular networks to improve …
Distributed Resource Allocation In 5g Networks With Multi-Agent Reinforcement Learning
In this paper, we propose using Multi-agent Reinforcement Learning (MARL) for distributed
resource allocation in 5G networks. We consider the case where the resource allocation is …
resource allocation in 5G networks. We consider the case where the resource allocation is …
Slice management in radio access network via deep reinforcement learning
In future 5G systems, it is envisioned that the physical resources of a single network will be
dynamically shared between the virtual end-to-end networks called “slices” and the network …
dynamically shared between the virtual end-to-end networks called “slices” and the network …
Deep Reinforcement Learning-based Resource Allocation for 5G Machine-type Communication in Active Distribution Networks with Time-varying Interference
Q Li, H Cheng, Y Yang, H Tang, J Wang, G Luo… - Mobile Networks and …, 2022 - Springer
Active distribution networks (ADNs) can solve the problem of grid compatibility and large-
scale, intermittent, renewable energy applications. As the core part of ADNs, advanced …
scale, intermittent, renewable energy applications. As the core part of ADNs, advanced …
Dynamic power allocation in cellular network based on multi-agent double deep reinforcement learning
Y Yang, F Li, X Zhang, Z Liu, KY Chan - Computer Networks, 2022 - Elsevier
With the massively growing wireless data traffic, the dense cellular network has become a
significant mode for the fifth generation (5G) network. To fully utilize the benefit of the cellular …
significant mode for the fifth generation (5G) network. To fully utilize the benefit of the cellular …
Multi-Agent Deep Reinforcement Learning for Resource Allocation in 5G and 6G Networks
Multi-Agent Deep Reinforcement Learning (MADRL) has been widely utilized in numerous
next-generation wireless network functions, such as resource allocation in both centralized …
next-generation wireless network functions, such as resource allocation in both centralized …
Deep reinforcement learning-based resource allocation for smart grid in RAN network slice
M Liu, Y Wang, S Meng, X Zhao, S Geng - Advances in Wireless …, 2021 - Springer
Driven by the construction of the Ubiquitous Electricity Internet of things, various services
have increasingly higher requirements for wireless communication indicators. The 5G …
have increasingly higher requirements for wireless communication indicators. The 5G …
Slice Admission Control in 5g Wireless Communication with Multi-Dimensional State Space and Distributed Action Space: A Sequential Twin Actor-Critic Approach
Network slicing represents a paradigm shift in the way resources are allocated for different
5G network functions through network function virtualization. This innovation aims to …
5G network functions through network function virtualization. This innovation aims to …
Equilibrated and fast resources allocation for massive and diversified MTC services using multiagent deep reinforcement learning
L Tang, Y Du, Q Chen, Q Liu, J Li… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Massive and diversified machine type communication (MTC) service is one of the
development trends of MTC in Internet of Things (IoT). Meanwhile, realizing network …
development trends of MTC in Internet of Things (IoT). Meanwhile, realizing network …