AI models for green communications towards 6G
Green communications have always been a target for the information industry to alleviate
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …
Actor-critic-based learning for zero-touch joint resource and energy control in network slicing
F Rezazadeh, H Chergui, L Christofi… - ICC 2021-IEEE …, 2021 - ieeexplore.ieee.org
To harness the full potential of beyond 5G (B5G) communication systems, zero-touch
network slicing (NS) is viewed as a promising fully-automated management and …
network slicing (NS) is viewed as a promising fully-automated management and …
Deep reinforcement learning-assisted energy harvesting wireless networks
J Ye, H Gharavi - IEEE transactions on green communications …, 2020 - ieeexplore.ieee.org
Heterogeneous ultra-dense networking (HUDN) with energy harvesting technology is a
promising approach to deal with the ever-growing traffic that can severely impact the power …
promising approach to deal with the ever-growing traffic that can severely impact the power …
AI based service management for 6G green communications
Green communications have always been a target for the information industry to alleviate
energy overhead and reduce fossil fuel usage. In current 5G and future 6G era, there is no …
energy overhead and reduce fossil fuel usage. In current 5G and future 6G era, there is no …
Throughput maximization by deep reinforcement learning with energy cooperation for renewable ultradense IoT networks
Y Li, X Zhao, H Liang - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
Ultradense network (UDN) is considered as one of the key technologies for the explosive
growth of mobile traffic demand on the Internet of Things (IoT). It enhances network capacity …
growth of mobile traffic demand on the Internet of Things (IoT). It enhances network capacity …
[HTML][HTML] Power Allocation and energy cooperation for UAV-enabled mmwave networks: A multi-agent deep reinforcement learning approach
MC Domingo - Sensors, 2021 - mdpi.com
Unmanned Aerial Vehicle (UAV)-assisted cellular networks over the millimeter-wave
(mmWave) frequency band can meet the requirements of a high data rate and flexible …
(mmWave) frequency band can meet the requirements of a high data rate and flexible …
[PDF][PDF] 基于多智能体柔性演员-评论家学习的服务功能链部署算法
唐伦， 李师锐， 杜雨聪， 陈前斌 - 电子与信息学报, 2022 - jeit.ac.cn
针对网络功能虚拟化(NFV) 架构下业务请求动态变化引起的服务功能链(SFC) 部署优化问题,
该文提出一种基于多智能体柔性演员-评论家(MASAC) 学习的SFC 部署优化算法. 首先 …
该文提出一种基于多智能体柔性演员-评论家(MASAC) 学习的SFC 部署优化算法. 首先 …
[PDF][PDF] 基于深度确定性策略梯度的虚拟网络功能迁移优化算法
唐伦， 贺兰钦， 谭颀， 陈前斌 - 电子与信息学报, 2021 - jeit.ac.cn
针对NFV/SDN 架构下, 服务功能链(SFC) 的资源需求动态变化引起的虚拟网络功能(VNF)
迁移优化问题, 该文提出一种基于深度强化学习的VNF 迁移优化算法. 首先, 在底层CPU …
迁移优化问题, 该文提出一种基于深度强化学习的VNF 迁移优化算法. 首先, 在底层CPU …
Deployment algorithm of service function chain based on multi-agent soft actor-critic learning
L TANG, S LI, Y DU, Q CHEN - 电子与信息学报, 2023 - jeit.ac.cn
Considering the problem of Service Function Chain (SFC) deployment optimization caused
by the dynamic change of service requests under the Network Function Virtualization (NFV) …
by the dynamic change of service requests under the Network Function Virtualization (NFV) …
[PDF][PDF] 基于改进深度强化学习的虚拟网络功能部署优化算法
唐伦， 贺兰钦， 连沁怡， 谭颀 - 电子与信息学报, 2021 - jeit.ac.cn
针对网络功能虚拟化/软件定义网络(NFV/SDN) 架构下, 网络服务请求动态到达引起的服务功能
链(SFC) 部署优化问题, 该文提出一种基于改进深度强化学习的虚拟网络功能(VNF) …
链(SFC) 部署优化问题, 该文提出一种基于改进深度强化学习的虚拟网络功能(VNF) …