Hypergraph based resource-efficient collaborative reinforcement learning for B5G massive IoT
Beyond 5G (B5G) networks rapidly growing to connect billions of Internet of Things (IoT)
devices and the dense deployment of IoT devices leads the large-scale network conflict and …
devices and the dense deployment of IoT devices leads the large-scale network conflict and …
Zeroth-order asynchronous learning with bounded delays with a use-case in resource allocation in communication networks
Distributed optimization has experienced a significant surge in interest due to its wide-
ranging applications in distributed learning and adaptation. While various scenarios, such …
ranging applications in distributed learning and adaptation. While various scenarios, such …
Model-free decentralized training for deep learning based resource allocation in communication networks
P Behmandpoor, P Patrinos… - 2023 31st European …, 2023 - ieeexplore.ieee.org
Decentralized deep learning (DL) based resource allocation (RA) in communication
networks guarantees scalability and higher communication bandwidth efficiency compared …
networks guarantees scalability and higher communication bandwidth efficiency compared …
An Efficient 6G Federated Learning-enabled Energy-Efficient Scheme for UAV Deployment
K Raja, K Kottursamy, V Ravichandran… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAVs) are widely used for commercial transportation and data
collection in many applications. Recently, UAVs have been used as flying relays to support …
collection in many applications. Recently, UAVs have been used as flying relays to support …
A Deep Learning Based Resource Allocator for Communication Systems with Dynamic User Utility Demands
Deep learning (DL) based resource allocation (RA) has recently gained a lot of attention due
to its performance efficiency. However, most of the related studies assume an ideal case …
to its performance efficiency. However, most of the related studies assume an ideal case …
[PDF][PDF] OPTIMISATION IN NOMA WIRELESS COMMUNICATION NETWORKS
X Xie - 2023 - pure.manchester.ac.uk
With the 5-th generation (5G) of wireless communication has been successfully
commercialised, people start to look forward to the next generation, the 6-th generation (6G) …
commercialised, people start to look forward to the next generation, the 6-th generation (6G) …
Federated Learning Under a Digital Communication Model
P Behmandpoor, P Patrinos… - IEEE Open Journal of …, 2023 - ieeexplore.ieee.org
Federated learning (FL) has received significant attention recently as a topic in distributed
learning. In FL, a global model is cooperatively trained by edge devices, as agents, where …
learning. In FL, a global model is cooperatively trained by edge devices, as agents, where …
Communication-Efficient Federated Learning for UAV Networks with Knowledge Distillation and Transfer Learning
Federated learning (FL) in unmanned aerial ve-hicles (UAVs) networks demands
considerable communication resources to transfer model data between the central server …
considerable communication resources to transfer model data between the central server …
无蜂窝大规模MIMO 网络下基于联邦学习的用户接入策略及能耗优化
姚媛媛， 刘忆秋， 黄赛， 潘春雨， 李学华， 袁昕 - 通信学报, 2023 - infocomm-journal.com
针对无蜂窝大规模多输入多输出(CF-mMIMO) 网络中用户如何选择接入点的问题,
提出了一种基于信道排序的较差用户优先接入策略. 首先, 用户进行信道感知后对其信道质量和 …
提出了一种基于信道排序的较差用户优先接入策略. 首先, 用户进行信道感知后对其信道质量和 …
Resource Allocation through Auction-based Incentive Scheme for Federated Learning in Mobile Edge Computing
J Asif - thesis.unipd.it
Abstract Mobile Edge Computing (MEC) combinedly with Federated Learning is con-sidered
as most capable solutions to AI-driven services. Most of the studies focus on Federated …
as most capable solutions to AI-driven services. Most of the studies focus on Federated …