Federated learning in edge computing: a systematic survey
Edge Computing (EC) is a new architecture that extends Cloud Computing (CC) services
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …
Evolution of NOMA toward next generation multiple access (NGMA) for 6G
Due to the explosive growth in the number of wireless devices and diverse wireless
services, such as virtual/augmented reality and Internet-of-Everything, next generation …
services, such as virtual/augmented reality and Internet-of-Everything, next generation …
Reinforcement learning for intelligent healthcare systems: A comprehensive survey
The rapid increase in the percentage of chronic disease patients along with the recent
pandemic pose immediate threats on healthcare expenditure and elevate causes of death …
pandemic pose immediate threats on healthcare expenditure and elevate causes of death …
Rlops: Development life-cycle of reinforcement learning aided open ran
Radio access network (RAN) technologies continue to evolve, with Open RAN gaining the
most recent momentum. In the O-RAN specifications, the RAN intelligent controllers (RICs) …
most recent momentum. In the O-RAN specifications, the RAN intelligent controllers (RICs) …
Reinforcement Learning for Intelligent Healthcare Systems: A Review of Challenges, Applications, and Open Research Issues
The rise of chronic disease patients and the pandemic pose immediate threats to healthcare
expenditure and mortality rates. This calls for transforming healthcare systems away from …
expenditure and mortality rates. This calls for transforming healthcare systems away from …
Hierarchical multi-agent DRL-based framework for joint multi-RAT assignment and dynamic resource allocation in next-generation hetnets
This article considers the problem of cost-aware downlink sum-rate maximization via joint
optimal radio access technologies (RATs) assignment and power allocation in next …
optimal radio access technologies (RATs) assignment and power allocation in next …
Distributed DRL-based downlink power allocation for hybrid RF/VLC networks
Hybrid radio frequency (RF) and visible light communication (VLC) networks can provide
high throughput and energy efficiency with VLC access points (APs) while ensuring …
high throughput and energy efficiency with VLC access points (APs) while ensuring …
[HTML][HTML] Energy-efficient joint resource allocation in 5G HetNet using multi-agent parameterized deep reinforcement learning
Small cells are a promising technique to improve the capacity and throughput of future
wireless networks. However, user association and power allocation in heterogeneous …
wireless networks. However, user association and power allocation in heterogeneous …
Graph-based resource allocation for integrated space and terrestrial communications
Resource allocation (RA) has always had a prominent place in wireless communications
research due to its significance for network throughput maximization, and its inherent …
research due to its significance for network throughput maximization, and its inherent …
Spectral efficiency improvement in downlink fog radio access network with deep reinforcement learning-enabled power control
NB Mohamed, MZ Hassan… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Fog radio access network (F-RAN) is a promising architecture that leverages edge
computing and caching to improve devices' latency and quality of service. However …
computing and caching to improve devices' latency and quality of service. However …