Advanced deep learning models for 6g: Overview, opportunities and challenges
The advent of the sixth generation of mobile communications (6G) ushers in an era of
heightened demand for advanced network intelligence to tackle the challenges of an …
heightened demand for advanced network intelligence to tackle the challenges of an …
Toward resilient network slicing for satellite–terrestrial edge computing IoT
Satellite–terrestrial edge computing networks (STECNs) emerged as a global solution to
support multiple Internet of Things (IoT) applications in 6G networks. The enabling …
support multiple Internet of Things (IoT) applications in 6G networks. The enabling …
Joint beam direction control and radio resource allocation in dynamic multi-beam leo satellite networks
Multi-beam low earth orbit (LEO) satellites are emerging as key components in beyond 5G
and 6G to provide global coverage and high data rate. To fully unleash the potential of LEO …
and 6G to provide global coverage and high data rate. To fully unleash the potential of LEO …
Interference Management in Space-Air-Ground Integrated Networks with Fully Distributed Rate-Splitting Multiple Access
Despite the allure of ubiquitous, high-speed, and low-latency connectivity offered by Space-
Air-Ground Integrated Networks (SAGINs), the co-existence of Low Earth Orbit (LEO) …
Air-Ground Integrated Networks (SAGINs), the co-existence of Low Earth Orbit (LEO) …
Rate-splitting multiple access-based satellite–vehicular communication system: A noncooperative game theoretical approach
Rate-Splitting Multiple Access (RSMA) has recently found favor in high-mobility scenarios
due to the benefits of relaxing the accuracy of Channel State Information at the Transmitter …
due to the benefits of relaxing the accuracy of Channel State Information at the Transmitter …
Multi-objective optimization for bandwidth-limited federated learning in wireless edge systems
This paper studies a bandwidth-limited federated learning (FL) system where the access
point is a central server for aggregation and the energy-constrained user equipments (UEs) …
point is a central server for aggregation and the energy-constrained user equipments (UEs) …
Decomposition and Meta-DRL based Multi-Objective Optimization for Asynchronous Federated Learning in 6G-Satellite Systems
Wireless-based federated learning (FL), as an emerging distributed learning approach, has
been widely studied for 6G systems. When the paradigm shifts from terrestrial to non …
been widely studied for 6G systems. When the paradigm shifts from terrestrial to non …
Transformer-empowered Predictive Beamforming for Rate-splitting Multiple Access in Non-Terrestrial Networks
Existing Rate-Splitting Multiple Access (RSMA) techniques offer a promise for Non-
Terrestrial Networks (NTNs) by managing interference and ensuring reliable data …
Terrestrial Networks (NTNs) by managing interference and ensuring reliable data …
Deep recurrent reinforcement learning for partially observable user association in a vertical heterogenous network
H Khoshkbari, G Kaddoum - IEEE Communications Letters, 2023 - ieeexplore.ieee.org
To ensure ubiquitous connectivity and meet increasing users' demands in next-generation
wireless networks, we investigate user association in a three-layer network consisting of a …
wireless networks, we investigate user association in a three-layer network consisting of a …
Dynamic Scheduling Scheme with Task Laxity for Data Relay Satellite Networks
With the increase of spacecrafts, data relay satellite network (DRSN) plays an essential role
in the space task transmission and processing through broad coverage and efficient …
in the space task transmission and processing through broad coverage and efficient …