Machine Learning Empowered Emerging Wireless Networks in 6G: Recent Advancements, Challenges & Future Trends
The upcoming 6G networks are sixth-sense next-generation communication networks with
an ever-increasing demand for enhanced end-to-end (E2E) connectivity towards a …
an ever-increasing demand for enhanced end-to-end (E2E) connectivity towards a …
Federated split learning for sequential data in satellite–terrestrial integrated networks
W Jiang, H Han, Y Zhang, J Mu - Information Fusion, 2024 - Elsevier
Satellite–terrestrial integrated networks (STINs) have been proposed for B5G/6G mobile
communication, and the increase in the computation and communication capacities of …
communication, and the increase in the computation and communication capacities of …
Resource allocation and offloading strategy for UAV-assisted LEO satellite edge computing
In emergency situations, such as earthquakes, landslides and other natural disasters, the
terrestrial communications infrastructure is severely disrupted and unable to provide …
terrestrial communications infrastructure is severely disrupted and unable to provide …
Stochastic computation offloading for LEO satellite edge computing networks: A learning-based approach
The deployment of mobile edge computing services in LEO satellite networks achieves
seamless coverage of computing services. However, the time-varying wireless channel …
seamless coverage of computing services. However, the time-varying wireless channel …
Federated deep reinforcement learning for task offloading in digital twin edge networks
Digital twin edge networks provide a new paradigm that combines mobile edge computing
(MEC) and digital twins to improve network performance and reduce communication cost by …
(MEC) and digital twins to improve network performance and reduce communication cost by …
Comprehensive Survey on Reinforcement Learning-Based Task Offloading Techniques in Aerial Edge Computing
Aerial edge computing (AEC) has emerged as a pivotal platform offering low-latency
computation services, seamless deployability, rapid operationality, and high maneuverability …
computation services, seamless deployability, rapid operationality, and high maneuverability …
Task offloading and trajectory scheduling for UAV-enabled MEC networks: An MADRL algorithm with prioritized experience replay
As a new network architecture, the air-ground cooperative network is a support for future 6G
network to achieve ubiquitous connectivities. To effectively relieve the computational …
network to achieve ubiquitous connectivities. To effectively relieve the computational …
Online computation offloading for collaborative space/aerial-aided edge computing toward 6G system
Y Liu, L Jiang, Q Qi, K Xie, S Xie - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In 6G systems, space-air-ground integrated network (SAGIN), relying on space/aerial
communications to complement terrestrial networks, is developed to achieve worldwide …
communications to complement terrestrial networks, is developed to achieve worldwide …
FedTO: Mobile-aware task offloading in multi-base station collaborative MEC
With the proliferation of the Internet of Things (IoT), mobile edge computing (MEC) has great
potential to achieve low latency, high reliability, and low energy consumption. However, in …
potential to achieve low latency, high reliability, and low energy consumption. However, in …
Intelligent Self-Optimization for Task Offloading in LEO-MEC-Assisted Energy-Harvesting-UAV Systems
Given the notable surge in Internet of Things (IoT) devices, low Earth orbit (LEO) satellites
and unmanned aerial vehicles (UAVs) have emerged as promising networking components …
and unmanned aerial vehicles (UAVs) have emerged as promising networking components …