From 5G to 6G—challenges, technologies, and applications
AI Salameh, M El Tarhuni - Future Internet, 2022 - mdpi.com
As the deployment of 5G mobile radio networks gains momentum across the globe, the
wireless research community is already planning the successor of 5G. In this paper, we …
wireless research community is already planning the successor of 5G. In this paper, we …
Machine learning in beyond 5G/6G networks—State-of-the-art and future trends
Artificial Intelligence (AI) and especially Machine Learning (ML) can play a very important
role in realizing and optimizing 6G network applications. In this paper, we present a brief …
role in realizing and optimizing 6G network applications. In this paper, we present a brief …
Overview of distributed machine learning techniques for 6G networks
The main goal of this paper is to survey the influential research of distributed learning
technologies playing a key role in the 6G world. Upcoming 6G technology is expected to …
technologies playing a key role in the 6G world. Upcoming 6G technology is expected to …
Service-aware resource orchestration in ultra-dense LEO satellite-terrestrial integrated 6G: A service function chain approach
With the rapid expansion of the scale of deployed low earth orbit (LEO) satellites, the ultra-
dense LEO satellite-terrestrial integrated network (LTIN) is envisioned as a promising …
dense LEO satellite-terrestrial integrated network (LTIN) is envisioned as a promising …
DRL-based computation rate maximization for wireless powered multi-AP edge computing
S Zhang, S Bao, K Chi, K Yu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In the ongoing 5G and upcoming 6G eras, the intelligent Internet of Things (IoT) network will
take increasingly important responsibility for industrial production, daily life and so on. The …
take increasingly important responsibility for industrial production, daily life and so on. The …
Space-aerial-ground-sea integrated networks: Resource optimization and challenges in 6G
Abstract Space–air–ground–sea integrated (SAGSI) networks are envisioned to connect
satellite, aerial, ground, and sea networks to provide connectivity everywhere and all the …
satellite, aerial, ground, and sea networks to provide connectivity everywhere and all the …
Joint power allocation and 3D deployment for UAV-BSs: A game theory based deep reinforcement learning approach
Ultra-dense unmanned aerial vehicle (UAV) plays an important role in the field of
communications due to its flexibility and low-cost feature. Ultra-dense unnamed aerial …
communications due to its flexibility and low-cost feature. Ultra-dense unnamed aerial …
Resource allocation for mobile metaverse with the Internet of Vehicles over 6G wireless communications: A deep reinforcement learning approach
Improving the interactivity and interconnectivity between people is one of the highlights of
the Metaverse. The Metaverse relies on a core approach, digital twinning, which is a means …
the Metaverse. The Metaverse relies on a core approach, digital twinning, which is a means …
Reinforcement learning-driven data-intensive workflow scheduling for volunteer edge-cloud
M Mounesan, M Lemus, H Yeddulapalli… - 2024 IEEE 8th …, 2024 - ieeexplore.ieee.org
In recent times, Volunteer Edge-Cloud (VEC) has gained traction as a cost-effective,
community computing paradigm to support data-intensive scientific workflows. However, due …
community computing paradigm to support data-intensive scientific workflows. However, due …
Computation offloading for tasks with bound constraints in multiaccess edge computing
Multiaccess edge computing (MEC) provides task offloading services to facilitate the
integration of idle resources with the network and bring cloud services closer to the end …
integration of idle resources with the network and bring cloud services closer to the end …