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 …
On softwarization of intelligence in 6G networks for ultra-fast optimal policy selection: Challenges and opportunities
The emerging Sixth Generation (6G) communication networks promising 100 to 1000 Gb/s
rates and ultra-low latency (1 millisecond) are anticipated to have native, embedded Artificial …
rates and ultra-low latency (1 millisecond) are anticipated to have native, embedded Artificial …
Intelligent content caching strategy in autonomous driving toward 6G
L Zhao, H Li, N Lin, M Lin, C Fan… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The rapid development of 6G can help to bring autonomous driving closed to the reality.
Drivers and passengers will have more time for work and leisure spending in the vehicles …
Drivers and passengers will have more time for work and leisure spending in the vehicles …
Low-latency federated learning over wireless channels with differential privacy
In federated learning (FL), model training is distributed over clients and local models are
aggregated by a central server. The performance of uploaded models in such situations can …
aggregated by a central server. The performance of uploaded models in such situations can …
Deep learning for wireless coded caching with unknown and time-variant content popularity
Z Zhang, M Tao - IEEE Transactions on Wireless …, 2020 - ieeexplore.ieee.org
Coded caching is effective in leveraging the accumulated storage size in wireless networks
by distributing different coded segments of each file in multiple cache nodes. This paper …
by distributing different coded segments of each file in multiple cache nodes. This paper …
[BOOK][B] Mobile edge computing
Y Zhang - 2022 - library.oapen.org
This is an open access book. It offers comprehensive, self-contained knowledge on Mobile
Edge Computing (MEC), which is a very promising technology for achieving intelligence in …
Edge Computing (MEC), which is a very promising technology for achieving intelligence in …
A survey on reinforcement learning-aided caching in heterogeneous mobile edge networks
Mobile networks experience a tremendous increase in data volume and user density due to
the massive number of coexisting users and devices. An efficient technique to alleviate this …
the massive number of coexisting users and devices. An efficient technique to alleviate this …
Deep reinforcement learning for reactive content caching with predicted content popularity in three-tier wireless networks
Y Liu, J Jia, J Cai, T Huang - IEEE Transactions on Network and …, 2022 - ieeexplore.ieee.org
With the explosive growth of micro-video applications, the mobile traffic generated by
retrieving a few user-generated micro-videos has brought a massive burden to backhaul …
retrieving a few user-generated micro-videos has brought a massive burden to backhaul …
Recommendation-driven multi-cell cooperative caching: A multi-agent reinforcement learning approach
In 5G small cell networks, edge caching is a key technique to alleviate the backhaul burden
by caching user desired contents at network edges such as small base stations (SBSs) …
by caching user desired contents at network edges such as small base stations (SBSs) …
Privacy-preserving communication-efficient federated multi-armed bandits
Communication bottleneck and data privacy are two critical concerns in federated multi-
armed bandit (MAB) problems, such as situations in decision-making and recommendations …
armed bandit (MAB) problems, such as situations in decision-making and recommendations …