Machine learning at the edge: A data-driven architecture with applications to 5G cellular networks
The fifth generation of cellular networks (5G) will rely on edge cloud deployments to satisfy
the ultra-low latency demand of future applications. In this paper, we argue that such …
the ultra-low latency demand of future applications. In this paper, we argue that such …
Deep learning at the mobile edge: Opportunities for 5G networks
M McClellan, C Cervelló-Pastor, S Sallent - Applied Sciences, 2020 - mdpi.com
Mobile edge computing (MEC) within 5G networks brings the power of cloud computing,
storage, and analysis closer to the end user. The increased speeds and reduced delay …
storage, and analysis closer to the end user. The increased speeds and reduced delay …
Machine learning meets computation and communication control in evolving edge and cloud: Challenges and future perspective
Mobile Edge Computing (MEC) is considered an essential future service for the
implementation of 5G networks and the Internet of Things, as it is the best method of …
implementation of 5G networks and the Internet of Things, as it is the best method of …
Softcell: Scalable and flexible cellular core network architecture
Cellular core networks suffer from inflexible and expensive equipment, as well as from
complex control-plane protocols. To address these challenges, we present SoftCell, a …
complex control-plane protocols. To address these challenges, we present SoftCell, a …
Machine learning for 5G and beyond: From model-based to data-driven mobile wireless networks
T Wang, S Wang, ZH Zhou - China Communications, 2019 - ieeexplore.ieee.org
During the past few decades, mobile wireless communications have experienced four
generations of technological revolution, namely from 1G to 4G, and the deployment of the …
generations of technological revolution, namely from 1G to 4G, and the deployment of the …
Intelligence and learning in O-RAN for data-driven NextG cellular networks
Next generation (NextG) cellular networks will be natively cloud-based and built on
programmable, virtualized, and disaggregated architectures. The separation of control …
programmable, virtualized, and disaggregated architectures. The separation of control …
Throughput prediction using machine learning in LTE and 5G networks
D Minovski, N Ögren, K Mitra… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The emergence of novel cellular network technologies, within 5G, are envisioned as key
enablers of a new set of use-cases, including industrial automation, intelligent …
enablers of a new set of use-cases, including industrial automation, intelligent …
[图书][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 …
Federated learning for 5G base station traffic forecasting
Cellular traffic prediction is of great importance on the path of enabling 5G mobile networks
to perform intelligent and efficient infrastructure planning and management. However …
to perform intelligent and efficient infrastructure planning and management. However …
Mobile edge computing-assisted admission control in vehicular networks: The convergence of communication and computation
With the spread of vehicular networks (VNs), technologies are needed to enable them to be
more reliable, to deliver lower latency, and to handle more intensive computation. Mobile …
more reliable, to deliver lower latency, and to handle more intensive computation. Mobile …