Deep learning in mobile and wireless networking: A survey
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …
services pose unprecedented demands on mobile and wireless networking infrastructure …
Deep learning challenges and prospects in wireless sensor network deployment
Y Qiu, L Ma, R Priyadarshi - Archives of Computational Methods in …, 2024 - Springer
This paper explores the transformative integration of deep learning applications in the
deployment of Wireless Sensor Networks (WSNs). As WSNs continue to play a pivotal role in …
deployment of Wireless Sensor Networks (WSNs). As WSNs continue to play a pivotal role in …
[HTML][HTML] A survey of 5G network systems: challenges and machine learning approaches
Abstract 5G cellular networks are expected to be the key infrastructure to deliver the
emerging services. These services bring new requirements and challenges that obstruct the …
emerging services. These services bring new requirements and challenges that obstruct the …
5g support for industrial iot applications—challenges, solutions, and research gaps
Industrial IoT has special communication requirements, including high reliability, low
latency, flexibility, and security. These are instinctively provided by the 5G mobile …
latency, flexibility, and security. These are instinctively provided by the 5G mobile …
From 5G to 6G technology: meets energy, internet-of-things and machine learning: a survey
Due to the rapid development of the fifth-generation (5G) applications, and increased
demand for even faster communication networks, we expected to witness the birth of a new …
demand for even faster communication networks, we expected to witness the birth of a new …
A survey of networking applications applying the software defined networking concept based on machine learning
The main task of future networks is to build, as much as possible, intelligent networking
architectures for intellectualization, activation, and customization. Software-defined …
architectures for intellectualization, activation, and customization. Software-defined …
Machine learning meets communication networks: Current trends and future challenges
The growing network density and unprecedented increase in network traffic, caused by the
massively expanding number of connected devices and online services, require intelligent …
massively expanding number of connected devices and online services, require intelligent …
Machine learning threatens 5G security
J Suomalainen, A Juhola, S Shahabuddin… - IEEE …, 2020 - ieeexplore.ieee.org
Machine learning (ML) is expected to solve many challenges in the fifth generation (5G) of
mobile networks. However, ML will also open the network to several serious cybersecurity …
mobile networks. However, ML will also open the network to several serious cybersecurity …
Network resource allocation system for QoE-aware delivery of media services in 5G networks
A Martin, J Egaña, J Flórez, J Montalban… - IEEE Transactions …, 2018 - ieeexplore.ieee.org
The explosion in the variety and volume of video services makes bandwidth and latency
performance of networks more critical to the user experience. The media industry's …
performance of networks more critical to the user experience. The media industry's …
Machine learning for 5G security: Architecture, recent advances, and challenges
The granularization of crucial network functions implementation using software-centric, and
virtualized approaches in 5G networks have brought forth unprecedented security …
virtualized approaches in 5G networks have brought forth unprecedented security …