Adaptive Retraining of AI/ML Model for Beyond 5G Networks: A Predictive Approach

V Gudepu, VR Chintapalli, P Castoldi… - 2023 IEEE 9th …, 2023 - ieeexplore.ieee.org
Beyond fifth-generation (B5G) networks (namely 6G) aim to support high data rates, low-
latency applications, and massive machine communications. Integrating Artificial …

An online context-aware machine learning algorithm for 5G mmWave vehicular communications

GH Sim, S Klos, A Asadi, A Klein… - IEEE/ACM Transactions …, 2018 - ieeexplore.ieee.org
Millimeter-Wave (mmWave) bands have become the de-facto candidate for 5G vehicle-to-
everything (V2X) since future vehicular systems demand Gbps links to acquire the …

Machine learning meets communication networks: Current trends and future challenges

I Ahmad, S Shahabuddin, H Malik, E Harjula… - IEEE …, 2020 - ieeexplore.ieee.org
The growing network density and unprecedented increase in network traffic, caused by the
massively expanding number of connected devices and online services, require intelligent …

[HTML][HTML] A survey: Distributed Machine Learning for 5G and beyond

O Nassef, W Sun, H Purmehdi, M Tatipamula… - Computer Networks, 2022 - Elsevier
Abstract 5 G is the fifth generation of cellular networks. It enables billions of connected
devices to gather and share information in real time; a key facilitator in Industrial Internet of …

AI-enabled future wireless networks: Challenges, opportunities, and open issues

M Elsayed, M Erol-Kantarci - IEEE Vehicular Technology …, 2019 - ieeexplore.ieee.org
An expected plethora of demanding services and use cases mandates a revolutionary shift
in the way future wireless network resources are managed. Indeed, when application …

[引用][C] Machine learning and software defined networks for high-density wlans

Á López-Raventós, F Wilhelmi… - arXiv preprint arXiv …, 2018 - Apr

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 …

When machine learning meets wireless cellular networks: Deployment, challenges, and applications

U Challita, H Ryden, H Tullberg - IEEE Communications …, 2020 - ieeexplore.ieee.org
AI powered wireless networks promise to revolutionize the conventional operation and
structure of current networks from network design to infrastructure management, cost …

SRCON: A data-driven network performance simulator for real-world wireless networks

ZQ Luo, X Zheng, D López-Pérez, Q Yan… - IEEE …, 2023 - ieeexplore.ieee.org
Optimizing the performance of a real-world wireless network is extremely challenging
because of the difficulty to predict the network performance as a function of network …

Secure federated learning in 5G mobile networks

M Isaksson, K Norrman - GLOBECOM 2020-2020 IEEE Global …, 2020 - ieeexplore.ieee.org
Machine Learning (ML) is an important enabler for optimizing, securing and managing
mobile networks. This leads to increased collection and processing of data from network …