A survey of online data-driven proactive 5G network optimisation using machine learning

B Ma, W Guo, J Zhang - IEEE access, 2020 - ieeexplore.ieee.org
In the fifth-generation (5G) mobile networks, proactive network optimisation plays an
important role in meeting the exponential traffic growth, more stringent service requirements …

“One Layer to Rule Them All” Data Layer‐oriented 6G Networks

M Corici, T Magedanz - Shaping Future 6G Networks: Needs …, 2021 - Wiley Online Library
With the high increase in the number of connected devices, the 6G network optimizations
cannot rely only on protocols and architecture customizations as in 5G. Instead, a better …

[PDF][PDF] Empowering the future 5G networks: an AI based approach

A CB, P Sharma - Telecom Business Review, 2017 - academia.edu
The next telecommunications standard, 5G, envisions that the future networks will support
advanced use cases, such as Internet of things while supporting voluminous simultaneous …

From classical to quantum machine learning: Survey on routing optimization in 6G software defined networking

O Bouchmal, B Cimoli, R Stabile… - Frontiers in …, 2023 - frontiersin.org
The sixth generation (6G) of mobile networks will adopt on-demand self-reconfiguration to
fulfill simultaneously stringent key performance indicators and overall optimization of usage …

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 …

Deep learning based optimization in wireless network

L Liu, Y Cheng, L Cai, S Zhou… - 2017 IEEE international …, 2017 - ieeexplore.ieee.org
With the development of wireless networks, the scale of network optimization problems is
growing correspondingly. While algorithms have been designed to reduce complexity in …

Toward reinforcement-learning-based service deployment of 5G mobile edge computing with request-aware scheduling

Y Zhai, T Bao, L Zhu, M Shen, X Du… - IEEE Wireless …, 2020 - ieeexplore.ieee.org
5G wireless network technology will not only significantly increase bandwidth but also
introduce new features such as mMTC and URLLC. However, high request latency will …

AI empowered resource management for future wireless networks

Y Shen, J Zhang, SH Song… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Resource management plays a pivotal role in wireless networks, which, unfortunately, leads
to challenging NP-hard problems. Artificial Intelligence (AI), especially deep learning …

Deep learning meets wireless network optimization: Identify critical links

L Liu, B Yin, S Zhang, X Cao… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
With the superior capability of discovering intricate structure of large data sets, deep learning
has been widely applied in various areas including wireless networking. While existing deep …

Survey on machine learning for intelligent end-to-end communication toward 6G: From network access, routing to traffic control and streaming adaption

F Tang, B Mao, Y Kawamoto… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
The end-to-end quality of service (QoS) and quality of experience (QoE) guarantee is quite
important for network optimization. The current 5G and conceived 6G network in the future …