Machine learning paradigms for next-generation wireless networks

C Jiang, H Zhang, Y Ren, Z Han… - IEEE Wireless …, 2016 - ieeexplore.ieee.org
Next-generation wireless networks are expected to support extremely high data rates and
radically new applications, which require a new wireless radio technology paradigm. The …

Qcell: Self-optimization of softwarized 5g networks through deep q-learning

B Casasole, L Bonati, S D'Oro… - 2021 IEEE Global …, 2021 - ieeexplore.ieee.org
With the unprecedented rise in traffic demand and mobile subscribers, real-time fine-grained
optimization frame-works are crucial for the future of cellular networks. Indeed, rigid and …

Infrastructure-wide and intent-based networking dataset for 5G-and-beyond AI-driven autonomous networks

J Andrade-Hoz, Q Wang, JM Alcaraz-Calero - Sensors, 2024 - mdpi.com
In the era of Autonomous Networks (ANs), artificial intelligence (AI) plays a crucial role for
their development in cellular networks, especially in 5G-and-beyond networks. The …

Wireless networks design in the era of deep learning: Model-based, AI-based, or both?

A Zappone, M Di Renzo… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
This paper deals with the use of emerging deep learning techniques in future wireless
communication networks. It will be shown that the data-driven approaches should not …

Knowledge-driven resource allocation for d2d networks: A wmmse unrolled graph neural network approach

H Yang, N Cheng, R Sun, W Quan, R Chai… - arXiv preprint arXiv …, 2023 - arxiv.org
This paper proposes an novel knowledge-driven approach for resource allocation in device-
to-device (D2D) networks using a graph neural network (GNN) architecture. To meet the …

AI-assisted E2E network slicing for integrated sensing and communication in 6G networks

MA Hossain, A Xiang, A Kiani… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
In the realm of modern wireless networks, the integration of wireless sensing and
communication systems is pivotal, especially in the context of the forthcoming 6G Internet of …

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 …

“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 …

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 …

Ten challenges in advancing machine learning technologies toward 6G

N Kato, B Mao, F Tang, Y Kawamoto… - IEEE Wireless …, 2020 - ieeexplore.ieee.org
As the 5G standard is being completed, academia and industry have begun to consider a
more developed cellular communication technique, 6G, which is expected to achieve high …