Cellular traffic prediction with machine learning: A survey

W Jiang - Expert Systems with Applications, 2022 - Elsevier
Cellular networks are important for the success of modern communication systems, which
support billions of mobile users and devices. Powered by artificial intelligence techniques …

From 5G to 6G—challenges, technologies, and applications

AI Salameh, M El Tarhuni - Future Internet, 2022 - mdpi.com
As the deployment of 5G mobile radio networks gains momentum across the globe, the
wireless research community is already planning the successor of 5G. In this paper, we …

Computation offloading and resource allocation in MEC-enabled integrated aerial-terrestrial vehicular networks: A reinforcement learning approach

N Waqar, SA Hassan, A Mahmood… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
As important services of the future sixth-generation (6G) wireless networks, vehicular
communication and mobile edge computing (MEC) have received considerable interest in …

[HTML][HTML] Industrial digital twins at the nexus of NextG wireless networks and computational intelligence: A survey

S Zeb, A Mahmood, SA Hassan, MDJ Piran… - Journal of Network and …, 2022 - Elsevier
By amalgamating recent communication and control technologies, computing and data
analytics techniques, and modular manufacturing, Industry 4.0 promotes integrating cyber …

[HTML][HTML] Towards defining industry 5.0 vision with intelligent and softwarized wireless network architectures and services: A survey

S Zeb, A Mahmood, SA Khowaja, K Dev… - Journal of Network and …, 2024 - Elsevier
Abstract Industry 5.0 vision, a step toward the next industrial revolution and enhancement to
Industry 4.0, conceives the new goals of resilient, sustainable, and human-centric …

Short-term traffic prediction using deep learning long short-term memory: Taxonomy, applications, challenges, and future trends

A Khan, MM Fouda, DT Do, A Almaleh… - IEEE Access, 2023 - ieeexplore.ieee.org
This paper surveys the short-term road traffic forecast algorithms based on the long-short
term memory (LSTM) model of deep learning. The algorithms developed in the last three …

Industry 5.0 is coming: A survey on intelligent nextG wireless networks as technological enablers

S Zeb, A Mahmood, SA Khowaja, K Dev… - arxiv preprint arxiv …, 2022 - arxiv.org
Industry 5.0 vision, a step toward the next industrial revolution and enhancement to Industry
4.0, envisioned the new goals of resilient, sustainable, and human-centric approaches in …

Split federated learning for 6G enabled-networks: Requirements, challenges and future directions

H Hafi, B Brik, PA Frangoudis, A Ksentini… - IEEE Access, 2024 - ieeexplore.ieee.org
Sixth-generation (6G) networks anticipate intelligently supporting a wide range of smart
services and innovative applications. Such a context urges a heavy usage of Machine …

[HTML][HTML] Towards 6G: Key technological directions

C De Alwis, P Kumar, QV Pham, K Dev, A Kalla… - ICT Express, 2023 - Elsevier
Sixth-generation mobile networks (6G) are expected to reach extreme communication
capabilities to realize emerging applications demanded by the future society. This paper …

Deep reinforcement learning for containerized edge intelligence inference request processing in IoT edge computing

L Nkenyereye, KJ Baeg… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Edge intelligence (EI) refers to a set of connected systems and devices for artificial
intelligence (AI) data collected and learned near the data collection site. The EI model …