Machine and Deep Learning in Cellular Networks
A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: closed (15 June 2023) | Viewed by 537
Special Issue Editor
Special Issue Information
Dear Colleagues,
Future cellular, 5G and beyond, technologies are evolving toward a unified communication and computing ecosystem to satisfy the strict requirements of evolving services and applications, e.g., VR/AR/XR and industry 4.0. The challenging nature of the wireless medium and the complexity of the unified system motivate incorporating advanced machine and deep learning techniques in the design of various application and network functions. This Special Issue solicits your contributions that illustrate how machine and deep learning can improve network and application performance in future cellular systems. The proposed solutions are expected to address key design problems, such as resource management, traffic management, mobility management, and adaptive application decisions to improve key performance metrics, such as resource utilization, energy efficiency, and quality of experience. Paper focusing on the collection of a large-scale dataset, the design of accurate ML models that overcome the aforementioned challenges, and the scalable implementation of ML models in real systems are of particular interest. The objective of this Special Issue is to highlight state-of-the-art research that leverages machine learning for designing future cellular networks and applications.
Dr. Ahmed Zahran
Guest Editor
Manuscript Submission Information
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Keywords
- 5G
- 6G
- machine learning
- deep learning
- federated learning
- VR/AR/XR
- IoT
- resource management
- QoE
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