Machine Learning for Signal Processing in 5G and Beyond: Review
To meet the demand of modern application, modern machine learning and adaptive signal processing techniques are needed. With the help of revolutionary advancements in mobile communication such as 5G and 6G, integration of machine learning in signal processing has emerged as a popular research field nowadays. In this survey paper, researches on machine learning for signal processing in 5G and 6G are considered. Many papers are examined carefully and the revolutionary ideas and applications will be mentioned in advance. Included subjects are channel estimation, beamforming, resource allocation, interference management and more. By using the adaptability and capabilities of machine learning, how these techniques can enhance the performance, efficiency, and reliability of nextgeneration wireless networks will be discussed in this paper.
Authors
- Ibraheem Shayea (ORCID: https://orcid.org/0000-0003-0957-4468)
- Leila Rzayeva (ORCID: https://orcid.org/0000-0002-3382-4685)
- Bilal Saoud (ORCID: https://orcid.org/0000-0002-3026-6016)
- Mustafa Kurt (ORCID: https://orcid.org/0000-0003-1838-3575)
Institutions
- University of Bouira (DZ)
- Astana Medical University (KZ)
- Istanbul Technical University (TR)
Publication Details
- Published
- 2024-12-22
- DOI
- https://doi.org/10.1109/cicn63059.2024.10847469
- Primary Topic
- Advanced Signal Processing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00