Using Deep-Learning for 5G End-to-End Delay Estimation Based on Gaussian Mixture Models

Using Deep-Learning for 5G End-to-End Delay Estimation Based on Gaussian Mixture Models

Deep learning is used in various applications due to its advantages over traditional Machine Learning (ML) approaches in tasks encompassing complex pattern learning, automatic feature extraction, scalability, adaptability, and performance in general. This paper proposes an end-to-end (E2E) delay est...

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Bibliographic Details
Main Authors: Diyar Fadhil, Rodolfo Oliveira
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Information
Subjects:
end-to-end delay
machine learning
estimation
heterogeneous networks
quality of service
Online Access:https://www.mdpi.com/2078-2489/14/12/648

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https://www.mdpi.com/2078-2489/14/12/648

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