Content popularity prediction based on quantized federated Bayesian learning in fog radio access networks

Content popularity prediction based on quantized federated Bayesian learning in fog radio access networks

In this paper, we investigate the content popularity prediction problem in cache-enabled fog radio access networks (F-RANs). In order to predict the content popularity with high accuracy and low complexity, we propose a Gaussian process based regressor to model the content request pattern. Firstly,...

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Bibliographic Details
Main Authors: Tao, Yunwei, Jiang, Yanxiang, Zheng, Fu-Chun, Wang, Zhiheng, Zhu, Pengcheng, Tao, Meixia, Niyato, Dusit, You, Xiaohu
Other Authors: School of Computer Science and Engineering
Format: Journal Article
Language:English
Published: 2023
Subjects:
Engineering::Computer science and engineering
Bayesian Learning
Federated Learning
Online Access:https://hdl.handle.net/10356/172071

Internet

https://hdl.handle.net/10356/172071

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