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

• 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: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering; Bayesian Learning; Federated Learning
• Online Access: https://hdl.handle.net/10356/172071
• Institution: Nanyang Technological University

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,...