Federated Learning-based Heterogeneous Load Prediction and Slicing for 5G Systems and Beyond

Author:

Pu Liyuan1,Cui Qimei1,I Xiangjun Li1,Zhao Borui1,Ni Wei2,Ai Ming3,Tao Xiaofeng1

Affiliation:

1. Beijing University of Posts and Telecommunications,Key Laboratory of Universal Wireless Communication,Beijing,China

2. The Commonwealth Scientific and Industrial Research Organisation,Sydney,Australia

3. CICT Mobile Communication Technology Co., Ltd.,Beijing

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

IEEE

Reference20 articles.

1. An overview of cooperative communications

2. Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts

3. Device Association for RAN Slicing Based on Hybrid Federated Deep Reinforcement Learning

4. Dual attention-based federated learning for wireless traffic prediction;chuanting;IEEE INFOCOM 2021,2021

5. A multi-source dataset of urban life in the city of Milan and the Province of Trentino;gianni;Scientific Data,2015

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