Deep Learning for Hybrid 5G Services in Mobile Edge Computing Systems: Learn from a Digital Twin

30 June 2019

Papers citing "Deep Learning for Hybrid 5G Services in Mobile Edge Computing Systems: Learn from a Digital Twin"

8 / 8 papers shown

Title
Multiple Access in the Era of Distributed Computing and Edge Intelligence Nikos G. Evgenidis Nikos A. Mitsiou Vasiliki I. Koutsioumpa Sotiris A. Tegos P. Diamantoulakis G. Karagiannidis 41 8 0 26 Feb 2024
Graph Neural Network-Based Bandwidth Allocation for Secure Wireless Communications Xin Hao Phee Lep Yeoh Yuhong Liu Changyang She B. Vucetic Yonghui Li 13 4 0 13 Dec 2023
Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and Insights Maryam Ben Driss Essaid Sabir H. Elbiaze Walid Saad 30 7 0 07 Dec 2023
A Bayesian Framework for Digital Twin-Based Control, Monitoring, and Data Collection in Wireless Systems Clement Ruah Osvaldo Simeone Bashir M. Al-Hashimi 27 28 0 02 Dec 2022
Smart Grid: Cyber Attacks, Critical Defense Approaches, and Digital Twin Tianming Zheng Ming Liu Deepak Puthal P. Yi Yue Wu Xiangjian He 16 14 0 24 May 2022
True-data Testbed for 5G/B5G Intelligent Network Yongming Huang Shengheng Liu Cheng Zhang X. You Hequan Wu 11 26 0 26 Nov 2020
Federated Learning for Task and Resource Allocation in Wireless High Altitude Balloon Networks Sihua Wang Mingzhe Chen Changchuan Yin Walid Saad Choong Seon Hong Shuguang Cui H. Vincent Poor 36 67 0 19 Mar 2020
Deep Learning for Ultra-Reliable and Low-Latency Communications in 6G Networks Changyang She Rui Dong Zhouyou Gu Zhanwei Hou Yonghui Li Wibowo Hardjawana Chenyang Yang Lingyang Song B. Vucetic AI4TS 19 104 0 22 Feb 2020