Mingzhe Chen
Mingzhe Chen
Postdoctoral Researcher at Princeton University and CUHKSZ
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα princeton.edu - Αρχική σελίδα
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Παρατίθεται από
Παρατίθεται από
Έτος
Caching in the sky: Proactive deployment of cache-enabled unmanned aerial vehicles for optimized quality-of-experience
M Chen, M Mozaffari, W Saad, C Yin, M Debbah, CS Hong
IEEE Journal on Selected Areas in Communications 35 (5), 1046-1061, 2017
4662017
A vision of 6G wireless systems: Applications, trends, technologies, and open research problems
W Saad, M Bennis, M Chen
IEEE Network, 2020
4512020
Artificial Neural Networks-Based Machine Learning for Wireless Networks: A Tutorial
M Chen, U Challita, W Saad, C Yin, M Debbah
IEEE Communications Surveys & Tutorials, 2019
378*2019
A joint learning and communications framework for federated learning over wireless networks
M Chen, Z Yang, W Saad, C Yin, HV Poor, S Cui
arXiv preprint arXiv:1909.07972, 2019
1542019
Echo state networks for proactive caching in cloud-based radio access networks with mobile users
M Chen, W Saad, C Yin, M Debbah
IEEE Transactions on Wireless Communications 16 (6), 3520-3535, 2017
1162017
Virtual reality over wireless networks: Quality-of-service model and learning-based resource management
M Chen, W Saad, C Yin
IEEE Transactions on Communications 66 (11), 5621-5635, 2018
942018
Echo State Networks for Self-Organizing Resource Allocation in LTE-U with Uplink-Downlink Decoupling
M Chen, W Saad, C Yin
IEEE Transactions on Wireless Communications, 2016
752016
Machine Learning for Wireless Connectivity and Security of Cellular-Connected UAVs
U Challita, A Ferdowsi, M Chen, W Saad
IEEE Wireless Communications 26 (1), 28 - 35, 2019
68*2019
Liquid state machine learning for resource and cache management in LTE-U unmanned aerial vehicle (UAV) networks
M Chen, W Saad, C Yin
IEEE Transactions on Wireless Communications 18 (3), 1504-1517, 2019
662019
Energy efficient federated learning over wireless communication networks
Z Yang, M Chen, W Saad, CS Hong, M Shikh-Bahaei
arXiv preprint arXiv:1911.02417, 2019
572019
Liquid state machine learning for resource allocation in a network of cache-enabled LTE-U UAVs
M Chen, W Saad, C Yin
GLOBECOM 2017-2017 IEEE Global Communications Conference, 1-6, 2017
402017
Echo-liquid state deep learning for content transmission and caching in wireless VR networks with cellular-connected UAVs
M Chen, W Saad, C Yin
IEEE Transactions on Communications, 2019
392019
Convergence time optimization for federated learning over wireless networks
M Chen, HV Poor, W Saad, S Cui
arXiv preprint arXiv:2001.07845, 2020
262020
Data correlation-aware resource management in wireless virtual reality (VR): An echo state transfer learning approach
M Chen, W Saad, C Yin, M Debbah
IEEE Transactions on Communications 67 (6), 4267-4280, 2019
262019
Federated echo state learning for minimizing breaks in presence in wireless virtual reality networks
M Chen, O Semiari, W Saad, X Liu, C Yin
IEEE Transactions on Wireless Communications 19 (1), 177-191, 2019
232019
6G White Paper on Machine Learning in Wireless Communication Networks
S Ali, W Saad, N Rajatheva, K Chang, D Steinbach, B Sliwa, C Wietfeld, ...
arXiv preprint arXiv:2004.13875, 2020
222020
Deep learning for optimal deployment of uavs with visible light communications
Y Wang, M Chen, Z Yang, T Luo, W Saad
arXiv preprint arXiv:1912.00752, 2019
182019
Resource management for wireless virtual reality: Machine learning meets multi-attribute utility
M Chen, W Saad, C Yin
GLOBECOM 2017-2017 IEEE Global Communications Conference, 1-7, 2017
162017
Optimized uplink-downlink decoupling in LTE-U networks: An echo state approach
M Chen, W Saad, C Yin
2016 IEEE International Conference on Communications (ICC), 1-6, 2016
162016
Federated Learning in the Sky: Joint Power Allocation and Scheduling with UAV Swarms
T Zeng, O Semiari, M Mozaffari, M Chen, W Saad, M Bennis
arXiv preprint arXiv:2002.08196, 2020
152020
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