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Federated Learning over Wireless IoT Networks with Optimized Communication and Resources
Hence, we investigate the problem of jointly optimized communication efficiency and resources for FL over wireless Internet of things (IoT) networks.
Fully Decentralized Federated Learning Based Beamforming Design for UAV Communications
To handle the data explosion in the era of internet of things (IoT), it is of interest to investigate the decentralized network, with the aim at relaxing the burden to central server along with keeping data privacy.
Signal Processing
Decentralized Beamforming Design for Intelligent Reflecting Surface-enhanced Cell-free Networks
Cell-free networks are considered as a promising distributed network architecture to satisfy the increasing number of users and high rate expectations in beyond-5G systems.
Learning Based Hybrid Beamforming for Millimeter Wave Multi-User MIMO Systems
Hybrid beamforming (HBF) design is a crucial stage in millimeter wave (mmWave) multi-user multi-input multi-output (MU-MIMO) systems.
Learning Based Hybrid Beamforming Design for Full-Duplex Millimeter Wave Systems
We propose two learning schemes to design HBF for FD mmWave systems, i. e., extreme learning machine based HBF (ELM-HBF) and convolutional neural networks based HBF (CNN-HBF).
