Compositional Distributed Learning for Multi-View Perception: A Maximal Coding Rate Reduction Perspective
In this letter, we formulate a compositional distributed learning framework for multi-view perception by leveraging the maximal coding rate reduction principle combined […]
Indoor Safety of Wireless Power Transfer: A Machine Learning Approach
This article introduces an innovative approach integrating machine learning (ML) methods into a far-field wireless power transfer (WPT) system. Within this system, […]
Near-Field MIMO Channel Acquisition: Geometry-Aided Feedback and Transmission Design
Near-field (NF) line-of-sight (LoS) MIMO systems enable efficient channel state information (CSI) acquisition and precoding by exploiting known antenna geometries at both […]
A Cost-Efficient Approach to Managing Simultaneous Charging Sessions in Large-Scale EV Stations
The rapid adoption of electric vehicles (EVs) poses significant challenges for large-scale EV charging stations in terms of efficiently addressing dynamic charging […]
QuaRTA-6G: Unified Post-Quantum Security and Quantum Learning for UAVs in 6G IoT
Unmanned Aerial Vehicles (UAVs), as key enablers of 6G-enabled Internet of Things (IoT) ecosystems, facilitate dynamic aerial coverage, seamless edge intelligence, and […]
Noninvasive and Quantitative Brain Temperature Monitoring Using Wearable Microwave Technique
A non-invasive and quantitative microwave method and setup for brain temperature monitoring is proposed in this study. The proposed microwave setup is […]
End-to-End Joint Waveform and Beamforming Optimization for RF Wireless Power Transfer with Hybrid Transmit Architecture and Non-Linear Energy Harvesters
Radio frequency (RF) wireless power transfer (WPT) is an appealing technology to provide sustainable and cost-efficent power supply to low-power devices in […]
Real-Time Tracking in a Status Update System with an Imperfect Feedback Channel
We consider a status update system consisting of a finite-state Markov source, an energy-harvesting-enabled transmitter, and a sink. The forward and feedback […]
eSNR-Adjusted Channel Decorrelation Preprocessing for AMP Data Detection in Highly Correlated THz MIMO Systems
The approximate message passing (AMP)-based data detection is a highly effective solution for terahertz (THz) multiple-input multiple-output (MIMO) communications, enabling reliable data […]
Alzheimer’s disease classification based on multimodal consistent distribution and trusted fusion
Multimodal data fusion has the potential to improve Alzheimer’s disease (AD) classification by capturing diverse disease manifestations. However, existing methods often fail […]