4 papers · 1 filter
Unlocking Realism and Interpretability in Wireless Channel Synthesis: A Physics-Guided Generative Approach
Satyavrat Wagle, Akshay Malhotra, Shahab Hamidi-Rad +3
In recent years, machine learning (ML) methods have become increasingly popular for wireless communication systems. These require large amounts of data reflecting the behavior of r…
CITYMPC: A Large-Scale Physics-Informed Benchmark and Tool for Generative Complete Multipath Wireless Channel Modeling
Ashwin Natraj Arun, David R. Nickel, Yaguang Zhang +6
Multipath wireless channels are fully characterized by multipath components (MPCs), including complex channel gain, propagation delay, angle of departure (AoD) and angle of arrival…
Coherence-Aware Over-the-Air Distributed Learning under Heterogeneous Link Impairments
Mehdi Karbalayghareh, David J. Love, Christopher G. Brinton
Distributed machine learning (ML) over wireless networks hinges on accurate channel state information (CSI) and efficient exchange of high-dimensional model updates. These demands…
Communication-Efficient Quantum Federated Learning over Large-Scale Wireless Networks
Shaba Shaon, Christopher G. Brinton, Dinh C. Nguyen
Quantum federated learning (QFL) combines the robust data processing of quantum computing with the privacy-preserving features of federated learning (FL). However, in large-scale w…