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Self-Supervised RF Signal Representation Learning for NextG Signal Classification with Deep Learning
Self-supervised learning (SSL) enables the learning of useful representations from Radio Frequency (RF) signals themselves even when only limited training data samples with labels are available.
Gaussian Kernel Variance For an Adaptive Learning Method on Signals Over Graphs
To be more specific, we focus on SKG with a Gaussian kernel and specify how to find a suitable variance for the kernel.
Machine Learning in NextG Networks via Generative Adversarial Networks
GANs have the following advantages.
Wave-Controlled Metasurface-Based Reconfigurable Intelligent Surfaces
Reconfigurable Intelligent Surfaces (RISs) are programmable metasurfaces that can adaptively steer received electromagnetic energy in desired directions by employing controllable phase shifting cells.
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