Search Results - deep+learning

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Methods for real-time wideband RF waveform and emission classification

Revolutionary deep learning tech for accurate, real-time spectrum sensing of wireless signals like 5G, WiFi, and Bluetooth https://nu.testtechnologypublisher.com/files/sites/mark-saulich-17.jpg Background: Spectrum sensing is crucial in wireless communications for efficiently utilizing the limited available radio frequency (RF) spectrum....

Published: 1/29/2025 | Updated: 7/14/2024 | Inventor(s): Tommaso Melodia, Milin Zhang, Salvatore D'Oro, Daniel Uvaydov, Francesco Restuccia, Clifton Robinson

Keywords(s): Deep learning, O-RAN, Spectrum sensing

Category(s): Technology Classifications > 3. Computer Science, Technology Classifications > WIoT

SEM-O-RAN: Semantic NextG O-RAN Slicing for Data-Driven Edge-Assisted Mobile Applications

SEM-O-RAN uses O-RAN architecture and semantic compression to offload ML tasks to the edge, optimizing network resources and reducing latency. Copy Image URL via instructions below https://nu.testtechnologypublisher.com/files/sites/mark-saulich-16.jpg Background The exponential growth in the number of connected devices and the increasingly...

Published: 1/27/2025 | Updated: 7/14/2024 | Inventor(s): Corrado Puligheddu, Francesco Restuccia, Carla Fabiana Chiasserini

Keywords(s): 5G and beyond, 5G Networks, 6G, Deep learning, Machine Learning, Mobile devices, O-RAN, Semantics, Software-defined Networks

Category(s): Technology Classifications > 3. Computer Science, Technology Classifications > WIoT

SplitBeam: Rethinking Beamforming Feedback in MU-MIMO Wi-Fi Systems Through Split Neural Networks

SplitBeam uses a split deep neural network to optimize Wi-Fi beamforming, improving connectivity and reducing interference by processing the channel state information matrix with machine learning. Copy Image URL via instructions below https://nu.testtechnologypublisher.com/files/sites/mark-saulich-9.jpg Background: Contemporary Wi-Fi networks...

Published: 1/27/2025 | Updated: 7/14/2024 | Inventor(s): Niloofar Bahadori, Francesco Restuccia, Marco Levorato, Yoshitomo Matsubara

Keywords(s): Deep learning, MU-MIMO, Split Computing, Wi-Fi

Category(s): Technology Classifications > 3. Computer Science

Rheology-Informed Neural Networks for complex fluids

INV-21050 Background Many complex and structured fluids exhibit a wide range of rheological responses to different flow characteristics. The ability to predict this complex rheological behavior is essential in better understanding and designing these complex fluids and their processing conditions. Despite the increasing trend in using artificial...

Published: 1/27/2025 | Updated: 3/21/2024 | Inventor(s): Mohammadamin Mahmoudabadbozchelou, Safa Jamali

Keywords(s): 3D Printer, Adaptive, Artificial intelligence, Biotech, Computational Modeling, Deep learning, Fabrication, Machine Learning, Manufacturing, Materials, Oil/petroleum, Process Engineering

Category(s): -Oil and Gas, Technology Classifications > 3. Computer Science, Technology Classifications > 2. Physical Science, Technology Classifications > 3. Computer Science > AI, Technology Classifications > 3. Computer Science > Neural Networks

DeepBeam: Coordination-Free mmWave Beam Management With Deep Waveform Learning

DeepBeam uses deep neural networks for passive, efficient 5G beam alignment, reducing latency and overhead. Copy Image URL via instructions below https://nu.testtechnologypublisher.com/files/sites/mark-saulich-18.jpg Background: The surge in mobile data traffic necessitates a new generation of wireless systems, leading to the development...

Published: 1/27/2025 | Updated: 3/21/2024 | Inventor(s): Michele Polese, Francesco Restuccia, Tommaso Melodia

Keywords(s): 5G Networks, 5g NR, Artificial intelligence, Beam, Beam Management, Communications, Deep learning, Machine Learning, Millimeter Wave Spectrum, Mobile devices, Next-generation Mobile Networks, Phased-Array

Category(s): -Networks, Technology Classifications > 3. Computer Science, Technology Classifications > WIoT