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W3: Machine Learning for Wireless Communications - VTC 2019 Fall

W3: Machine Learning for Wireless Communications

September 22, 2019
9:00 AM  -  12:30 PM
Kaimuki 2

Session Details:

Paper 1: An Adaptive Machine Learning Based Approach for the Cancellation of Second-Order-Intermodulation Distortions in 4G/5G Transceivers

Authors: Oliver Ploder, Oliver Lang, Thomas Paireder, Mario Huemer, Johannes Kepler University Linz

Paper 2: Deep Neural Network based Cell Sleeping Control and Beamforming Optimization in Cloud-RAN

Authors: Gehui?Du, Luhan Wang, Qing Liao, Haoxiang Hu, Beijing University of Posts and Telecommunications

Paper 3: Democratized Radio Tomography: Using Consumer Equipment to See Through Walls

Authors: Lucy Bowen, Robert Hulbert, Jason Fong, Zachary Rentz, Bruce DeBruhl, California Polytechnic State University

Paper 4: Learning the Wireless V2I Channels Using Deep Neural Networks

Authors: Tian-Hao Li, Muhammad RA Khandaker, Heriot-Watt University; Faisal Tariq, University of Glasgow; Kai-Kit Wong, University College London; Risala Tasin Khan, Jahangirnagar University

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Session Category :  Workshop