W3: Machine Learning for Wireless Communications
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
Paper 5:
Authors:
Paper 6:
Authors:
Paper 7:
Authors:
Paper 8:
Authors:
Paper 9:
Authors:
Paper 10:
Authors:
Paper 11:
Authors:
Paper 12:
Authors:
Session Category : Workshop