MP1a.4

Machine Learning Based Homomorphic Directional Beamforming with TTD Arrays

Ibrahim Pehlivan, Benjamin W. Domae, Rushabha Balaji, Danijela Cabric, University of California Los Angeles, United States
Session:
MP1a: Machine Learning for Communications Lecture
Track:
Communication Systems
Location:
Heather
Presentation Time:
Mon, 27 Oct, 14:45 - 15:10 PT (UTC -7)
Presentation
Discussion
Resources
No resources available.
Session MP1a
MP1a.1: A Self-Refining Multi-Layer Receiver Pipeline
Shahab Hamidi-Rad, Akshay Malhotra, InterDigital, United States
MP1a.2: Quantum Connected Collaborative Learning with Superdense Coding for Wireless Internet-of-Everything Networks
Goki F. R. Purba, Bhaskara Narottama, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, Canada; Saeed R. Khosravirad, Nokia Bell Labs, United States; Trung Q. Duong, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, Canada
MP1a.3: Comparing Stochastic and Ray Tracing Datasets in Machine Learning for Wireless Applications
Joao Morais, Arizona State University, United States; Akshay Malhotra, Shahab Hamidi-Rad, InterDigital, United States; Ahmed Alkhateeb, Arizona State University, United States
MP1a.4: Machine Learning Based Homomorphic Directional Beamforming with TTD Arrays
Ibrahim Pehlivan, Benjamin W. Domae, Rushabha Balaji, Danijela Cabric, University of California Los Angeles, United States
Contacts