SPCOM-8: Deep learning for communications |
Session Type: Poster |
Time: Friday, 11 June, 14:00 - 14:45 |
Location: Gather.Town |
Virtual Session: View on Virtual Platform |
Session Chair: Mingyi Hong, University of Minnesota |
SPCOM-8.1: DEEP WEIGHTED MMSE DOWNLINK BEAMFORMING |
Lissy Pellaco; KTH Royal Institute of Technology |
Mats Bengtsson; KTH Royal Institute of Technology |
Joakim Jaldén; KTH Royal Institute of Technology |
SPCOM-8.2: DEEP GENERATIVE MODEL LEARNING FOR BLIND SPECTRUM CARTOGRAPHY WITH NMF-BASED RADIO MAP DISAGGREGATION |
Sagar Shrestha; Oregon State University |
Xiao Fu; Oregon State University |
Mingyi Hong; University of Minnesota |
SPCOM-8.3: MITIGATING CLIPPING DISTORTION IN OFDM USING DEEP RESIDUAL LEARNING |
Muhammad Shahmeer Omar; Georgia Institute of Technology |
Xiaoli Ma; Georgia Institute of Technology |
SPCOM-8.4: A LOW-COMPLEXITY ADMM-BASED MASSIVE MIMO DETECTORS VIA DEEP NEURAL NETWORKS |
Isayiyas Nigatu Tiba; Xidian University |
Quan Zhang; Xidian University |
Jing Jiang; Xidian University |
Yongchao Wang; Xidian University |
SPCOM-8.5: REAL-TIME RADIO MODULATION CLASSIFICATION WITH AN LSTM AUTO-ENCODER |
Ziqi Ke; University of Texas at Austin |
Haris Vikalo; University of Texas at Austin |