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 |