| Optimizing coverage and capacity in cellular networks using machine learning RM Dreifuerst, S Daulton, Y Qian, P Varkey, M Balandat, S Kasturia, ... ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 90 | 2021 |
| Massive MIMO in 5G: How beamforming, codebooks, and feedback enable larger arrays RM Dreifuerst, RW Heath IEEE Communications Magazine 61 (12), 18-23, 2023 | 44 | 2023 |
| Deep learning-based carrier frequency offset estimation with one-bit ADCs RM Dreifuerst, RW Heath, MN Kulkarni, J Charlie 2020 IEEE 21st International Workshop on Signal Processing Advances in …, 2020 | 38 | 2020 |
| Intent-aware radio resource scheduling in a ran slicing scenario using reinforcement learning CV Nahum, VHL Lopes, RM Dreifuerst, P Batista, I Correa, KV Cardoso, ... IEEE Transactions on Wireless Communications 23 (3), 2253-2267, 2023 | 20 | 2023 |
| SignalNet: A low resolution sinusoid decomposition and estimation network RM Dreifuerst, RW Heath IEEE Transactions on Signal Processing 70, 4454-4467, 2022 | 13 | 2022 |
| Machine learning codebook design for initial access and CSI type-II feedback in sub-6GHz 5G NR RM Dreifuerst, RW Heath IEEE Transactions on Wireless Communications, 2023 | 12 | 2023 |
| Massive MIMO Beam Management in Sub-6 GHz 5G NR RM Dreifuerst, RW Heath Jr, A Yazdan arXiv preprint arXiv:2204.06064, 2022 | 12 | 2022 |
| Deep reinforcement learning-based scheduling for multiband massive MIMO VHL Lopes, CV Nahum, RM Dreifuerst, P Batista, A Klautau, KV Cardoso, ... IEEE Access 10, 125509-125525, 2022 | 10 | 2022 |
| Load balancing and handover optimization in multi-band networks using deep reinforcement learning M Gupta, RM Dreifuerst, A Yazdan, PH Huang, S Kasturia, JG Andrews 2021 IEEE Global Communications Conference (GLOBECOM), 1-6, 2021 | 8 | 2021 |
| Hierarchical ML Codebook Design for Extreme MIMO Beam Management RM Dreifuerst, RW Heath IEEE Transactions on Machine Learning in Communications and Networking, 2024 | 5 | 2024 |
| CSI type-II codebook of codebooks RM Dreifuerst, RW Heath 2023 IEEE 24th International Workshop on Signal Processing Advances in …, 2023 | 3 | 2023 |
| Initial Access Codebook Design and CSI Type-II Feedback for Sub-6GHz 5G NR RM Dreifuerst, RW Heath arXiv preprint arXiv:2303.02850, 2023 | 3 | 2023 |
| Neural Codebook Design for Network Beam Management RM Dreifuerst, RW Heath Jr arXiv preprint arXiv:2403.03053, 2024 | 2 | 2024 |
| Beam training in mmWave vehicular systems: Machine learning for decoupling beam selection I Kilinc, RM Dreifuerst, J Kim, RW Heath 2024 IEEE International Black Sea Conference on Communications and …, 2024 | 1 | 2024 |
| ML Codebook Design for Initial Access and CSI Type-II Feedback in Sub-6GHz 5G NR RM Dreifuerst, RW Heath Jr arXiv preprint arXiv:2303.02850, 2023 | 1 | 2023 |
| End-to-End Radio Fingerprinting with Neural Networks RM Dreifuerst, A Graff, S Kumar, C Unger, D Bray arXiv preprint arXiv:2010.05169, 2020 | 1 | 2020 |
| Neural Codebook Design for MIMO Network Beam Management RM Dreifuerst, RW Heath IEEE Transactions on Wireless Communications, 2025 | | 2025 |
| Context-aware Codebook Design for 6G Extreme MIMO Systems RM Dreifuerst, I Kilinc, RW Heath 2024 IEEE 25th International Workshop on Signal Processing Advances in …, 2024 | | 2024 |
| Machine Learning-Assisted Beam Management and Codebook Design. RM Dreifuerst | | 2024 |
| Low resolution sinusoid decomposition and estimation RM Dreifuerst | | 2021 |
Robert HeathCharles Lee Powell Chair in Wireless Communication, University of California, San Diegoucsd.edu의 이메일 확인됨