| Deep neural network-based active user detection for grant-free NOMA systems W Kim, Y Ahn, B Shim IEEE Transactions on Communications 68 (4), 2143-2155, 2020 | 98 | 2020 |
| Deep reinforcement learning-based network slicing for beyond 5G K Suh, S Kim, Y Ahn, S Kim, H Ju, B Shim IEEE Access 10, 7384-7395, 2022 | 58 | 2022 |
| Toward intelligent millimeter and terahertz communication for 6G: Computer vision-aided beamforming Y Ahn, J Kim, S Kim, K Shim, J Kim, S Kim, B Shim IEEE Wireless Communications 30 (5), 179-186, 2022 | 42 | 2022 |
| Towards deep learning-aided wireless channel estimation and channel state information feedback for 6G W Kim, Y Ahn, J Kim, B Shim Journal of Communications and Networks 25 (1), 61-75, 2023 | 38 | 2023 |
| Active User Detection and Channel Estimation for Massive Machine-Type Communication: Deep Learning Approach Y Ahn, W Kim, B Shim IEEE Internet of Things Journal 9 (14), 11904-11917, 2022 | 33 | 2022 |
| Massive data generation for deep learning-aided wireless systems using meta learning and generative adversarial network J Kim, Y Ahn, B Shim IEEE Transactions on Vehicular Technology 72 (1), 1302-1306, 2022 | 13 | 2022 |
| Parametric sparse channel estimation using long short-term memory for mmwave massive mimo systems J Kim, Y Ahn, S Kim, B Shim ICC 2022-IEEE International Conference on Communications, 1397-1402, 2022 | 13 | 2022 |
| Active user detection of machine-type communications via dimension spreading neural network W Kim, G Lim, Y Ahn, B Shim ICC 2019-2019 IEEE International Conference on Communications (ICC), 1-6, 2019 | 10 | 2019 |
| Deep neural network-based joint active user detection and channel estimation for mMTC Y Ahn, W Kim, B Shim ICC 2020-2020 IEEE International Conference on Communications (ICC), 1-6, 2020 | 9 | 2020 |
| Deep learning-based beamforming for intelligent reflecting surface-assisted mmWave systems Y Ahn, B Shim 2021 International Conference on Information and Communication Technology …, 2021 | 7 | 2021 |
| Computer Vision-Aided Proactive Mobility Management for 6G Terahertz Communications Y Ahn, J Kim, S Kim, B Shim GLOBECOM 2023-2023 IEEE Global Communications Conference, 1513-1518, 2023 | 5 | 2023 |
| D-TLoc: Deep learning-aided hybrid tdoa/aoa-based localization J Son, I Keum, Y Ahn, B Shim 2022 IEEE VTS Asia Pacific Wireless Communications Symposium (APWCS), 47-50, 2022 | 5 | 2022 |
| Role of Sensing and Computer Vision in 6G Wireless Communications S Kim, J Moon, J Kim, Y Ahn, D Kim, S Kim, K Shim, B Shim arXiv preprint arXiv:2405.03945, 2024 | 3 | 2024 |
| Sensing and Computer Vision-Aided Mobility Management for 6G Millimeter and Terahertz Communication Systems Y Ahn, J Kim, S Kim, S Kim, B Shim IEEE Transactions on Communications, 2024 | 3 | 2024 |
| Computer vision-aided beamforming for 6G wireless communications: Dataset and training perspective S Kim, Y Ahn, B Shim ICC 2024-IEEE International Conference on Communications, 672-677, 2024 | 1 | 2024 |
| Toward deep learning-based wireless communication systems: Design perspective W Kim, Y Ahn, J Kim, B Shim IEEE Wireless Communications, 0 | 1 | |
| VOMTC: Vision Objects for Millimeter and Terahertz Communications S Kim, Y Ahn, D Park, B Shim IEEE Transactions on Cognitive Communications and Networking, 2024 | | 2024 |
| Deep Learning-aided Parametric Sparse Channel Estimation for Terahertz Massive MIMO Systems J Kim, Y Ahn, S Kim, B Shim IEEE Transactions on Cognitive Communications and Networking, 2024 | | 2024 |
| Active User Detection and Channel Estimation Method and Device, Using Deep Neural Network B Shim, AHN Yongjun US Patent App. 18/038,357, 2023 | | 2023 |
| Deep Learning-based Localization Using Spatial Information in the NLoS Scenarios Y Ahn, I Keum, J Son, B Shim 2023 14th International Conference on Information and Communication …, 2023 | | 2023 |
Byonghyo ShimProfessor, Department of Electrical and Computer Engineering, Seoul National UniversityEmail verificata su snu.ac.kr
