| A tutorial on ultrareliable and low-latency communications in 6G: Integrating domain knowledge into deep learning C She, C Sun, Z Gu, Y Li, C Yang, HV Poor, B Vucetic Proceedings of the IEEE 109 (3), 204-246, 2021 | 365 | 2021 |
| Optimizing resource allocation in the short blocklength regime for ultra-reliable and low-latency communications C Sun, C She, C Yang, TQS Quek, Y Li, B Vucetic IEEE Transactions on Wireless Communications 18 (1), 402-415, 2018 | 241 | 2018 |
| Learning to optimize with unsupervised learning: Training deep neural networks for URLLC C Sun, C Yang 2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile …, 2019 | 51 | 2019 |
| Energy-efficient resource allocation for ultra-reliable and low-latency communications C Sun, C She, C Yang GLOBECOM 2017-2017 IEEE Global Communications Conference, 1-6, 2017 | 49 | 2017 |
| Optimizing wireless systems using unsupervised and reinforced-unsupervised deep learning D Liu, C Sun, C Yang, L Hanzo ieee network 34 (4), 270-277, 2020 | 44 | 2020 |
| Unsupervised deep learning for ultra-reliable and low-latency communications C Sun, C Yang 2019 IEEE Global Communications Conference (GLOBECOM), 1-6, 2019 | 18 | 2019 |
| Unsupervised deep learning for optimizing wireless systems with instantaneous and statistic constraints C Sun, C She, C Yang Ultra‐Reliable and Low‐Latency Communications (URLLC) Theory and Practice …, 2023 | 17 | 2023 |
| Exploiting multi-user diversity for ultra-reliable and low-latency communications C Sun, C She, C Yang 2017 IEEE Globecom Workshops (GC Wkshps), 1-6, 2017 | 16 | 2017 |
| Improving learning efficiency for wireless resource allocation with symmetric prior C Sun, J Wu, C Yang IEEE Wireless Communications 29 (2), 162-168, 2022 | 13 | 2022 |
| Model-free unsupervised learning for optimization problems with constraints C Sun, D Liu, C Yang 2019 25th Asia-Pacific Conference on Communications (APCC), 392-397, 2019 | 13 | 2019 |
| A tutorial of ultra-reliable and low-latency communications in 6g: Integrating theoretical knowledge into deep learning C She, C Sun, Z Gu, Y Li, C Yang, HV Poor, B Vucetic arXiv preprint arXiv:2009.06010, 2009 | 7 | 2009 |
| On the size generalizibility of graph neural networks for learning resource allocation J Wu, C Sun, C Yang Science China Information Sciences 67 (4), 142301, 2024 | 5 | 2024 |
| Resource allocation in URLLC with online learning for mobile users J Zhang, C Sun, C Yang 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), 1-5, 2021 | 5 | 2021 |
| Retransmission policy with frequency hopping for ultra-reliable and low-latency communications C Sun, C She, C Yang 2018 IEEE International Conference on Communications (ICC), 1-6, 2018 | 5 | 2018 |
| Probabilistic Constrained Optimization for Predictive Video Streaming by Deep Learning M Yin, C Sun, C Yang, S Han IEEE Transactions on Communications 71 (2), 823-836, 2022 | 4 | 2022 |
| Proactive optimization with machine learning: Femto-caching with future content popularity J Wu, C Sun, C Yang arXiv preprint arXiv:1910.13446, 2019 | 2 | 2019 |
| Resource allocation for URLLC with parameter generation network J Wu, C Sun, C Yang Journal of Communications and Information Networks 8 (4), 319-328, 2023 | 1 | 2023 |
| Optimizing Ultra-Reliable and Low-Latency Communication Systems with Unsupervised Learning C Sun, C She, C Yang arXiv preprint arXiv:2006.01641, 2020 | 1 | 2020 |
| Reducing sample complexity of deep learning with symmetric prior of wireless tasks C Sun, J Wu, C Yang arXiv preprint arXiv:2005.08510, 2020 | 1 | 2020 |
| Data representation for deep learning with prior knowledge of symmetric wireless tasks C Sun, J Wu, C Yang arXiv preprint arXiv:2005.08510, 2020 | 1 | 2020 |
