|
深度学习在无线传输物理层的应用与实现
|
Abstract:
[1] | Yadav, P., McCann, J.A. and Pereira, T. (2017) Self-Synchronization in Duty-Cycled Internet of Things (IoT) Ap-plications. IEEE Internet of Things Journal, 4, 2058-2069. |
[2] | Nachmani, E., Be’ery, Y. and Burshtein, D. (2016) Learning to Decode Linear Codes Using Deep Learning. 2016 IEEE 54th Annual Allerton Conference on Commu-nication, Control, and Computing, Monticello, 27-30 September 2016, 341-346. https://doi.org/10.1109/ALLERTON.2016.7852251 |
[3] | Nachmani, E., Marciano, E. and Burshtein, D. RNN Decoding of Linear Block Codes. arXiv:1702.07560. |
[4] | Gruber, T., Cammerer, S. and Hoydis, J. (2017) On Deep Learning-Based Channel Decoding. 2017 IEEE 51st Annual Conference on Information Sciences and Systems (CISS), Baltimore, 22-24 March 2017, 1-6. https://doi.org/10.1109/CISS.2017.7926071 |
[5] | Cammerer, S., Gruber, T. and Hoydis, J. (2017) Scaling Deep Learning-Based Decoding of Polar Codes via Partitioning. 2017 IEEE Global Communications Conference (GLOBECOM), Singapore, 4-8 December 2017, 1-6. https://doi.org/10.1109/GLOCOM.2017.8254811 |
[6] | Samuel, N., Diskin, T. and Wiesel, A. (2017) Deep MIMO Detection. 2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communi-cations (SPAWC), Sapporo, 3-6 July 2017, 1-5. https://doi.org/10.1109/SPAWC.2017.8227772 |
[7] | Farsad, N. and Goldsmith, A. Detection Algorithms for Communication Systems Using Deep Learning. arXiv:1705.08044. |
[8] | Ye, H., Li, G.Y. and Juang, B.H. (2018) Power of Deep Learning for Channel Estimation and Signal Detection in OFDM Systems. IEEE Wireless Commu-nications Letters, 7, 114-117. https://doi.org/10.1109/LWC.2017.2757490 |
[9] | Gao, X., Jin, S., Wen, C. and Li, G.Y. (2018) ComNet: Combination of Deep Learning and Expert Knowledge in OFDM Receivers. IEEE Com-munications Letters, 22, 2627-2630. https://doi.org/10.1109/LCOMM.2018.2877965 |