[TuA3] Mobile x-Haul

3:30 PM - 3:45 PM JST(6:30 AM - 6:45 AM UTC)

[TuA3-6] Hybrid Linear-Convolutional Neural Network for Timing Error Mitigation towards 6G Deterministic Communications

Haotian Li¹, ○Hongxing Li¹, Lele Yang¹, Qianhan Gao¹, Xiangqun Lu¹, Guochu Shou¹, Yihong Hu¹, Zhigang Guo¹ (1. Beijing University of Posts and Telecommunications (China))

Keywords:

precise timing,deep learning,time series analysis,6G,deterministic communications

We propose a timing error mitigation approach using hybrid linear-convolutional neural network towards 6G deterministic communications. Experiments demonstrate that the proposed method achieves a relative timing error of ±100 μs in wireless networks.