5 papers
CARNet: Channel-Adaptive Receiver Network for Robust NextG Communications
Chao Jiang, Zhuo Xu, Yongli Yan
Neural receivers have been recognized as a promising paradigm for the next-generation (NextG) communications. However, due to the reliance on a static network optimized for specifi…
A General DoF and Pattern Analyzing Scheme for Electromagnetic Information Theory
Zhongzhichao Wan, Jieao Zhu, Yongli Yan +1
Electromagnetic information theory (EIT) is one of the emerging topics for 6G communication due to its potential to reveal the performance limit of wireless communication systems.…
Decoding for Punctured Convolutional and Turbo Codes: A Deep Learning Solution for Protocols Compliance
Yongli Yan, Linglong Dai
Neural network-based decoding methods show promise in enhancing error correction performance but face challenges with punctured codes. In particular, existing methods struggle to a…
Unified Error Correction Code Transformer with Low Complexity
Yongli Yan, Jieao Zhu, Tianyue Zheng +3
Channel coding is vital for reliable sixth-generation (6G) data transmission, employing diverse error correction codes for various application scenarios. Traditional decoders requi…
Coded Beam Training
Tianyue Zheng, Jieao Zhu, Qiumo Yu +2
In extremely large-scale multiple input multiple output (XL-MIMO) systems for future sixth-generation (6G) communications, codebook-based beam training stands out as a promising te…