3 papers
eess.SP2026
Cross-System Neural Precoder: Exploiting Structural Consistency for Fast Adaptation
Jia Guo, Chenyang Yang
Adapting learning-based precoding across different system configurations is challenging due to multiple types of variables and constraints. While large-scale neural networks have b…
eess.SP2025
When Attention is Beneficial for Learning Wireless Resource Allocation Efficiently?
Jia Guo, Chenyang Yang
Owing to the use of attention mechanism to leverage the dependency across tokens, Transformers are efficient for natural language processing. By harnessing permutation properties b…
eess.SP2025
Learning Precoding in Multi-user Multi-antenna Systems: Transformer or Graph Transformer?
Yuxuan Duan, Jia Guo, Chenyang Yang
Transformers have been designed for channel acquisition tasks such as channel prediction and other tasks such as precoding, while graph neural networks (GNNs) have been demonstrate…