10 papers
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…
Learning Wideband User Scheduling and Hybrid Precoding with Graph Neural Networks
Shengjie Liu, Chenyang Yang, Shengqian Han
User scheduling and hybrid precoding in wideband multi-antenna systems have never been learned jointly due to the challenges arising from the massive user combinations on resource…
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…
Optimizing QoE-Privacy Tradeoff for Proactive VR Streaming
Xing Wei, Shengqian Han, Chenyang Yang +1
Proactive virtual reality (VR) streaming requires users to upload viewpoint-related information, raising significant privacy concerns. Existing strategies preserve privacy by intro…
Precoder Learning by Leveraging Unitary Equivariance Property
Yilun Ge, Shuyao Liao, Shengqian Han +1
Incorporating mathematical properties of a wireless policy to be learned into the design of deep neural networks (DNNs) is effective for enhancing learning efficiency. Multi-user p…
Quantization Design for Deep Learning-Based CSI Feedback
Manru Yin, Shengqian Han, Chenyang Yang
Deep learning-based autoencoders have been employed to compress and reconstruct channel state information (CSI) in frequency-division duplex systems. Practical implementations requ…