50 citations · 55 across the 11 of their papers we have counts for
12 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…
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…
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…
Recursive GNNs for Learning Precoding Policies with Size-Generalizability
Jia Guo, Chenyang Yang
Graph neural networks (GNNs) have been shown promising in optimizing power allocation and link scheduling with good size generalizability and low training complexity. These merits…
Learning Resource Allocation Policy: Vertex-GNN or Edge-GNN?
Yao Peng, Jia Guo, Chenyang Yang
Graph neural networks (GNNs) update the hidden representations of vertices (called Vertex-GNNs) or hidden representations of edges (called Edge-GNNs) by processing and pooling the…
Multidimensional Graph Neural Networks for Wireless Communications
Shengjie Liu, Jia Guo, Chenyang Yang
Graph neural networks (GNNs) have been shown promising in improving the efficiency of learning communication policies by leveraging their permutation properties. Nonetheless, exist…
A Model-based GNN for Learning Precoding
Jia Guo, Chenyang Yang
Learning precoding policies with neural networks enables low complexity online implementation, robustness to channel impairments, and joint optimization with channel acquisition. H…
Understanding the Performance of Learning Precoding Policy with GNN and CNNs
Baichuan Zhao, Jia Guo, Chenyang Yang
Learning-based precoding has been shown able to be implemented in real-time, jointly optimized with channel acquisition, and robust to imperfect channels. Yet previous works rarely…
Learning Power Control for Cellular Systems with Heterogeneous Graph Neural Network
Jia Guo, Chenyang Yang
Optimizing power control in multi-cell cellular networks with deep learning enables such a non-convex problem to be implemented in real-time. When channels are time-varying, the de…
Constructing Deep Neural Networks with a Priori Knowledge of Wireless Tasks
Jia Guo, Chenyang Yang
Deep neural networks (DNNs) have been employed for designing wireless systems in many aspects, say transceiver design, resource optimization, and information prediction. Existing w…
Structure of Deep Neural Networks with a Priori Information in Wireless Tasks
Jia Guo, Chenyang Yang
Deep neural networks (DNNs) have been employed for designing wireless networks in many aspects, such as transceiver optimization, resource allocation, and information prediction. E…
Exploiting Residual Resources to Support High Throughput with Resource Allocation
Jia Guo, Chuting Yao, Chenyang Yang +1
Residual radio resources are abundant in wireless networks due to dynamic traffic load, which can be exploited to support high throughput for serving non-real-time (NRT) traffic. I…