Recursive GNNs for Learning Precoding Policies with Size-Generalizability
J Guo, C Yang - arXiv preprint arXiv:2402.18332, 2024 - arxiv.org
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 …
and link scheduling with good size generalizability and low training complexity. These merits …
Learning Adaptive Beamforming Policy for Different Optimization Problems
Deep learning has been widely used for wireless optimization. In most existing studies, a
deep neural network (DNN) is trained for a particular optimization problem and then tested …
deep neural network (DNN) is trained for a particular optimization problem and then tested …