4 papers
Conjugate Equivariant Neural Network for Precoder Learning
Shiyong Chen, Mingyu Deng, Shengqian Han
Exploiting mathematical properties of wireless policies in deep neural network (DNN) design can improve learning performance and generalizability while reducing training complexity…
Association-Aware GNN for Precoder Learning in Cell-Free Systems
Mingyu Deng, Shengqian Han
Deep learning has been widely recognized as a promising approach for optimizing multi-user multi-antenna precoders in traditional cellular systems. However, a critical distinction…
Precoder Learning for Weighted Sum Rate Maximization
Mingyu Deng, Shengqian Han
Weighted sum rate maximization (WSRM) for precoder optimization effectively balances performance and fairness among users. Recent studies have demonstrated the potential of deep le…
On the adaptive deterministic block coordinate descent methods with momentum for solving large linear least-squares problems
Long-Ze Tan, Ming-Yu Deng, Jia-Li Qiu +1
In this work, we first present an adaptive deterministic block coordinate descent method with momentum (mADBCD) to solve the linear least-squares problem, which is based on Polyak'…