3 citations · 3 across the 8 of their papers we have counts for
10 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…
Joint Optimization of Uplink and Downlink Resources under QoS Constraints of AR
Shiyong Chen, Shengqian Han
This paper studies joint uplink (UL) and downlink (DL) resource optimization for interactive augmented reality (AR) services, where the live video captured by an AR device is uploa…
Learning-Based Beamforming for Energy Efficiency of Continuous Aperture Array Systems
Shiyong Chen, Jia Guo, Shengqian Han
This paper jointly optimizes the base-station (BS) continuous aperture array (CAPA) dimensions and beamforming functions to maximize energy efficiency (EE) of the downlink multiuse…
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…
Implicit Neural Representation for Multiuser Continuous Aperture Array Beamforming
Shiyong Chen, Shengqian Han, Jia Guo
This paper studies the optimization of beamforming functions for multiuser multi-continuous aperture array (CAPA) systems, where both the base station and the users are equipped wi…
Functional WMMSE Algorithm for Multiuser Continuous Aperture Array Systems
Shiyong Chen, Shengqian Han, Jia Guo
In this paper, we develop a functional weighted minimum mean-squared error (WMMSE) algorithm for downlink beamforming in multiuser continuous aperture array (CAPA) systems where bo…
Implicit Neural Representation of Beamforming for Continuous Aperture Array Systems
Shiyong Chen, Jia Guo, Shengqian Han
In this paper, a learning-based approach is proposed for optimizing downlink beamforming in multiple-input multiple-output (MIMO) systems that employ continuous aperture arrays (CA…
Learning-based Multiuser Beamforming for Holographic MIMO~Systems
Shiyong Chen, Shengqian Han
Holographic multiple-input multiple-output (HMIMO) can improve spectral efficiency (SE) with low hardware cost, but conventional alternating optimization (AO) methods for jointly o…
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…
Learn to Optimize Resource Allocation under QoS Constraint of AR
Shiyong Chen, Yuwei Dai, Shengqian Han
This paper studies the uplink and downlink power allocation for interactive augmented reality (AR) services, where the live video captured by an AR device is uploaded to the networ…