5 papers
DSRDM: Digital Signal Recovery Diffusion Model for Semantic Communications
Zhigang Yan, Dong Li
Diffusion model (DM) has recently appeared as a promising type of generative model for AI-generated content, which has been widely used for image reconstruction, generation, and ch…
Semantic Communications for Digital Signals via Carrier Images
Zhigang Yan, Dong Li
Most of current semantic communication (SemCom) frameworks focus on the image transmission, which, however, do not address the problem on how to deliver digital signals without any…
Adaptive Decentralized Federated Learning in Energy and Latency Constrained Wireless Networks
Zhigang Yan, Dong Li
In Federated Learning (FL), with parameter aggregated by a central node, the communication overhead is a substantial concern. To circumvent this limitation and alleviate the single…
Performance Analysis for Resource Constrained Decentralized Federated Learning Over Wireless Networks
Zhigang Yan, Dong Li
Federated learning (FL) can lead to significant communication overhead and reliance on a central server. To address these challenges, decentralized federated learning (DFL) has bee…
Revisiting Communication-Efficient Federated Learning with Balanced Global and Local Updates
Zhigang Yan, Dong Li, Zhichao Zhang +1
In federated learning (FL), a number of devices train their local models and upload the corresponding parameters or gradients to the base station (BS) to update the global model wh…