activity
20062023
most citedLearning to Branch: Accelerating Resource Allocation in Wireless Networks

59 citations · 199 across the 37 of their papers we have counts for

collaborators

38 papers

eess.SP2023★ 1 cited

Alleviating Distortion Accumulation in Multi-Hop Semantic Communication

Guangyi Zhang, Qiyu Hu, Yunlong Cai +1

Recently, semantic communication has been investigated to boost the performance of end-to-end image transmission systems. However, existing semantic approaches are generally based…

eess.SP2023

SCAN: Semantic Communication with Adaptive Channel Feedback

Guangyi Zhang, Qiyu Hu, Yunlong Cai +1

In existing semantic communication systems for image transmission, some images are generally reconstructed with considerably low quality. As a result, the reliable transmission of…

eess.SP2023

Meta-Gating Framework for Fast and Continuous Resource Optimization in Dynamic Wireless Environments

Qiushuo Hou, Mengyuan Lee, Guanding Yu +1

With the great success of deep learning (DL) in image classification, speech recognition, and other fields, more and more studies have applied various neural networks (NNs) to wire…

eess.SP2023

Rate-Adaptive Coding Mechanism for Semantic Communications With Multi-Modal Data

Yangshuo He, Guanding Yu, Yunlong Cai

Recently, the ever-increasing demand for bandwidth in multi-modal communication systems requires a paradigm shift. Powered by deep learning, semantic communications are applied to…

eess.SP2023★ 2 cited

Deep-Unfolding for Next-Generation Transceivers

Qiyu Hu, Yunlong Cai, Guangyi Zhang +2

The stringent performance requirements of future wireless networks, such as ultra-high data rates, extremely high reliability and low latency, are spurring worldwide studies on def…

eess.SP2023

FAST: Feature Arrangement for Semantic Transmission

Kequan Zhou, Guangyi Zhang, Yunlong Cai +2

Although existing semantic communication systems have achieved great success, they have not considered that the channel is time-varying wherein deep fading occurs occasionally. Mor…