activity
20242026
most citedSC-CDM: Enhancing Quality of Image Semantic Communication with a Compact Diffusion Model

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.MA2026

Embodied Semantic Communication for Collective Autonomous Agents: A Tutorial on Representation, Wireless Delivery, and Closed-Loop Coordination

Yizheng Huang, Wensheng Lin, Lixin Li +3

As autonomous systems and embodied intelligence enter the dynamic physical world, multi-agent collaboration calls for a paradigm shift in communication design. However, existing co…

cs.AI2026

MA-HEAD-Net: Adaptive Rule-Guided Multi-Agent DRL for AoI Minimization in UAV-Assisted Emergency Networks

Yixin Zhang, Zhuohui Yao, Wenchi Cheng +1

In post-disaster scenarios, unmanned aerial vehicles (UAVs) are critical for establishing emergency communication networks. For time-critical rescue missions, information freshness…

cs.IR2025

Emergency Communication: OTFS-Based Semantic Transmission with Diffusion Noise Suppression

Kexin Zhang, Xin Zhang, Lixin Li +3

Due to their flexibility and dynamic coverage capabilities, Unmanned Aerial Vehicles (UAVs) have emerged as vital platforms for emergency communication in disaster-stricken areas.…

eess.IV2024★ 1 cited

SC-CDM: Enhancing Quality of Image Semantic Communication with a Compact Diffusion Model

Kexin Zhang, Lixin Li, Wensheng Lin +3

Semantic Communication (SC) is an emerging technology that has attracted much attention in the sixth-generation (6G) mobile communication systems. However, few literature has fully…

cs.NI2024

SAFE: Semantic Adaptive Feature Extraction with Rate Control for 6G Wireless Communications

Yuna Yan, Lixin Li, Xin Zhang +3

Most current Deep Learning-based Semantic Communication (DeepSC) systems are designed and trained exclusively for particular single-channel conditions, which restricts their adapta…

cs.LG2024

Semantic Successive Refinement: A Generative AI-aided Semantic Communication Framework

Kexin Zhang, Lixin Li, Wensheng Lin +4

Semantic Communication (SC) is an emerging technology aiming to surpass the Shannon limit. Traditional SC strategies often minimize signal distortion between the original and recon…

cs.AI2024

FSSC: Federated Learning of Transformer Neural Networks for Semantic Image Communication

Yuna Yan, Xin Zhang, Lixin Li +4

In this paper, we address the problem of image semantic communication in a multi-user deployment scenario and propose a federated learning (FL) strategy for a Swin Transformer-base…