2025
Digital Semantic Communication with Neural Image Compression
L. V. Nguyen, T. T. Nguyen, O. A. Dobre, T. Q. Duong
IEEE International Conference on Computer Communications (INFOCOM) 2025 Conference
In this work, we introduce a neural image compression-enabled semantic communication system to enhance the efficiency of digital image transmission, named NCSC. By employing an accurate and adaptable entropy model, NCSC obtains the efficiently compressed bitstreams, which are compatible with digital communication systems. Incorporating with the well-established digital components, our system trained on the MS-SSIM metric can achieve a significant bandwidth compression ratio of 0.002 at low SNR, reducing remarkably transmission overhead.
Digital Semantic Communication with Neural Image Compression
L. V. Nguyen, T. T. Nguyen, O. A. Dobre, T. Q. Duong
IEEE International Conference on Computer Communications (INFOCOM) 2025 Conference
In this work, we introduce a neural image compression-enabled semantic communication system to enhance the efficiency of digital image transmission, named NCSC. By employing an accurate and adaptable entropy model, NCSC obtains the efficiently compressed bitstreams, which are compatible with digital communication systems. Incorporating with the well-established digital components, our system trained on the MS-SSIM metric can achieve a significant bandwidth compression ratio of 0.002 at low SNR, reducing remarkably transmission overhead.
2024
Leveraging Stable Diffusion with Context-Aware Prompts for Semantic Communication
L. V. Nguyen, T. T. Nguyen, O. A. Dobre, T. Q. Duong
IEEE 21st International Conference on Mobile Ad-Hoc and Smart Systems (MASS) 2024 Conference
In this study, we present a novel Stable Diffusion-based semantic communication (SDSC) framework that demonstrates high performance, characterized by an elevated bandwidth compression ratio (BCR) and robust noise tolerance achieved by diffusion mechanism integrating supplementary prompts. This scheme significantly enhances the system's ability to preserve data integrity and meaning in noisy environments. By introducing additional context-aware prompts during transmission, we improve the accuracy of received information and mitigate the adverse effects of interference and noise.
Leveraging Stable Diffusion with Context-Aware Prompts for Semantic Communication
L. V. Nguyen, T. T. Nguyen, O. A. Dobre, T. Q. Duong
IEEE 21st International Conference on Mobile Ad-Hoc and Smart Systems (MASS) 2024 Conference
In this study, we present a novel Stable Diffusion-based semantic communication (SDSC) framework that demonstrates high performance, characterized by an elevated bandwidth compression ratio (BCR) and robust noise tolerance achieved by diffusion mechanism integrating supplementary prompts. This scheme significantly enhances the system's ability to preserve data integrity and meaning in noisy environments. By introducing additional context-aware prompts during transmission, we improve the accuracy of received information and mitigate the adverse effects of interference and noise.