Adaptive Wireless Image Semantic Transmission: Design, Simulation, and Prototype Validation

TL;DR

This paper introduces ASCViT-JSCC, an adaptive wireless image transmission scheme that prioritizes important image regions using vision transformers, incorporates real-world prototype testing, and improves reconstruction quality in challenging wireless channels.

Contribution

It presents a novel adaptive semantic transmission scheme with vision transformer-based JSCC, object prioritization, and prototype validation for wireless image communication.

Findings

Enhanced image quality in challenging channels.

Effective prioritization of important image regions.

Successful real-world prototype validation.

Abstract

The rapid development of artificial intelligence has significantly advanced semantic communications, particularly in wireless image transmission. However, most existing approaches struggle to precisely distinguish and prioritize image content, and they do not sufficiently incorporate semantic priorities into system design. In this study, we propose an adaptive wireless image semantic transmission scheme called ASCViT-JSCC, which utilizes vision transformer-based joint source-channel coding (JSCC). This scheme prioritizes different image regions based on their importance, identified through object and feature point detection. Unimportant background sections are masked, enabling them to be recovered at the receiver, while the freed resources are allocated to enhance object protection via the JSCC network. We also integrate quantization modules to enable compatibility with quadrature amplitude modulation, commonly used in modern wireless communications. To address frequency-selective fading channels, we introduce CSIPA-Net, which allocates power based on channel information, further improving performance. Notably, we conduct over-the-air testing on a prototype platform composed of a software-defined radio and embedded graphics processing unit systems, validating our methods. Both simulations and real-world measurements demonstrate that ASCViT-JSCC effectively prioritizes object protection according to channel conditions, significantly enhancing image reconstruction quality, especially in challenging channel environments.