SNR-Independent Joint Source-Channel Coding for wireless image transmission

Understand

Significant progress has been made in wireless Joint Source-Channel Coding (JSCC) using deep learning techniques.

• The latest DL-based image JSCC methods have demonstrated exceptional performance during transmission, while also avoiding cliff effects.
• However, current channel adaptive JSCC methods rely on channel SNR information, which can lead to performance degradation in practical applications due to channel mismatch effects.
• This paper proposes a novel approach for image transmission, called SNR Independent Joint Source-Channel Coding (SIJSCC), which utilizes Deep Learning techniques to achieve exceptional performance across various signal-to-noise ratio (SNR) levels without SNR estimating.