4 papers
Selective Depthwise Separable Convolution for Lightweight Joint Source-Channel Coding in Wireless Image Transmission
Ming Ye, Kui Cai, Cunhua Pan +3
Depthwise separable convolutional (DSConv) layers have been successfully applied to deep learning (DL)-based joint source-channel coding (JSCC) schemes to reduce computational comp…
U-Net-Based Generative Joint Source-Channel Coding for Wireless Image Transmission
Ming Ye, Kui Cai, Cunhua Pan +3
Deep learning (DL)-based joint source-channel coding (JSCC) methods have achieved remarkable success in wireless image transmission. However, these methods either focus on conventi…
On the Sequence Reconstruction Problem for the Single-Deletion Two-Substitution Channel
Wentu Song, Kui Cai, Tony Q. S. Quek
The Levenshtein sequence reconstruction problem studies the reconstruction of a transmitted sequence from multiple erroneous copies of it. A fundamental question in this field is t…
Sequence Reconstruction for the Single-Deletion Single-Substitution Channel
Wentu Song, Kui Cai, Tony Q. S. Quek
The central problem in sequence reconstruction is to find the minimum number of distinct channel outputs required to uniquely reconstruct the transmitted sequence. According to Lev…