Motivated by deep learning in wireless image transmissions, joint source-channel coding
(JSCC) techniques based on convolutional neural networks (CNNs) can successfully …

Semantic communication, when examined through the lens of joint source-channel coding
(JSCC), maps source messages directly into channel input symbols, where the measure of …

Wireless image transmission and estimation techniques have found a variety of applications
in 5G Internet of Things (IoT) under the finite block length transmissions. However, the …

Modern computationally-intensive applications often operate under time constraints,
necessitating acceleration methods and distribution of computational workloads across …

The implementation of joint source-channel coding (JSCC) schemes using deep learning
has accelerated the development of semantic communication research. Existing JSCC …

We propose a low complexity deep joint source channel coding (DJSCC) with adaptive rate
control model for wireless image transmission using Tensor-Train (TT) decomposition. TT is …

Semantic communication (SemCom) aims to achieve high fidelity information delivery under
low communication consumption by only guaranteeing semantic accuracy. Nevertheless …

With the introduction of the deep learning (DL), joint source and channel coding (JSCC) has
achieved great success and has been demonstrated to have better performance especially …

In this paper, we propose a puncturing-based joint source channel coding scheme with a
hierarchical down-sampling layer (PJSCC). The proposed hierarchical down-sampling layer …

Deep Joint Source-Channel Coding (JSCC) has gained increased attention, asserting its
significance in the communication field. However, existing Deep JSCC techniques struggle …