In this paper, we present a learning scheme for Joint Source-Channel Coding (JSCC) over
analog independent additive noise channels. We formulate the learning problem by …

We consider the design of low-delay joint source-channel coding (JSCC) schemes for the
transmission of discrete-time analog sources over noisy channels based on deep neural …

The introduction of 5G with excessively high speeds and ever-advancing cellular device
capabilities has increased the demand for high data rate wireless multimedia …

We consider the design of neural network based joint source channel coding (JSCC)
schemes for transmitting an independent and identically distributed (iid) Gaussian source …

Joint source-channel coding (JSCC) has achieved great success due to the introduction of
deep learning (DL). Compared to traditional separate source-channel coding (SSCC) …

We study deep joint source-channel coding (JSCC) in a distributed dual-view scenario
where the sources are correlated images and the channels are independent. The …

In this paper, we introduce a framework for Joint Source-Channel Coding of distributed
Gaussian sources over a multiple access AWGN channel. Although there are prior works …

We revisit the joint source-channel coding (JSCC) problem of transmitting correlated
sources over the additive white Gaussian noise channel using deep learning methods …

In this paper, we study Joint Source-Channel Coding (JSCC) for distributed analog
functional compression over both Gaussian Multiple Access Channel (MAC) and AWGN …

In recent years, applying Deep Learning (DL) techniques has emerged as a common
practice in the communication system, demonstrating promising results. The present paper …