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 …

This paper studies the zero-delay source-channel coding problem, and specifically the
problem of obtaining the vector transformations that optimally map between the m …

The problem of transmitting a parameter value over an additive white Gaussian noise
(AWGN) channel is considered, where, in addition to the transmitter and the receiver, there …

The research challenge of current wireless sensor networks (WSNs) is to design energy-
efficient, low-cost, high-accuracy, self-healing, and scalable systems for applications such as …

In this paper, delay-free, low complexity, joint source-channel coding (JSCC) for
transmission of two correlated Gaussian memoryless sources over a Gaussian Multiple …

We consider the problem of controlling an unstable linear plant with Gaussian disturbances
over an additive white Gaussian noise channel with an average transmit power constraint …

Analog Joint Source-Channel Coding (JSCC) is a communication strategy that does not
follow the separation principle of conventional digital systems but approaches the optimal …

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

With the development of the distributed learning and edge computing, servers must often
receive information from multiple terminal devices; thus, the importance of source-channel …