Recently, deep learned enabled end-to-end communication systems have been developed
to merge all physical layer blocks in the traditional communication systems, which make joint …

Data-driven machine learning (ML) is promoted as one potential technology to be used in
next-generation wireless systems. This led to a large body of research work that applies ML …

Learning to optimize (L2O) is an emerging approach that leverages machine learning to
develop optimization methods, aiming at reducing the laborious iterations of hand …

Given the unprecedented availability of data and computing resources, there is widespread
renewed interest in applying data-driven machine learning methods to problems for which …

Reliable digital communication is a primary workhorse of the modern information age. The
disciplines of communication, coding, and information theories drive the innovation by …

We consider wireless transmission of images in the presence of channel output feedback.
From a Shannon theoretic perspective feedback does not improve the asymptotic end-to …

Designing codes that combat the noise in a communication medium has remained a
significant area of research in information theory as well as wireless communications …

For reliable transmission across a noisy communication channel, classical results from
information theory show that it is asymptotically optimal to separate out the source and …

In this paper, we investigate an artificial-intelligence (AI) driven approach to design error
correction codes (ECC). Classic error-correction code design based upon coding-theoretic …

Designing channel codes under low-latency constraints is one of the most demanding
requirements in 5G standards. However, a sharp characterization of the performance of …