5 citations · 11 across the 8 of their papers we have counts for
9 papers
Deep Learning Models for Physical Layer Communications
Nunzio A. Letizia
The increased availability of data and computing resources has enabled researchers to successfully adopt machine learning (ML) techniques and make significant contributions in seve…
Cooperative Channel Capacity Learning
Nunzio A. Letizia, Andrea M. Tonello, H. Vincent Poor
In this paper, the problem of determining the capacity of a communication channel is formulated as a cooperative game, between a generator and a discriminator, that is solved via d…
Mutual Information Estimation via -Divergence and Data Derangements
Nunzio A. Letizia, Nicola Novello, Andrea M. Tonello
Estimating mutual information accurately is pivotal across diverse applications, from machine learning to communications and biology, enabling us to gain insights into the inner me…
Copula Density Neural Estimation
Nunzio A. Letizia, Nicola Novello, Andrea M. Tonello
Probability density estimation from observed data constitutes a central task in statistics. In this brief, we focus on the problem of estimating the copula density associated to an…
MIND: Maximum Mutual Information Based Neural Decoder
Andrea M. Tonello, Nunzio A. Letizia
We are assisting at a growing interest in the development of learning architectures with application to digital communication systems. Herein, we consider the detection/decoding pr…
Discriminative Mutual Information Estimation for the Design of Channel Capacity Driven Autoencoders
Nunzio A. Letizia, Andrea M. Tonello
The development of optimal and efficient machine learning-based communication systems is likely to be a key enabler of beyond 5G communication technologies. In this direction, phys…
Discriminative Mutual Information Estimators for Channel Capacity Learning
Nunzio A. Letizia, Andrea M. Tonello
Channel capacity plays a crucial role in the development of modern communication systems as it represents the maximum rate at which information can be reliably transmitted over a c…
Capacity-Approaching Autoencoders for Communications
Nunzio A. Letizia, Andrea M. Tonello
The autoencoder concept has fostered the reinterpretation and the design of modern communication systems. It consists of an encoder, a channel, and a decoder block which modify the…
Machine Learning Tips and Tricks for Power Line Communications
Andrea M. Tonello, Nunzio A. Letizia, Davide Righini +1
A great deal of attention has been recently given to Machine Learning (ML) techniques in many different application fields. This paper provides a vision of what ML can do in Power…