Paper accepted in IEEE Transactions on Information Theory

Our paper “Typical Error Exponents: A Dual Domain Derivation” has been just published on the journal IEEE Transactions on Information Theory What is it about? Here is a sketch: The reliable transmission of information is possible thanks to “channel codes”. For this reason, they are widely used in digital applications like mobile communications, server farms, …

New paper accepted at the IEEE Information Theory Workshop 2022

I am happy to announce that our paper “Convergence in Distribution of the Error Exponent of Random Codes at Zero Rate” has been accepted at the Information Theory Workshop (ITW) 2022 to be held in Mumbai (India) in November. The paper is a joint work with Lan V. Truong, Josep Font-Segura and Albert Guillén i …

New paper accepted at IEEE ISIT 2022

Our new paper “Typical Random Coding Exponent for Finite-State Channels” has been presented at the 2022 IEEE International Symposium of Information Theory that was held at the Aalto University in Finland in June.The paper is a joint work with Albert Guillén i Fàbregas and Joep Font Segura. This work was funded by: Beatriu de Pinós …

New paper presented at IEEE ISIT 2021

Channel codes enable reliable transmission of information. For this reason, they are widely used in applications like mobile communication networks, server farms, fiber-optic communication, DVD, Blue Rays, deep space communication and many more. Now, how easy is it to find a “good” channel code? It was known that, under some conditions, if you pick at …

Special Issue “Information Theory for Delay-Constrained Data Compression and Communication”

As Guest Editor, I am happy to announce that the new Entropy Special Issue “Information Theory for Delay-Constrained Data Compression and Communication” is open for submissions! More information here The issue deals with fundamental theoretical aspects that are pivotal in the contexts of #IoT, #5G, real-time video streaming from #UAVs and robotic communications These are topics I am …