102 citations · 194 across the 25 of their papers we have counts for
4 papers · 1 filter
Forecasting Self-Similar User Traffic Demand Using Transformers in LEO Satellite Networks
Yekta Demirci, Guillaume Mantelet, Stéphane Martel +2
In this paper, we propose the use of a transformer-based model to address the need for forecasting user traffic demand in the next generation Low Earth Orbit (LEO) satellite networ…
A Foundation Model for Massive MIMO Precoding with an Adaptive per-User Rate-Power Tradeoff
Jérôme Emery, Ali Hasanzadeh Karkan, Jean-François Frigon +1
Deep learning (DL) has emerged as a solution for precoding in massive multiple-input multiple-output (mMIMO) systems due to its capacity to learn the characteristics of the propaga…
Compression of Site-Specific Deep Neural Networks for Massive MIMO Precoding
Ghazal Kasalaee, Ali Hasanzadeh Karkan, Jean-François Frigon +1
The deployment of deep learning (DL) models for precoding in massive multiple-input multiple-output (mMIMO) systems is often constrained by high computational demands and energy co…
A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites
Ali Hasanzadeh Karkan, Ahmed Ibrahim, Jean-François Frigon +1
Massive multiple-input multiple-output (mMIMO) technology has transformed wireless communication by enhancing spectral efficiency and network capacity. This paper proposes a novel…