6 papers
Statistical Precoder Design in Multi-User Systems via Graph Neural Networks and Generative Modeling
Nurettin Turan, Srikar Allaparapu, Donia Ben Amor +3
This letter proposes a graph neural network (GNN)-based framework for statistical precoder design that leverages model-based insights to compactly represent statistical knowledge,…
Robust Precoding for FDD MISO Systems via Minorization Maximization
Donia Ben Amor, Michael Joham, Wolfgang Utschick
In this work, we propose an approach to robust precoder design based on a minorization maximization technique that optimizes a surrogate function of the achievable spectral efficie…
Design of a Multi-User RIS-Aided System with Statistical Channel Knowledge
Sadaf Syed, Dominik Semmler, Donia Ben Amor +2
Reconfigurable intelligent surface (RIS) is a promising technology to enhance the spectral and energy efficiency in a wireless communication system. The design of the phase shifts…
An Efficient Rate Splitting Precoding Approach in Multi-User MISO FDD Systems
Donia Ben Amor, Michael Joham, Wolfgang Utschick
In this work, we develop an efficient precoding strategy for a multi-user multiple-input-single output (MU MISO) system operating in frequency-division-duplex (FDD) mode, where rat…
Design of a Single-User RIS-Aided MISO System Based on Statistical Channel Knowledge
Sadaf Syed, Dominik Semmler, Donia Ben Amor +2
Reconfigurable intelligent surface (RIS) is considered a prospective technology for beyond fifth-generation (5G) networks to improve the spectral and energy efficiency at a low cos…
Asymptotic Behavior of Zero-Forcing Precoding based on Imperfect Channel Knowledge for Massive MISO FDD Systems
Donia Ben Amor, Michael Joham, Wolfgang Utschick
In this work, we study the asymptotic behavior of the zero-forcing precoder based on the least squares (LS) and the linear minimum mean-square error (LMMSE) channel estimates for t…