318 citations · 1k across the 84 of their papers we have counts for
7 papers · 2 filters
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…
High-SNR Comparison of Linear Precoding and DPC in RIS-Aided MIMO Broadcast Channels
Dominik Semmler, Benedikt Fesl, Michael Joham +1
We compare dirty paper coding (DPC) and linear precoding methods in a reconfigurable intelligent surface (RIS)- aided high-signal-to-noise ratio (SNR) scenario, where the channel b…
Enhancing Channel Estimation in Quantized Systems with a Generative Prior
Benedikt Fesl, Aziz Banna, Wolfgang Utschick
Channel estimation in quantized systems is challenging, particularly in low-resolution systems. In this work, we propose to leverage a Gaussian mixture model (GMM) as generative pr…
Channel-Adaptive Pilot Design for FDD-MIMO Systems Utilizing Gaussian Mixture Models
Nurettin Turan, Benedikt Fesl, Benedikt Böck +2
In this work, we propose to utilize Gaussian mixture models (GMMs) to design pilots for downlink (DL) channel estimation in frequency division duplex (FDD) systems. The GMM capture…
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…
Diffusion-based Generative Prior for Low-Complexity MIMO Channel Estimation
Benedikt Fesl, Michael Baur, Florian Strasser +2
This work proposes a novel channel estimator based on diffusion models (DMs), one of the currently top-rated generative models. Contrary to related works utilizing generative prior…
Wireless Channel Prediction via Gaussian Mixture Models
Nurettin Turan, Benedikt Böck, Kai Jie Chan +5
In this work, we utilize a Gaussian mixture model (GMM) to capture the underlying probability density function (PDF) of the channel trajectories of moving mobile terminals (MTs) wi…