105 citations · 109 across the 13 of their papers we have counts for
5 papers · 1 filter
Graph Neural Networks for Channel Decoding
Sebastian Cammerer, Jakob Hoydis, Fayçal Aït Aoudia +1
In this work, we propose a fully differentiable graph neural network (GNN)-based architecture for channel decoding and showcase a competitive decoding performance for various codin…
GPU-Accelerated Machine Learning in Non-Orthogonal Multiple Access
Daniel Schäufele, Guillermo Marcus, Nikolaus Binder +3
Non-orthogonal multiple access (NOMA) is an interesting technology that enables massive connectivity as required in future 5G and 6G networks. While purely linear processing alread…
Deep Learning-Based Synchronization for Uplink NB-IoT
Fayçal Aït Aoudia, Jakob Hoydis, Sebastian Cammerer +2
We propose a neural network (NN)-based algorithm for device detection and time of arrival (ToA) and carrier frequency offset (CFO) estimation for the narrowband physical random-acc…
Sionna: An Open-Source Library for Next-Generation Physical Layer Research
Jakob Hoydis, Sebastian Cammerer, Fayçal Ait Aoudia +4
Sionna is a GPU-accelerated open-source library for link-level simulations based on TensorFlow. It enables the rapid prototyping of complex communication system architectures and p…
GPU-accelerated partially linear multiuser detection for 5G and beyond URLLC systems
Matthias Mehlhose, Guillermo Marcus, Daniel Schäufele +6
In this feasibility study, we have implemented a recently proposed partially linear multiuser detection algorithm in reproducing kernel Hilbert spaces (RKHSs) on a GPU-accelerated…