Learning Radio Environments by Differentiable Ray Tracing

no code implementations • 30 Nov 2023 • Jakob Hoydis, Fayçal Aït Aoudia, Sebastian Cammerer, Florian Euchner, Merlin Nimier-David, Stephan ten Brink, Alexander Keller

Ray tracing (RT) is instrumental in 6G research in order to generate spatially-consistent and environment-specific channel impulse responses (CIRs).

Sionna RT: Differentiable Ray Tracing for Radio Propagation Modeling

1 code implementation • 20 Mar 2023 • Jakob Hoydis, Fayçal Aït Aoudia, Sebastian Cammerer, Merlin Nimier-David, Nikolaus Binder, Guillermo Marcus, Alexander Keller

Sionna is a GPU-accelerated open-source library for link-level simulations based on TensorFlow.

Graph Neural Networks for Channel Decoding

2 code implementations • 29 Jul 2022 • Sebastian Cammerer, Jakob Hoydis, Fayçal Aït Aoudia, Alexander Keller

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 coding schemes, such as low-density parity-check (LDPC) and BCH codes.

Decoder Graph Neural Network

Deep Learning-Based Synchronization for Uplink NB-IoT

1 code implementation • 22 May 2022 • Fayçal Aït Aoudia, Jakob Hoydis, Sebastian Cammerer, Matthijs Van Keirsbilck, Alexander Keller

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-access channel (NPRACH) of narrowband internet of things (NB-IoT).

Benchmarking Deep Learning