887 citations · 1.4k across the 37 of their papers we have counts for
55 papers
Ballistic transport and crystallographic control in altermagnetic quantum rings
Edilberto O. Silva
We study coherent two-terminal transport through a finite-width -wave altermagnetic quantum ring with nonmagnetic leads. A confined Aharonov--Bohm flux remains exactly per…
Autonomous Discovery of Wireless Communications Algorithms
Fayçal Aït Aoudia, Jakob Hoydis, Sebastian Cammerer +4
Large language model (LLM)-driven evolutionary search is an emerging algorithm-discovery paradigm that has already produced novel results in several scientific fields. Yet its appl…
The AI Telco Engineer: Toward Autonomous Discovery of Wireless Communications Algorithms
Fayçal Aït Aoudia, Jakob Hoydis, Sebastian Cammerer +3
Agentic AI is rapidly transforming the way research is conducted, from prototyping ideas to reproducing results found in the literature. In this paper, we explore the ability of ag…
SINR Estimation under Limited Feedback via Online Convex Optimization
Lorenzo Maggi, Boris Bonev, Reinhard Wiesmayr +2
We introduce a novel online convex optimization (OCO) framework to estimate the user's signal-to-interference-plus-noise ratio (SINR) from ACK/NACK feedback, channel quality indica…
Site-Specific Finetuning of Neural Receivers with Real-World 5G NR Measurements
Nuri Berke Baytekin, Reinhard Wiesmayr, Sebastian Cammerer +2
Finetuning wireless receivers to a specific deployment scenario can yield significant error-rate performance improvements without increasing processing complexity. However, site-sp…
Serial Polar Automorphism Ensemble Decoders for Physical Unclonable Functions
Marvin Rübenacke, Sebastian Cammerer, Michael Sullivan +1
Physical unclonable functions (PUFs) involve challenging practical applications of error-correcting codes (ECCs), requiring extremely low failure rates on the order of an…
SALAD: Self-Adaptive Link Adaptation
Reinhard Wiesmayr, Lorenzo Maggi, Sebastian Cammerer +3
Adapting the modulation and coding scheme (MCS) to the wireless link quality is critical for maximizing spectral efficiency while ensuring reliability. We propose SALAD (self-adapt…
Sionna Research Kit: A GPU-Accelerated Research Platform for AI-RAN
Sebastian Cammerer, Guillermo Marcus, Tobias Zirr +4
We introduce the NVIDIA Sionna Research Kit, a GPU-accelerated research platform for developing and testing AI/ML algorithms in 5G NR cellular networks. Powered by the NVIDIA Jetso…
Design of a Standard-Compliant Real-Time Neural Receiver for 5G NR
Reinhard Wiesmayr, Sebastian Cammerer, Fayçal Aït Aoudia +3
We detail the steps required to deploy a multi-user multiple-input multiple-output (MU-MIMO) neural receiver (NRX) in an actual cellular communication system. This raises several e…
Toward Low-latency Iterative Decoding of QLDPC Codes Under Circuit-Level Noise
Anqi Gong, Sebastian Cammerer, Joseph M. Renes
We introduce a sliding window decoder based on belief propagation (BP) with guided decimation for the purposes of decoding quantum low-density parity-check codes in the presence of…
A Neural Receiver for 5G NR Multi-user MIMO
Sebastian Cammerer, Fayçal Aït Aoudia, Jakob Hoydis +4
We introduce a neural network (NN)-based multiuser multiple-input multiple-output (MU-MIMO) receiver with 5G New Radio (5G NR) physical uplink shared channel (PUSCH) compatibility.…
Learning Radio Environments by Differentiable Ray Tracing
Jakob Hoydis, Fayçal Aït Aoudia, Sebastian Cammerer +4
Ray tracing (RT) is instrumental in 6G research in order to generate spatially-consistent and environment-specific channel impulse responses (CIRs). While acquiring accurate scene…
Graph Neural Networks for Enhanced Decoding of Quantum LDPC Codes
Anqi Gong, Sebastian Cammerer, Joseph M. Renes
In this work, we propose a fully differentiable iterative decoder for quantum low-density parity-check (LDPC) codes. The proposed algorithm is composed of classical belief propagat…
Sionna RT: Differentiable Ray Tracing for Radio Propagation Modeling
Jakob Hoydis, Fayçal Aït Aoudia, Sebastian Cammerer +4
Sionna is a GPU-accelerated open-source library for link-level simulations based on TensorFlow. Since release v0.14 it integrates a differentiable ray tracer (RT) for the simulatio…
Learning Joint Detection, Equalization and Decoding for Short-Packet Communications
Sebastian Dörner, Jannis Clausius, Sebastian Cammerer +1
We propose and practically demonstrate a joint detection and decoding scheme for short-packet wireless communications in scenarios that require to first detect the presence of a me…
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…
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…
Adaptive Neural Network-based OFDM Receivers
Moritz Benedikt Fischer, Sebastian Dörner, Sebastian Cammerer +3
We propose and examine the idea of continuously adapting state-of-the-art neural network (NN)-based orthogonal frequency division multiplex (OFDM) receivers to current channel cond…
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…
Iterative Reed-Muller Decoding
Marvin Geiselhart, Ahmed Elkelesh, Moustafa Ebada +2
Reed-Muller (RM) codes are known for their good maximum likelihood (ML) performance in the short block-length regime. Despite being one of the oldest classes of channel codes, find…
Serial vs. Parallel Turbo-Autoencoders and Accelerated Training for Learned Channel Codes
Jannis Clausius, Sebastian Dörner, Sebastian Cammerer +1
Attracted by its scalability towards practical codeword lengths, we revisit the idea of Turbo-autoencoders for end-to-end learning of PHY-Layer communications. For this, we study t…
Wiener Filter versus Recurrent Neural Network-based 2D-Channel Estimation for V2X Communications
Moritz Benedikt Fischer, Sebastian Dörner, Sebastian Cammerer +4
We compare the potential of neural network (NN)-based channel estimation with classical linear minimum mean square error (LMMSE)-based estimators, also known as Wiener filtering. F…
On the Automorphism Group of Polar Codes
Marvin Geiselhart, Ahmed Elkelesh, Moustafa Ebada +2
The automorphism group of a code is the set of permutations of the codeword symbols that map the whole code onto itself. For polar codes, only a part of the automorphism group was…
Iterative Detection and Decoding of Finite-Length Polar Codes in Gaussian Multiple Access Channels
Moustafa Ebada, Sebastian Cammerer, Ahmed Elkelesh +2
We consider the usage of finite-length polar codes for the Gaussian multiple access channel (GMAC) with a finite number of users. Based on the interleave-division multipleaccess (I…