963 citations · 3.4k across the 52 of their papers we have counts for
9 papers · 1 filter
DUIDD: Deep-Unfolded Interleaved Detection and Decoding for MIMO Wireless Systems
Reinhard Wiesmayr, Chris Dick, Jakob Hoydis +1
Iterative detection and decoding (IDD) is known to achieve near-capacity performance in multi-antenna wireless systems. We propose deep-unfolded interleaved detection and decoding…
Attacking and Defending Deep-Learning-Based Off-Device Wireless Positioning Systems
Pengzhi Huang, Emre Gönültaş, Maximilian Arnold +3
Localization services for wireless devices play an increasingly important role in our daily lives and a plethora of emerging services and applications already rely on precise posit…
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…
Mixed-Timescale Deep-Unfolding for Joint Channel Estimation and Hybrid Beamforming
Kai Kang, Qiyu Hu, Yunlong Cai +3
In massive multiple-input multiple-output (MIMO) systems, hybrid analog-digital beamforming is an essential technique for exploiting the potential array gain without using a dedica…
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…
Bit-Metric Decoding Rate in Multi-User MIMO Systems: Applications
K. Pavan Srinath, Jakob Hoydis
This is the second part of a two-part paper that focuses on link-adaptation (LA) and physical layer (PHY) abstraction for multi-user MIMO (MU-MIMO) systems with non-linear receiver…
Bit-Metric Decoding Rate in Multi-User MIMO Systems: Theory
K. Pavan Srinath, Jakob Hoydis
Link-adaptation (LA) is one of the most important aspects of wireless communications where the modulation and coding scheme (MCS) used by the transmitter is adapted to the channel…
Waveform Learning for Reduced Out-of-Band Emissions Under a Nonlinear Power Amplifier
Dani Korpi, Mikko Honkala, Janne M. J. Huttunen +2
Machine learning (ML) has shown great promise in optimizing various aspects of the physical layer processing in wireless communication systems. In this paper, we use ML to learn jo…