963 citations · 3.4k across the 52 of their papers we have counts for
8 papers · 1 filter
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…
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…
Improving Channel Charting using a Split Triplet Loss and an Inertial Regularizer
Brian Rappaport, Emre Gönültaş, Jakob Hoydis +3
Channel charting is an emerging technology that enables self-supervised pseudo-localization of user equipments by performing dimensionality reduction on large channel-state informa…
Adaptive Neural Signal Detection for Massive MIMO
Mehrdad Khani, Mohammad Alizadeh, Jakob Hoydis +1
Symbol detection for Massive Multiple-Input Multiple-Output (MIMO) is a challenging problem for which traditional algorithms are either impractical or suffer from performance limit…
Transmitter Classification With Supervised Deep Learning
Cyrille Morin, Leonardo Cardoso, Jakob Hoydis +2
Hardware imperfections in RF transmitters introduce features that can be used to identify a specific transmitter amongst others. Supervised deep learning has shown good performance…
Towards Massive MIMO 2.0: Understanding spatial correlation, interference suppression, and pilot contamination
Luca Sanguinetti, Emil Björnson, Jakob Hoydis
Since the seminal paper by Marzetta from 2010, Massive MIMO has changed from being a theoretical concept with an infinite number of antennas to a practical technology. The key conc…
Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays
Emil Björnson, Luca Sanguinetti, Henk Wymeersch +2
Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 f…
Novel Massive MIMO Channel Sounding Data Applied to Deep Learning-based Indoor Positioning
Maximilian Arnold, Jakob Hoydis, Stephan ten Brink
With a significant increase in area throughput, Massive MIMO has become an enabling technology for fifth generation (5G) wireless mobile communication systems. Although prototypes…