2 citations · 3 across the 10 of their papers we have counts for
12 papers
Learning Sparsifying Transforms for mmWave Communication via -Norm Maximization
Sueda Taner, Christoph Studer
The high directionality of wave propagation at millimeter-wave (mmWave) carrier frequencies results in only a small number of significant transmission paths between user equipments…
CSI-Based User Positioning, Channel Charting, and Device Classification with an NVIDIA 5G Testbed
Reinhard Wiesmayr, Frederik Zumegen, Sueda Taner +2
Channel-state information (CSI)-based sensing will play a key role in future cellular systems. However, no CSI dataset has been published from a real-world 5G NR system that facili…
CSI2Vec: Towards a Universal CSI Feature Representation for Positioning and Channel Charting
Victoria Palhares, Sueda Taner, Christoph Studer
Natural language processing techniques, such as Word2Vec, have demonstrated exceptional capabilities in capturing semantic and syntactic relationships of text through vector embedd…
Cauchy-Schwarz Regularizers
Sueda Taner, Ziyi Wang, Christoph Studer
We introduce a novel class of regularization functions, called Cauchy-Schwarz (CS) regularizers, which can be designed to induce a wide range of properties in solution vectors of o…
Channel Charting in Real-World Coordinates with Distributed MIMO
Sueda Taner, Victoria Palhares, Christoph Studer
Channel charting is an emerging self-supervised method that maps channel-state information (CSI) to a low-dimensional latent space (the channel chart) that represents pseudo-positi…
Channel Charting for Streaming CSI Data
Sueda Taner, Maxime Guillaud, Olav Tirkkonen +1
Channel charting (CC) applies dimensionality reduction to channel state information (CSI) data at the infrastructure basestation side with the goal of extracting pseudo-position in…
Channel Charting in Real-World Coordinates
Sueda Taner, Victoria Palhares, Christoph Studer
Channel charting is an emerging self-supervised method that maps channel state information (CSI) to a low-dimensional latent space, which represents pseudo-positions of user equipm…
Alternating Projections Method for Joint Precoding and Peak-to-Average-Power Ratio Reduction
Sueda Taner, Christoph Studer
Orthogonal frequency-division multiplexing (OFDM) time-domain signals exhibit high peak-to-average (power) ratio (PAR), which requires linear radio-frequency chains to avoid an inc…
Feature Learning for Neural-Network-Based Positioning with Channel State Information
Emre Gönültaş, Sueda Taner, Howard Huang +1
Recent channel state information (CSI)-based positioning pipelines rely on deep neural networks (DNNs) in order to learn a mapping from estimated CSI to position. Since real-world…
Hardware-Aware Beamspace Precoding for All-Digital mmWave Massive MU-MIMO
Emre Gönültaş, Sueda Taner, Alexandra Gallyas-Sanhueza +2
Massive multi-user multiple-input multiple-output (MU-MIMO) wireless systems operating at millimeter-wave (mmWave) frequencies enable simultaneous wideband data transmission to a l…
-Norm Minimization for Joint Precoding and Peak-to-Average-Power Ratio Reduction
Sueda Taner, Christoph Studer
Wireless communication systems that rely on orthogonal frequency-division multiplexing (OFDM) suffer from a high peak-to-average (power) ratio (PAR), which necessitates power-ineff…
Optimality of the Discrete Fourier Transform for Beamspace Massive MU-MIMO Communication
Sueda Taner, Christoph Studer
Beamspace processing is an emerging technique to reduce baseband complexity in massive multiuser (MU) multiple-input multiple-output (MIMO) communication systems operating at milli…