335 citations · 859 across the 12 of their papers we have counts for
12 papers
Double-Directional V2V Channel Measurement using ReRoMA at 60 GHz
Hussein Hammoud, Yuning Zhang, Zihang Cheng +9
The coordination of vehicles is a crucial element of autonomous driving, as it enhances the efficiency, convenience, and safety of road traffic. In order to fully exploit the capab…
Deep Learning-based Modulation Classification of Practical OFDM Signals for Spectrum Sensing
Byungjun Kim, Christoph Mecklenbräuker, Peter Gerstoft
In this study, the modulation of symbols on OFDM subcarriers is classified for transmissions following Wi-Fi~6 and 5G downlink specifications. First, our approach estimates the OFD…
Channel Estimation for mmWave MIMO using sub-6 GHz Out-of-Band Information
Faruk Pasic, Markus Hofer, Mariam Mussbah +4
Future wireless multiple-input multiple-output (MIMO) communication systems will employ sub-6 GHz and millimeter wave (mmWave) frequency bands working cooperatively. Establishing a…
Stationarity Evaluation of High-mobility sub-6 GHz and mmWave non-WSSUS Channels
Danilo Radovic, Faruk Pasic, Markus Hofer +3
Analysis and modeling of wireless communication systems are dependent on the validity of the wide-sense stationarity uncorrelated scattering (WSSUS) assumption. However, in high-mo…
Robust and Sparse M-Estimation of DOA
Christoph F. Mecklenbräuker, Peter Gerstoft, Esa Ollila +1
A robust and sparse Direction of Arrival (DOA) estimator is derived for array data that follows a Complex Elliptically Symmetric (CES) distribution with zero-mean and finite second…
Sparse Bayesian learning with uncertainty models and multiple dictionaries
Santosh Nannuru, Kay L. Gemba, Peter Gerstoft +2
Sparse Bayesian learning (SBL) has emerged as a fast and competitive method to perform sparse processing. The SBL algorithm, which is developed using a Bayesian framework, approxim…
Multi Snapshot Sparse Bayesian Learning for DOA Estimation
Peter Gerstoft, Christoph F. Mecklenbräuker, Angeliki Xenaki
The directions of arrival (DOA) of plane waves are estimated from multi-snapshot sensor array data using Sparse Bayesian Learning (SBL). The prior source amplitudes is assumed inde…
Multiple and single snapshot compressive beamforming
Peter Gerstoft, Angeliki Xenaki, Christoph F. Mecklenbräuker
For a sound field observed on a sensor array, compressive sensing (CS) reconstructs the direction-of-arrival (DOA) of multiple sources using a sparsity constraint. The DOA estimati…
Using the LASSO's Dual for Regularization in Sparse Signal Reconstruction from Array Data
Christoph F. Mecklenbräuker, Peter Gerstoft, Erich Zöchmann
Waves from a sparse set of source hidden in additive noise are observed by a sensor array. We treat the estimation of the sparse set of sources as a generalized complex-valued LASS…
Simulation and Measurement Based Vehicle-to-Vehicle Channel Characterization: Accuracy and Constraint Analysis
Taimoor Abbas, Jörg Nuckelt, Thomas Kürner +3
In this paper, a deterministic channel model for vehicle-to-vehicle (V2V) communication, is compared against channel measurement data collected during a V2V channel measurement cam…
Time- and Frequency-Varying -Factor of Non-Stationary Vehicular Channels for Safety Relevant Scenarios
Laura Bernadó, Thomas Zemen, Fredrik Tufvesson +2
Vehicular communication channels are characterized by a non-stationary time- and frequency-selective fading process due to fast changes in the environment. We characterize the dist…
Delay and Doppler Spreads of Non-Stationary Vehicular Channels for Safety Relevant Scenarios
Laura Bernadó, Thomas Zemen, Fredrik Tufvesson +2
Vehicular communication channels are characterized by a non-stationary time- and frequency-selective fading process due to rapid changes in the environment. The non-stationary fadi…