arXiv subjects

Christoph Mecklenbräuker

Publications and source records attributed to Christoph Mecklenbräuker.

3 recordsLinked to original sources

arXiv2024

Deep Learning-based Modulation Classification of Practical OFDM Signals for Spectrum Sensing

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 OFDM symbol duration and cyclic prefix length based on the cyclic autocorrelation function. We propose a feature extraction algorithm characterizing the modulation of OFDM signals, which includes removing the effects of a synchronization error. The obtained feature is converted into a 2D histogram of phase and amplitude and this histogram is taken as input to a convolutional neural network (CNN)-based classifier. The classifier does not require prior knowledge of protocol-specific information such as Wi-Fi preamble or resource allocation of 5G physical channels. The classifier's performance, evaluated using synthetic and real-world measured over-the-air (OTA) datasets, achieves a minimum accuracy of 97\% accuracy with OTA data when SNR is above the value required for data transmission.

cs.NI↗

arXiv2017

Sparse Bayesian learning with uncertainty models and multiple dictionaries

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, approximately solves a non-convex optimization problem using fixed point updates. It provides comparable performance and is significantly faster than convex optimization techniques used in sparse processing. We propose a signal model which accounts for dictionary mismatch and the presence of errors in the weight vector at low signal-to-noise ratios. A fixed point update equation is derived which incorporates the statistics of mismatch and weight errors. We also process observations from multiple dictionaries. Noise variances are estimated using stochastic maximum likelihood. The derived update equations are studied quantitatively using beamforming simulations applied to direction-of-arrival (DoA). Performance of SBL using single- and multi-frequency observations, and in the presence of aliasing, is evaluated. SwellEx-96 experimental data demonstrates qualitatively the advantages of SBL.

stat.AP↗

arXiv2014

Simulation and Measurement Based Vehicle-to-Vehicle Channel Characterization: Accuracy and Constraint Analysis

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 campaign using a channel sounder. Channel metrics such as channel gain, delay and Doppler spreads, eigenvalue decomposition and antenna correlations are derived from the ray tracing (RT) simulations as well as from the measurement data obtained from two different measurements in an urban four-way intersection scenario. The channel metrics are compared separately for line-of-sight (LOS) and non-LOS (NLOS) situation. Most power contributions arise from the LOS component (if present) as well as from multipaths with single bounce reflections. Measurement and simulation results show a very good agreement in the presence of LOS, as most of the received power is contributed from the LOS component. In NLOS, the difference is large because the ray tracer is unable to capture some of the multi bounced propagation paths that are present in the measurements. Despite the limitations of the ray-based propagation model identified in this work, the model is suitable to characterize the channel properties in a sufficient manner.

cs.NI↗