An efficient modeling approach of 1D-planar metamaterials in the high-frequency regime. - In: Compel, ISSN 2054-5606, Bd. 42 (2023), 3, S. 776-786
Purpose The purpose of this paper is to present an alternative modeling approach in terms of the determination of a physically equivalent circuit model for one-dimensional (1D) planar metamaterials in the high-frequency regime, without a postprocessing optimization procedure. Thereby, an efficient implementation of physical relationships is aimed. Design/methodology/approach In this paper, a method based on quasi-stationary simulations and mathematical conversions to derive the values for a physically equivalent circuit model is proposed. Because the electromagnetic coupling mechanisms are investigated in detail, a simplification for the considered multiconductor transmission line structure is achieved. Findings The results show that the proposed modeling approach is an efficient and physically meaningful alternative to classical full-wave simulation techniques for the investigated inhomogeneous transmission line structure in both the time domain as well as in the frequency domain. In the course of this, the effort is reduced while a comparable accuracy is maintained, whereby specific coupling mechanisms are considered in circuit simulations. Originality/value The process to obtain information about physically interpretable lumped element values for a given structure or to determine a layout for known ones is simplified with the aid of the proposed approach. An advantageous adaption of the presented procedure to other areas of application is well conceivable.
https://doi.org/10.1108/COMPEL-09-2022-0313
Configurable pseudo noise radar imaging system enabling synchronous MIMO channel extension. - In: Sensors, ISSN 1424-8220, Bd. 23 (2023), 5, 2454, insges. 27 S.
In this article, we propose an evolved system design approach to ultra-wideband (UWB) radar based on pseudo-random noise (PRN) sequences, the key features of which are its user-adaptability to meet the demands provided by desired microwave imaging applications and its multichannel scalability. In light of providing a fully synchronized multichannel radar imaging system for short-range imaging as mine detection, non-destructive testing (NDT) or medical imaging, the advanced system architecture is presented with a special focus put on the implemented synchronization mechanism and clocking scheme. The core of the targeted adaptivity is provided by means of hardware, such as variable clock generators and dividers as well as programmable PRN generators. In addition to adaptive hardware, the customization of signal processing is feasible within an extensive open-source framework using the Red Pitaya® data acquisition platform. A system benchmark in terms of signal-to-noise ratio (SNR), jitter, and synchronization stability is conducted to determine the achievable performance of the prototype system put into practice. Furthermore, an outlook on the planned future development and performance improvement is provided.
https://doi.org/10.3390/s23052454
Precise motor mapping with transcranial magnetic stimulation. - In: Nature protocols, ISSN 1750-2799, Bd. 18 (2023), S. 293-318
We describe a routine to precisely localize cortical muscle representations within the primary motor cortex with transcranial magnetic stimulation (TMS) based on the functional relation between induced electric fields at the cortical level and peripheral muscle activation (motor-evoked potentials; MEPs). Besides providing insights into structure-function relationships, this routine lays the foundation for TMS dosing metrics based on subject-specific cortical electric field thresholds. MEPs for different coil positions and orientations are combined with electric field modeling, exploiting the causal nature of neuronal activation to pinpoint the cortical origin of the MEPs. This involves constructing an individual head model using magnetic resonance imaging, recording MEPs via electromyography during TMS and computing the induced electric fields with numerical modeling. The cortical muscle representations are determined by relating the TMS-induced electric fields to the MEP amplitudes. Subsequently, the coil position to optimally stimulate the origin of the identified cortical MEP can be determined by numerical modeling. The protocol requires 2 h of manual preparation, 10 h for the automated head model construction, one TMS session lasting 2 h, 12 h of computational postprocessing and an optional second TMS session lasting 30 min. A basic level of computer science expertise and standard TMS neuronavigation equipment suffices to perform the protocol.
https://doi.org/10.1038/s41596-022-00776-6
Robust multi-dimensional model order estimation using LineAr Regression of Global Eigenvalues (LaRGE). - In: IEEE transactions on signal processing, ISSN 1941-0476, Bd. 70 (2022), S. 5751-5764
The efficient estimation of an approximate model order is very important for real applications with multi-dimensional low-rank data that may be corrupted by additive noise. In this paper, we present a novel robust to noise method for model order estimation of noise-corrupted multi-dimensional low-rank data based on the LineAr Regression of Global Eigenvalues (LaRGE). The LaRGE method uses the multi-linear singular values obtained from the HOSVD of the measurement tensor to construct global eigenvalues. In contrast to the Modified Exponential Test (EFT) that also exploits the approximate exponential profile of the noise eigenvalues, LaRGE does not require the calculation of the probability of false alarm. Moreover, LaRGE achieves a significantly improved performance in comparison with popular state-of-the-art methods. It is well suited for the analysis of noisy multidimensional low-rank data including biomedical signals. The excellent performance of the LaRGE method is illustrated via simulations and results obtained from EEG recordings.
https://doi.org/10.1109/TSP.2022.3222737
Virtuelle Sensorvalidierung für automatisiertes und vernetztes Fahren. - In: Automobiltechnische Zeitschrift, ISSN 2192-8800, Bd. 124 (2022), 11, S. 58-62
https://doi.org/10.1007/s35148-022-1505-0
Virtual sensor validation for automated and connected driving. - In: ATZ worldwide, ISSN 2192-9076, Bd. 124 (2022), 11, S. 54-57
https://doi.org/10.1007/s38311-022-1405-7
Using tensor contractions to derive the structure of slice-wise multiplications of tensors with applications to space-time Khatri-Rao coding for MIMO-OFDM systems. - In: EURASIP journal on advances in signal processing, ISSN 1687-6180, Bd. 2022 (2022), 109, S. 1-26
The slice-wise multiplication of two tensors is required in a variety of tensor decompositions (including PARAFAC2 and PARATUCK2) and is encountered in many applications, including the analysis of multidimensional biomedical data (EEG, MEG, etc.) or multi-carrier multiple-input multiple-output (MIMO) systems. In this paper, we propose a new tensor representation that is not based on a slice-wise (matrix) description, but can be represented by a double contraction of two tensors. Such a double contraction of two tensors can be efficiently calculated via generalized unfoldings. It leads to new tensor models of the investigated system that do not depend on the chosen unfolding (in contrast to matrix models) and reveal the tensor structure of the data model, such that all possible unfoldings can be seen at the same time. As an example, we apply this new concept to the design of new receivers for multi-carrier MIMO systems in wireless communications. In particular, we consider MIMO-orthogonal frequency division multiplexing (OFDM) systems with and without Khatri-Rao coding. The proposed receivers exploit the channel correlation between adjacent subcarriers, require the same amount of training symbols as traditional OFDM techniques, but have an improved performance in terms of the symbol error rate. Furthermore, we show that the spectral efficiency of the Khatri-Rao-coded MIMO-OFDM can be increased by introducing cross-coding such that the “coding matrix” also contains useful information symbols. Considering this transmission technique, we derive a tensor model and two types of receivers for cross-coded MIMO-OFDM systems using the double contraction of two tensors.
https://doi.org/10.1186/s13634-022-00937-5
Human RF electromagnetic exposure to V2X-communication. - In: Advances in radio science, ISSN 1684-9973, Bd. 19 (2022), S. 233-239
In the era of automated and connected driving, more and more cars will be equipped with wireless transmission technologies such as mobile communications 4G (LTE) and 5G, WiFi, Bluetooth, and V2X. For the technical implementation of V2X-communications, different standards like cellular-V2X from the cooperation 3rd Generation Partnership Project and ITS-G5, based on the WiFi standard 802.11p from the Institute of Electrical and Electronics Engineers, are under consideration. The electromagnetic environment of cars and the corresponding exposure of the general public to wireless emission will be significantly influenced by new radio technologies. Under all circumstances, it must be ensured that the exposure of the electromagnetic fields inside a car does not cause any harmful effects on humans. In order to quantitatively assess the resulting exposure, the generated exposure must be correctly recorded and evaluated according to their specific time-frequency spectra. This paper describes a new measurement procedure suitable for the V2X-standard ITS-G5 together with various exposure measurements performed in different cars with WiFi, Bluetooth and ITS-G5. In comparison of all wireless standards studied here, the V2X-service generated the highest electric field strengths inside a car, when a transmitting di-patch antenna was mounted on the windscreen inside the driver's cabin. The maximum fraction of the corresponding ICNIRP reference level amounted to 15.1 %. We conclude that the total exposure of wireless on-board automotive devices will be dominated by ITS-G5, if the transmitting antenna is located inside the passenger cabin. As V2X-communications will increasingly penetrate road traffic, the resulting exposure should be carefully monitored, in order not to exceed the corresponding reference levels for general public.
https://doi.org/10.5194/ars-19-233-2022
5G new radio physical downlink control channel reliability enhancements for multiple transmission-reception-point communications. - In: IEEE access, ISSN 2169-3536, Bd. 10 (2022), S. 97394-97407
Non-coherent transmission from multiple transmission-reception-points (TRPs), i.e., base stations, or base station panels to a user equipment (UE) is exploited in 5G New Radio (NR) to improve downlink reliability and cell-edge throughput. Ultra reliable low-latency communications (URLLC) and enhanced Mobile BroadBand (eMBB) are prominent target use-cases for multi-TRP or multi-panel transmissions. In Third-Generation Partnership Project (3GPP) Release 17 specifications, multi-TRP-based transmissions were specified for the physical downlink control channel (PDCCH) specifically to enhance its reliability and robustness. In this work, a comprehensive account of various multi-TRP reliability enhancement schemes applicable for the 5G NR PDCCH, including the ones supported by the 3GPP Release 17 specifications, is provided. The impact of the specifications for each scheme, UE and network complexity and their utility in various use-cases is studied. Their error performances are evaluated via link-level simulations using the evaluation criteria agreed in the 3GPP proceedings. The 3GPP-supported multi-TRP PDCCH repetition schemes, and the additionally proposed PDCCH repetition and diversity schemes are shown to be effective in improving 5G NR PDCCH reliability and combating link blockage in mmWave scenarios. The link-level simulations also provide insights for the implementation of the decoding schemes for the PDCCH enhancements under different channel conditions. Analysis of the performance, complexity and implementation constraints of the proposed PDCCH transmission schemes indicate their suitability to UEs with reduced-capability or stricter memory constraints and flexible network scheduling.
https://doi.org/10.1109/ACCESS.2022.3206027
Machine learning for CSI recreation in the digital twin based on prior knowledge. - In: IEEE open journal of the Communications Society, ISSN 2644-125X, Bd. 3 (2022), S. 1578-1591
Knowledge of channel state information (CSI) is fundamental to many functionalities for mobile communication systems. With the advance of machine learning (ML) and digital maps, i.e., digital twins, we have a big opportunity to learn the propagation environment and design novel methods to derive and report CSI. In this work, we propose to combine untrained neural networks (UNNs) and conditional generative adversarial networks (cGANs) for MIMO channel recreation based on prior knowledge. The UNNs learn the prior-CSI for some locations which are used to build the input to a cGAN. Based on the prior-CSI estimates, their locations and the location of the desired channel, the cGAN is trained to output the channel expected at the desired location. This combined approach can be used for low overhead CSI reporting as, after training, we only need to report the desired location. Our results show that our CSI recreation method is successful in modelling the wireless channel under different configurations of prior-CSI spatial sampling. In addition, the results consider a real world measurement campaign for indoor line of sight and non-line of sight channels. The signal to noise ratio (SNR) achieved by our CSI recreation is better than the SNR reported by the measured campaign providers. Moreover, our CSI recreation provides means for low overhead CSI reporting as the UNN structure is underparameterized compared to the full explicit CSI, and only the desired location is needed for the cGAN to recreate the desired CSI.
https://doi.org/10.1109/OJCOMS.2022.3208323