Kongress- und Tagungsbeiträge des Fachgebiets Elektronische Messtechnik und SignalverarbeitungKongress- und Tagungsbeiträge des Fachgebiets Elektronische Messtechnik und Signalverarbeitung

Kongress- und Tagungsbeiträge

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Schieler, Steffen; Semper, Sebastian; Faramarzahangari, Reza; Döbereiner, Michael; Schneider, Christian; Thomä, Reiner
Grid-free harmonic retrieval and model order selection using convolutional neural networks. - In: IEEE Xplore digital library, ISSN 2473-2001, (2024), insges. 5 S.

Harmonic retrieval techniques are the foundation of radio channel sounding, estimation and modeling. This paper introduces a Deep Learning approach for joint delay- and Doppler estimation from frequency and time samples of a radio channel transfer function. Our work estimates the two-dimensional parameters from a signal containing an unknown number of paths. Compared to existing deep learning-based methods, the signal parameters are not estimated via classification but in a quasi-grid-free manner. This alleviates the bias, spectral leakage, and ghost targets that grid-based approaches produce. The proposed architecture also reliably estimates the number of paths in the measurement. Hence, it jointly solves the model order selection and parameter estimation task. Additionally, we propose a multi-channel windowing of the data to increase the estimator's robustness. We also compare the performance to other harmonic retrieval methods and integrate it into an existing maximum likelihood estimator for efficient initialization of a gradient-based iteration.

Dupleich, Diego; Ebert, Alexander; Völker-Schöneberg, Yanneck; Sitdikov, Damir; Boban, Mate; Samara, Lutfi; Del Galdo, Giovanni; Thomä, Reiner
Characterization of propagation in an industrial scenario from sub-6 GHz to 300 GHz. - In: IEEE Xplore digital library, ISSN 2473-2001, (2023), S. 1475-1480

We perform simultaneous multi-band ultra-wideband dual-polarized double-directional measurements at sub-6 GHz (center frequency, 6.75 GHz), mmWave (74.25 GHz), and sub-THz (305.27 GHz) in line of sight (LOS) and non-LOS in a small industrial scenario (machine room). The aim is to characterize the propagation at THz taking as a reference the lower bands and identifying shared and distinguishing features. The spatial/temporal analysis of the measurements shows strong similarities in multi-path components (MPCs) between the different bands. Moreover, high order reflections have been identified at THz. Overall, the results indicate that THz channels exhibit significant multipath, with some specular MPCs unique to the band and with lower contribution by the diffuse components. Finally, path-loss has also been computed and compared with existing multi-band models.

¸Cakiro&bovko;glu, Ozan; Pérez, Eduardo; Römer, Florian; Schiffner, Martin Friedrich
Autoencoder-based learning of transmission parameters in fast pulse-echo ultrasound imaging employing sparse recovery. - In: IEEE Xplore digital library, ISSN 2473-2001, (2023), S. 516-520

There is recently a notable rise in the exploration of pulse-echo ultrasound image reconstruction techniques that address the inverse problem employing sparse signal and rely on a single measurement cycle. Nevertheless, these techniques continue to pose significant challenges with regard to accuracy of estimations. Previous studies have endeavored to decrease the correlation between received samples in each transducer array in order to enhance accuracy of sparsely approximated solutions to inverse problems. In this paper, our objective is to learn the transmission parameters within a parametric measurement matrix by employing an autoencoder, which encodes sparse spatial data with a parametric measurement matrix and subsequently decodes it using Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). Outcomes exhibit superior performance in comparison to both state-of-art random selection of the parameters and conventional plane wave imaging (PWI) scenarios in terms of reconstruction accuracy.

Wang, Han; Pérez, Eduardo; Römer, Florian
Data-driven subsampling matrices design for phased array ultrasound nondestructive testing. - In: IEEE IUS 2023, International Ultrasonics Symposium, Palais des congrès de Montréal, September 3-8, 2023, (2023), insges. 4 S.

By subsampling optimally in the spatial and temporal domains, ultrasound imaging can achieve high performance, while also accelerating data acquisition and reducing storage requirements. We study the design of experiment problem that attempts to find an optimal choice of the subsampling patterns, leading to a non-convex combinatorial optimization problem. Recently, deep learning was shown to provide a feasible approach for solving such problems efficiently by virtue of the softmax function as a differentiable approximation of the one-hot encoded subsampling vectors. We incorporate softmax neural networks into information theory-based and task-based algorithms, respectively, to design optimal subsampling matrices in Full Matrix Capture (FMC) measurements predicated on compressed sensing theory.

Wang, Han; Pérez, Eduardo; Römer, Florian
Deep learning-based optimal spatial subsampling in ultrasound nondestructive testing. - In: 31st European Signal Processing Conference (EUSIPCO 2024), (2023), S. 1863-1867

Traditional ultrasound synthetic aperture imaging relies on closely spaced measurement positions, where the pitch size is smaller than half the ultrasound wavelength. While this approach achieves high-quality images, it necessitates the storage of large data sets and an extended measurement time. To address these issues, there is a burgeoning interest in exploring effective subsampling techniques. Recently, Deep Probabilistic Subsampling (DPS) has emerged as a feasible approach for designing selection matrices for multi-channel systems. In this paper, we address spatial subsampling in single-channel ultrasound imaging for Nondestructive Testing (NDT) applications. To accomplish a model-based data-driven spatial subsampling approach within the DPS framework that allows for the optimal selection of sensing positions on a discretized grid, it is crucial to build an adequate signal model and design an adapted network architecture with a reasonable cost function. The reconstructed image quality is then evaluated through simulations, showing that the presented subsampling pattern approaches the performance of fully sampling and substantially outperforms uniformly spatial subsampling in terms of signal recovery quality.

Semper, Sebastian; Pérez, Eduardo; Landmann, Markus; Thomä, Reiner
Misspecification under the narrowband assumption: a Cramér-Rao bound perspective. - In: 31st European Signal Processing Conference (EUSIPCO 2024), (2023), S. 1524-1528

To efficiently extract estimates about the propagation behavior of electromagnetic waves in a radio environment it is common to invoke the narrowband-assumption. It essentially states that the relative bandwidth of the measurement system is so low that the frequency response of a single propagation path only depends on it Time-of-Flight and the response of the measurement device can be calibrated independently of the measured channel. Recent advances into higher relative bandwidths and antenna arrays with larger spatial aperture render this assumption less likely to be satisfied, which leads to a model mismatch during estimation. In this case estimates are inherently biased and have a special statistical behavior. This behavior can be captured by the so-called Misspecified Cramér-Rao Bound, which formulates a lower bound for the variance of estimates that are biased due to model mismatch. We analyze this bound in contrast to the traditional Cramér-Rao Bound and show the shortcomings in the setting of joint ToF-DoA estimation in the mmWave spectrum. The conducted numerical studies also show that planar array geometries inherently suffer from violation of the narrowband assumption irrespective of the individual elements' frequency response, whereas circular structures show it to a lesser degree.

¸Cakiro&bovko;glu, Ozan; Pérez, Eduardo; Römer, Florian; Schiffner, Martin
Optimization of transmission parameters in fast pulse-echo ultrasound imaging using sparse recovery. - In: 31st European Signal Processing Conference (EUSIPCO 2024), (2023), S. 441-445

In pulse-echo ultrasound imaging, the goal is to achieve a certain image quality while minimizing the duration of the signal acquisition. In the past, fast ultrasound imaging methods applying sparse signal recovery have been implemented by accepting a single pulse-echo measurement. However, they have experienced a certain amount of reconstruction error. In sparse signal recovery, reducing the correlation between the samples of the measurements observed by the different receivers is beneficial for lowering the reconstruction error. Exploiting the Born approximation and Green's function for the wave equation, the analytical inverse scattering problem can be defined in matrix-vector form. Adopting this setting, it has been suggested in the past to reduce the correlation between the samples of the measurement using Cylindrical Waves (CWs) with randomly selected delays and weights. In a similar setting, we created an optimization problem accepting transmission delays and weights as variables to minimize the correlation between the samples of the measurement in each receiver. We demonstrate via simulations that CWs employing the optimized transmission parameters outperformed the cases with Plane Wave Imaging (PWI) and CWs with random transmission parameters in terms of reconstruction accuracy.

Foliadis, Anastasios; Garcia, Mario H. Castañeda; Stirling-Gallacher, Richard A.; Gong, Xitao; Thomä, Reiner
Deep learning based positioning with beamformed CSI fingerprints. - In: Proceedings of the 2023 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN), (2023), insges. 6 S.

User positioning with deep learning (DL) models based on channel state information (CSI) fingerprints, e.g., obtained at a base station (BS), has emerged as a promising technology. Related prior works generally assume a CSI fingerprint with multiple spatial dimensions (i.e antennas or beams) at the BS but only a single spatial dimension at the user equipment (UE). However, a UE may be equipped with multiple antennas or may need to perform beamforming, e.g., to support transmissions at higher frequencies. In this work we consider user positioning with DL models based on uplink beamformed CSI fingerprints considering multiple spatial dimensions at both the BS and the UE. By considering a single or multiple beams at the BS and UE, the use of different CSI fingerprints is proposed. The positioning accuracy achieved with the different beamformed CSI fingerprints is evaluated and compared. The different orientation during training and UE deployment is also considered. In addition, we also consider the positioning of UEs with different spatial capabilities, i.e. with different number of beams. This work provides valuable insights into the design of wireless positioning with CSI fingerprints considering multiple spatial dimensions at both the BS and UE.

Vintimilla, Renato Zea; Lorenz, Mario; Muchhal, Nitin; Landmann, Markus; Del Galdo, Giovanni
Demonstration and validation of a 3D wave field synthesis setup for multiple GNSS satellite emulation via over-the-air testing. - In: AMTA 2023 proceedings, (2023), insges. 10 S.

Wireless devices supporting global navigation satellite systems (GNSS) services have become an essential tool in different areas of technology such as agriculture, construction, automotive, etc. Therefore the performance and reliability of such devices are important aspects that need to be addressed in the testing stage during the development of the units. The integration of the Over-the-Air (OTA) testing method with the 3D Wave Field Synthesis (3DWFS) technique offer not only the benefit of having tests under controllable and repeatable conditions but also the ability to recreate complex and realistic scenarios in a controlled environment with full polarimetric support for the testing of wireless devices. This contribution applies this technology to emulate a GNSS scenario within an anechoic chamber. For the results validation, a realistic GNSS outdoor scenario was recorded and compared with the emulated scenario where 3DWFS was applied for each individual satellite. This represents a significant step for the GNSS community and also for the future development and testing of wireless devices.

Thomä, Reiner; Dallmann, Thomas
Distributed ISAC systems - multisensor radio access and coordination. - In: 2023 20th European Radar Conference, (2023), S. 351-354

Integrated sensing and communication (ISAC) qualifies mobile radio systems for detecting and localizing of passive objects by means of radar sensing. Advanced ISAC networks rely on distributed infrastructure, multisensor uplink and downlink, or meshed sidelink access. In this way, ISAC develops into a MS-MIMO (multisensor multiple input multiple output) network which constitutes a distributed MIMO radar network. Multisensor link coordination and synchronization are becoming crucial. Many multisensor access and signaling techniques find their communication counterpart in multiuser MIMO and cooperative multilink communications (CoMP) and can be adopted from there.