LO and calibration signal distribution in a multi-antenna satellite navigation receiver. - In: Engineering proceedings, ISSN 2673-4591, Bd. 54 (2023), 1, 23, S. 1-10
Due to the low signal power of global navigation satellite signals, the receivers are prone to radio frequency interference. Employing multi-antenna arrays is one method to mitigate such effects, by incorporating spatial processing techniques. The large size of the uniform rectangular arrays prevents their use in applications where installation space is limited. Therefore, we proposed a new approach, namely to split one full array into a number of smaller, spatially distributed, sub-arrays to reduce their size and exploit available installation spaces. This concept challenges the distribution of the local oscillator and calibration signals to the respective sub-arrays. This paper compares qualitatively different design concepts for a satellite navigation receiver with two two-element sub-arrays, installed multiple wavelengths apart from each other, in support of establishing an optimal choice for our intended applications in the automotive sector in terms of electrical performance and required hardware and software efforts. In general, weighing the pros and cons of the different concepts, as discussed in the paper, will assist in optimizing the system design approach for a specific application.
https://doi.org/10.3390/ENC2023-15447
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.
https://doi.org/10.1109/IUS51837.2023.10308257
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.
https://doi.org/10.23919/EUSIPCO58844.2023.10289868
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.
https://doi.org/10.23919/EUSIPCO58844.2023.10289949
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.
https://doi.org/10.23919/EUSIPCO58844.2023.10290105
MOSFETs with stacked 2D nanosheet channels - an auspicious option to delay “forever”. - In: 2023 37th Symposium on Microelectronics Technology and Devices (SBMicro), (2023), insges. 4 S.
For decades, chipmakers brought digital logic ICs (integrated circuit) with an exponentially increasing complexity and computing power to market. This was made possible by continuously shrinking the size of the basic component of logic ICs, i.e., by MOSFET scaling. Over the years, MOSFET scaling passed through several stages with a new stage beginning when the scaling method used at the previous stage was approaching its limits. In the present paper, we provide an overview of these stages of scaling, discuss the transition from the conventional planar MOSFET to the FinFET architecture in the early 2010s, and converse about the upcoming introduction of another new MOSFET architecture, the SNC (stacked nanosheet channel) MOSFET. Here, special emphasis is put on transistors using two-dimensional (2D) materials for the stacked channels.
https://doi.org/10.1109/SBMicro60499.2023.10302491
Optical character recognition for medical records digitization with deep learning. - In: 2023 IEEE International Conference on Image Processing, (2023), S. 3260-3263
The importance of document digitization has increased due to recent technological advancements, including in the medical field. Digitization of medical records plays a vital role in the healthcare sector as it helps expedite emergency treatment. Due to the scarcity of published studies and public German textual resources, a medical records database with German handwriting was collected and digitized. In this study, document digitization was accomplished by implementing deep learning, region of interest (ROI) detection, and optical character recognition (OCR) on a dataset containing medical forms filled with German and English characters. To find the best model for ROI detection, YOLOv5, and SSDResNet50 models were utilized and compared with YOLOv5 producing a better mean average precision (mAP) of 0.91. OCR was then carried out on the output from YOLOv5 with two different methods again for comparison. The Gated-CNN-BLSTM algorithm yielded a character error rate (CER) of 9%, while transformer-based OCR (TrOCR) achieved a CER of 6%. The proposed system could be implemented and further tested in local hospitals, with the OCR dictionary being expandable to include other Roman character-based languages.
https://doi.org/10.1109/ICIP49359.2023.10222038
Circularly polarized patch antenna array for 5G automotive satellite communications. - In: 2023 53rd European Microwave Conference, (2023), S. 794-797
5G low-earth orbit (LEO) satellite communication plays a crucial role in enhancing the reliability and coverage of wireless connectivity for automated and connected driving. Compactness of user equipment antennas presents a key requirement for automotive mass-market applications offering non-terrestrial connectivity in addition to terrestrial mobile communications. Latest studies reveal the potential for moderate-gain antenna terminals for such applications. We present a circularly polarized 4 × 4 patch antenna array operating at a center frequency of 2S GHz in the 5G new-radio band n257 suitable for LEO satellite communications. The antenna is feasible for integration into the rear spoiler of a car, roof-top shark-fin antenna, or other plastic-covered antenna mounting locations. The embedded array offers 12 dBi measured realized gain and 4 GHz of -10 dB impedance bandwidth. It offers a 3-dB axial-ratio bandwidth of 900 MHz, demonstrating its circular polarization purity along the broadside direction. Realistic link budget calculations predict an uplink data rate of 6 Mbit/s, promising for various automotive mobility applications.
https://doi.org/10.23919/EuMC58039.2023.10290591
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.
https://doi.org/10.1109/IPIN57070.2023.10332494
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.
https://doi.org/10.23919/AMTA58553.2023.10293372