Transfer learning capabilities of untrained neural networks for MIMO CSI recreation. - In: 2022 IEEE International Conference on Communications, (2022), S. 1288-1293
Machine learning (ML) applications for wireless communications have gained momentum on the standardization discussions for 5G advanced and beyond. One of the biggest challenges for real world ML deployment is the need for labeled signals and big measurement campaigns. To overcome those problems, we propose the use of untrained neural networks (UNNs) for MIMO channel recreation/estimation and low over-head reporting. The UNNs learn the propagation environment by fitting a few channel measurements and we exploit their learned prior to provide higher channel estimation gains. Moreover, we present a UNN for simultaneous channel recreation for multiple users, or multiple user equipment (UE) positions, in which we have a trade-off between the estimated channel gain and the number of parameters. Our results show that transfer learning techniques are effective in accessing the learned prior on the environment structure as they provide higher channel gain for neighbouring users. Moreover, the proposed UNN channel state information (CSI) estimators are under-parameterized and can further enable low-overhead CSI reporting.
https://doi.org/10.1109/ICC45855.2022.9838738
Reliable deep learning based localization with CSI fingerprints and multiple base stations. - In: 2022 IEEE International Conference on Communications, (2022), S. 3214-3219
Deep learning (DL) methods have been recently proposed for user equipment (UE) localization in wireless communication networks, based on the channel state information (CSI) between a UE and multiple base stations (BSs) in the uplink. With the CSI from the available BSs, UE localization can be performed in different ways. On the one hand, a single neural network (NN) can be trained for the UE localization by considering the CSI from all the available BSs as one overall fingerprint of the user’s location. On the other hand, the CSI at each BS can be used to obtain an estimate of the UE’s position with a separate NN at each BS, and then the position estimates of all BSs are combined to obtain an overall estimate of the UE position. In this work, we show that UE localization with the latter approach can achieve a higher positioning accuracy. We propose to consider the uncertainty in the UE localization at each BS, such that overall UE’s position is determined by combining the position estimates of the different BSs based on the uncertainty at each BS. With this approach, a more reliable position estimate can be obtained in case of variations in the channel.
https://doi.org/10.1109/ICC45855.2022.9838535
Optimal parameters of a nonmagnetic conducting cylindrical double-shell shield rotating in a static magnetic field. - In: International journal of applied electromagnetics and mechanics, ISSN 1875-8800, Bd. 69 (2022), 3, S. 401-410
This paper first presents an analytical model for calculating the shielding effectiveness of static magnetic fields using a rotating double-shell cylindrical shield with electromagnetically thin layers made of non-magnetic conducting material. Then a procedure is given for finding the optimum distance between the shells and their thickness for maximum mass reduction compared to a thick single shield for a given shielding factor.
https://doi.org/10.3233/JAE-210208
Spotting the gap in the design flow for superconducting electronic devices. - In: 2022 18th International Conference on Synthesis, Modeling, Analysis and Simulation Methods, and Applications to Circuit Design, (2022), insges. 4 S.
Quantum technologies have matured in a way that real applications are considered to be viable. The new quality emerges from the use of explicit quantum phenomena in single objects as qubits for computation, or photons for sensing and communication. However, to make these features exploitable, suitable microelectronic components for controlling and readout of the quantum states have to be available. For this, superconductive solid-state electronic circuits are considered to be promising candidates. First demonstrations for suitability are known. In order to provide scaling towards large-scale integrated structures, appropriate design methods and capabilities have to be developed. We provide an assessment of the current state of design automation for such superconducting digital electronic structures and survey existing approaches and tools.
https://doi.org/10.1109/SMACD55068.2022.9816318
LTCC patch antenna array for 5G mobile applications featuring embedded air cavities. - In: 2022 International Conference on Electronics Packaging (ICEP 2022), (2022), S. 139-140
A LTCC patch antenna array was designed and fabricated in Low Temperature Co-fired Ceramic (LTCC) multilayer technology using picosecond laser structuring for precise manufacturing of embedded air cavities and feeding structures, which are beneficial for the antenna RF performance. Moreover, free-standing feeding vias in the embedded air cavities were successfully implemented in LTCC technology that enable a very simple and low-loss feed at the antenna ports. The 2x2 dual-polarized patch antenna array with embedded air cavities and transitions was first characterized by reflection measurements. The measured center frequency of the antenna is about 29.5 GHz and a bandwidth of nearly 1 GHz was achieved.
https://doi.org/10.23919/ICEP55381.2022.9795485
Descending staircase detection for service robots based on M-sequence UWB radar. - In: 2021 18th European Radar Conference, (2022), S. 29-32
Service robotics is expected to be one of the central growth industries of this century. The technological key to this lies in the sufficient perception of the environment, even under difficult conditions, because mobile robots have to orientate themselves and navigate without collision under all circumstances. However, the safe detection of especially descending stairs is a big challenge so far. In this paper, the results of descending staircase detection using UWB radar are shown. The individual steps of the signal processing from signal preparation to multi-target tracking are briefly explained and an outlook is given on how to classify a staircase based on the results. For all investigated stairs the edge of the first step could be detected reliably from a distance of 1.5 m and multiple steps are distinguishable as well.
https://doi.org/10.23919/EuRAD50154.2022.9784493
Angle-dependent reflectivity of microwave absorbers at oblique wave incidence. - In: 2021 51st European Microwave Conference, (2022), S. 233-236
For frequencies in the GHz-range, anechoic chambers are usually evaluated using ray-tracing techniques to locate disturbing reflections off the chamber walls. Most approaches reduce this wave-absorber interaction to a specular reflection, although the absorbers may extend over several wavelengths in size and display a rough surface. In order to develop more realistic ray-tracing models, the reflection characteristics of absorbers must be evaluated based on physical wave phenomena. In this paper, a measurement method is proposed which extends the established NRL-arch to measure the angle-dependent reflectivity for non-specular cases. First measurement results of commercial pyramidal absorbers in the frequency range between 1GHz and 10GHz indicate that the assumption of specular reflections is not justified, as power is reflected over a wide angular range with approximately the same intensity. This effect is, to our knowledge, currently not implemented in ray-tracing methods. These results contribute to a better understanding of the properties of RF absorbers to improve the efficiency of their use.
https://doi.org/10.23919/EuMC50147.2022.9784282
Localization and navigation of service robots by means of M-sequence UWB radars. - In: 2021 18th European Radar Conference, (2022), S. 189-192
The use of service robots has become much more relevant in industry and retail in recent years. To be of best possible benefit to humans, an autonomous motion ability of the service robots is of central importance. This requires that the robot can perceive its surroundings as precisely as possible by using different sensors and their fusion. In contrast to optical sensors, an UWB sensor can, for example, detect small and almost invisible objects such as glass panes with high range resolution. In this paper, a signal processing chain for detection of the environment with M-sequence UWB sensors is proposed. The proposed chain includes pulse reconstruction based on calibration measurements, background subtraction, object detection based on CFAR techniques, and multi-target tracking based on the Kalman filter and the nearest-neighbor approach.
https://doi.org/10.23919/EuRAD50154.2022.9784511
Impact of small-cell deployment on combined uplink and downlink RF exposure compared to the status quo in mobile networks. - In: 2021 51st European Microwave Conference, (2022), S. 618-621
As new cellular technologies are introduced in mobile networks nowadays, more and more small cells and mobile road side units are being deployed to upgrade the performance of the wireless communication network. With regard to the overall human RF exposure, the question arises to what extent the exposure is affected by the deployment of such small cells compared to macro cells as the status quo. In an attempt to answer this important question, this paper proposes a method to measure and evaluate the combined uplink and downlink exposure in terms of the specific absorption rate of a mobile phone user at recently installed small cell locations. The comparison between the small cell and macro cell scenarios revealed a reduction of the total exposure when the user equipment was logged into the investigated LTE small cells, although the downlink exposure increased. The main reason for this encouraging result is the reduction of the uplink transmission power due to the improved link conditions across the small cell. In contrast, the total exposure in a macro cell scenario is dominated by the uplink exposure. In order to minimise the total exposure, a balance must be sought between downlink and uplink exposure.
https://doi.org/10.23919/EuMC50147.2022.9784284
A data-driven approach for stochastic modeling of automotive radar detections for extended objects. - In: Ulm 2022 GeMiC, (2022), S. 80-83
Radar sensors play an important role in automated driving technologies. However, the rising number of sensors deployed to enable autonomous driving functions leads to enormous validation efforts. While simulations are a possible approach to accelerate the validation process, the development effort for realistic sensor models increases significantly. Data-driven sensor models offer the possibility to replicate sensor data accurately and efficiently. Using real measurement data, the sensor output can be simulated without the detailed parametric modeling of the wave propagation and sensor effects. In this paper, the radar signatures of a passenger vehicle under a constant aspect angle are analyzed in real measurements. Then, a data-driven approach for stochastically modeling the radar target detections is presented. The model is trained with real sensor data to achieve a high degree of realism. A qualitative comparison between the simulated and measured detections reveals promising results.
https://ieeexplore.ieee.org/document/9783497