Browsing by Author "Grass, Eckhard"
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- Item60-GHz-Multimode-Chip-Satz und Demonstrator (EASY-A/IHP) : Schlussbericht(Hannover : Technische Informationsbibliothek (TIB), 2012) Grass, Eckhard; Tittelbach-Helmrich, Klaus; Petri, Markus; Ehrig, Marcus; Glisic, Srdjan; Elkhouly, Mohamed[no abstract available]
- ItemDesign, implementation, evaluation and application of a 32-channel radio frequency signal generator for thermal magnetic resonance based anti-cancer treatment(Basel : MDPI AG, 2020) Han, Haopeng; Eigentler, Thomas Wilhelm; Wang, Shuailin; Kretov, Egor; Winter, Lukas; Hoffmann, Werner; Grass, Eckhard; Niendorf, ThoralfThermal Magnetic Resonance (ThermalMR) leverages radio frequency (RF)-induced heating to examine the role of temperature in biological systems and disease. To advance RF heating with multi-channel RF antenna arrays and overcome the shortcomings of current RF signal sources, this work reports on a 32-channel modular signal generator (SGPLL). The SGPLL was designed around phase-locked loop (PLL) chips and a field-programmable gate array chip. To examine the system properties, switching/settling times, accuracy of RF power level and phase shifting were characterized. Electric field manipulation was successfully demonstrated in deionized water. RF heating was conducted in a phantom setup using self-grounded bow-tie RF antennae driven by the SGPLL. Commercial signal generators limited to a lower number of RF channels were used for comparison. RF heating was evaluated with numerical temperature simulations and experimentally validated with MR thermometry. Numerical temperature simulations and heating experiments controlled by the SGPLL revealed the same RF interference patterns. Upon RF heating similar temperature changes across the phantom were observed for the SGPLL and for the commercial devices. To conclude, this work presents the first 32-channel modular signal source for RF heating. The large number of coherent RF channels, wide frequency range and accurate phase shift provided by the SGPLL form a technological basis for ThermalMR controlled hyperthermia anti-cancer treatment. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
- ItemLow Complexity Radar Gesture Recognition Using Synthetic Training Data(Basel : MDPI, 2022) Zhao, Yanhua; Sark, Vladica; Krstic, Milos; Grass, EckhardDevelopments in radio detection and ranging (radar) technology have made hand gesture recognition feasible. In heat map-based gesture recognition, feature images have a large size and require complex neural networks to extract information. Machine learning methods typically require large amounts of data and collecting hand gestures with radar is time- and energy-consuming. Therefore, a low computational complexity algorithm for hand gesture recognition based on a frequency-modulated continuous-wave (FMCW) radar and a synthetic hand gesture feature generator are proposed. In the low computational complexity algorithm, two-dimensional Fast Fourier Transform is implemented on the radar raw data to generate a range-Doppler matrix. After that, background modelling is applied to separate the dynamic object and the static background. Then a bin with the highest magnitude in the range-Doppler matrix is selected to locate the target and obtain its range and velocity. The bins at this location along the dimension of the antenna can be utilised to calculate the angle of the target using Fourier beam steering. In the synthetic generator, the Blender software is used to generate different hand gestures and trajectories and then the range, velocity and angle of targets are extracted directly from the trajectory. The experimental results demonstrate that the average recognition accuracy of the model on the test set can reach 89.13% when the synthetic data are used as the training set and the real data are used as the test set. This indicates that the generation of synthetic data can make a meaningful contribution in the pre-training phase.
- ItemPräzise Lokalisierung und Breitband-Kommunikation im 60-GHz-Band - PreLocate, Teilvorhaben: HF-Chips und Basisbandverarbeitung für Lokalisierung und Kommunikation im 60- GHz-Band (PreLocate-IHP) : Schlussbericht ; Projektlaufzeit: 01.10.2011 bis 31.07.2014(Hannover : Technische Informationsbibliothek (TIB), 2015) Grass, Eckhard; Tittelbach-Helmrich, Klaus; Sark, Vladica; Ehrig, MarcusFür zahlreiche Anwendungen im Bereich mobile drahtlose Kommunikation besteht der Bedarf nach einer genauen Lokalisierung mobiler Terminals. Dabei ist oft eine zentimetergenaue Lokalisierung bei gleichzeitiger Datenübertagung mit Raten von > 1 Gb/s notwendig. Auf Grund der hohen verfügbaren Bandbreite eignen sich dafür Funksysteme im mm-Wellen Bereich und insbesondere im 60-GHz-Band hervorragend. Am IHP wurde ein HF-Chip-Satz für 60 GHz Übertragung mit Beamsteering-Funktionalität entwickelt. Des Weiteren wurde ein OFDM Basisband-Prozessor für Übertragungsraten bis zu 3,6 Gb/s entwickelt. Dieser wurde mit einem Verfahren zur Entfernungsmessung erweitert. Die Steuerung von Datenübertragung und Entfernungsmessung erfolgt über einen speziellen MAC Prozessor. Beide Funktionen laufen im zeitmultiplex quasi-gleichzeitig ab. Zum Nachweis der Funktionalität der gleichzeitigen Datenübertragung und Lokalisierung wurde ein FPGA-basierter Demonstrator entwickelt und mehrfach ausgestellt.
- ItemSchichtenübergreifender Entwurf eines Höchstgeschwindigkeits-WLAN: Konzept, SoC-Implementierung und Demonstrator (WIGWAM-IHP) : Schlussbericht(Hannover : Technische Informationsbibliothek (TIB), 2008) Grass, Eckhard[no abstract available]
- ItemSynchronization in 5G networks: a hybrid Bayesian approach toward clock offset/skew estimation and its impact on localization(Heidelberg : Springer, 2021) Goodarzi, Meysam; Cvetkovski, Darko; Maletic, Nebojsa; Gutiérrez, Jesús; Grass, EckhardClock synchronization has always been a major challenge when designing wireless networks. This work focuses on tackling the time synchronization problem in 5G networks by adopting a hybrid Bayesian approach for clock offset and skew estimation. Furthermore, we provide an in-depth analysis of the impact of the proposed approach on a synchronization-sensitive service, i.e., localization. Specifically, we expose the substantial benefit of belief propagation (BP) running on factor graphs (FGs) in achieving precise network-wide synchronization. Moreover, we take advantage of Bayesian recursive filtering (BRF) to mitigate the time-stamping error in pairwise synchronization. Finally, we reveal the merit of hybrid synchronization by dividing a large-scale network into local synchronization domains and applying the most suitable synchronization algorithm (BP- or BRF-based) on each domain. The performance of the hybrid approach is then evaluated in terms of the root mean square errors (RMSEs) of the clock offset, clock skew, and the position estimation. According to the simulations, in spite of the simplifications in the hybrid approach, RMSEs of clock offset, clock skew, and position estimation remain below 10 ns, 1 ppm, and 1.5 m, respectively.