Kaiserslautern - Fachbereich Elektrotechnik und Informationstechnik
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Modern society relies on convenience services and mobile communication. Cloud computing is the current trend to make data and applications available at any time on every device. Data centers concentrate computation and storage at central locations, while they claim themselves green due to their optimized maintenance and increased energy efficiency. The key enabler for this evolution is the microelectronics industry. The trend to power efficient mobile devices has forced this industry to change its design dogma to: ”keep data locally and reduce data communication whenever possible”. Therefore we ask: is cloud computing repeating the aberrations of its enabling industry?
Sensing location information in indoor scenes requires a high accuracy and is a challenging task, mainly because of multipath and NLoS (non-line-of-sight) propagation. GNSS signals cannot penetrate well in indoor environment. Satellite-based navigation and positioning systems cannot therefore be used for indoor positioning.. Other technologies have been suggested for indoor usage, among them, Wi-Fi (802.11) and 5G NR (New Radio). The primary aim of this study is to discuss the advantages and drawbacks of 5G and Wi-Fi positioning techniques for indoor localization.
We study the sensor fault estimation and accommodation problems in a data-driven \(\mathcal{H}_\infty\) setting, leading to a data-driven sensor fault-tolerant control scheme. First, we formulate the fault estimation problem as a finite-horizon minimax \(\mathcal{H}_\infty\)-optimization problem in a data-driven setup, whose solution yields the fault estimate. The estimated fault is then used for output compensation. This compensated output and the experimental input are used to achieve certain control objectives in a data-driven \(\mathcal{H}_\infty\) setting. Next, the data-driven \(\mathcal{H}_\infty\) fault estimation and control problems are solved using a subspace predictor-based approach. Finally, the proposed algorithm is applied to the steering subsystem of the remotely operated underwater vehicle.
Netzbasierte Automatisierungssysteme (NAS) sind das Ergebnis der zunehmenden Dezentralisierung von Automatisierungssystemen mittels neuerer Netzwerkstrukturen. Eine ganze Fülle von Einflussfaktoren führt jedoch zu einem Spektrum von nicht-deterministischen Verzögerungen, die direkten Einfluss auf Qualität, Sicherheit und Zuverlässigkeit der Automatisierungsanlagen haben. Eine genaue Analyse dieser Einflussfaktoren ist somit nicht nur Voraussetzung für den verantwortungsbewussten Einsatz dieser Technologie sondern ermöglicht es auch, bereits im Vorfeld von Umstrukturierungen oder Erweiterungen Fragen der Verlässlichkeit zu klären. In diesem Beitrag wird gezeigt, welchen Einfluss einzelne Komponenten sowie netzbedingte Verhaltensmodi wie Synchronisation und die gemeinsame Nutzung von Ressourcen auf die Antwortzeiten des Gesamtsystems haben. Zur Analyse wird die wahrscheinlichkeitsbasierte Modellverifikation (PMC) verwendet. Umfangreiche Messungen wurden zur Validierung der Ergebnisse durchgeführt.
Phase-gradient metasurfaces can be designed to manipulate electromagnetic waves according to the generalized Snell’s law. Here, we show that a phased parallel-plate waveguide array (PPWA) can be devised to act in the same manner as a phase-gradient metasurface. We derive an analytic model that describes the wave propagation in the PPWA and calculate both the angle and amplitude distribution of the diffracted waves. The analytic model provides an intuitive understanding of the diffraction from the PPWA. We verify the (semi-)analytically calculated angle and amplitude distribution of the diffracted waves by numerical 3-D simulations and experimental measurements in a microwave goniometer.
Radar cross section reducing (RCSR) metasurfaces or coding metasurfaces were primarily designed for normally incident radiation in the past. It is evident that the performance of coding metasurfaces for RCSR can be significantly improved by additional backscattering reduction of obliquely incident radiation, which requires a valid analytic conception tool. Here, we derive an analytic current density distribution model for the calculation of the backscatter far-field of obliquely incident radiation on a coding metasurface for RCSR. For demonstration, we devise and fabricate a metasurface for a working frequency of 10.66GHz and obtain good agreement between the measured, simulated, and analytically calculated backscatter far-fields. The metasurface significantly reduces backscattering for incidence angles between −40∘ and 40∘ in a spectral working range of approximately 1GHz.
The design of the fifth generation (5G) cellular network should take account of the emerging services with divergent quality of service requirements. For instance, a vehicle-to-everything (V2X) communication is required to facilitate the local data exchange and therefore improve the automation level in automated driving applications. In this work, we inspect the performance of two different air interfaces (i.e., LTE-Uu and PC5) which are proposed by the third generation partnership project (3GPP) to enable the V2X communication. With these two air interfaces, the V2X communication can be realized by transmitting data packets either over the network infrastructure or directly among traffic participants. In addition, the ultra-high reliability requirement in some V2X communication scenarios can not be fulfilled with any single transmission technology (i.e., either LTE-Uu or PC5). Therefore, we discuss how to efficiently apply multi-radio access technologies (multi-RAT) to improve the communication reliability. In order to exploit the multi-RAT in an efficient manner, both the independent and the coordinated transmission schemes are designed and inspected. Subsequently, the conventional uplink is also extended to the case where a base station can receive data packets through both the LTE-Uu and PC5 interfaces. Moreover, different multicast-broadcast single-frequency network (MBSFN) area mapping approaches are also proposed to improve the communication reliability in the LTE downlink. Last but not least, a system level simulator is implemented in this work. The simulation results do not only provide us insights on the performances of different technologies but also validate the effectiveness of the proposed multi-RAT scheme.
Hardware prototyping is an essential part in the hardware design flow. Furthermore, hardware prototyping usually relies on system-level design and hardware-in-the-loop simulations in order to develop, test and evaluate intellectual property cores. One common task in this process consist on interfacing cores with different port specifications. Data width conversion is used to overcome this issue. This work presents two open source hardware cores compliant with AXI4-Stream bus protocol, where each core performs upsizing/downsizing data width conversion.
The fifth-generation mobile telecommunication network is expected to support multi-access edge computing (MEC), which intends to distribute computation tasks and services from the central cloud to the edge clouds. Toward ultra-responsive, ultra-reliable, and ultra-low-latency MEC services, the current mobile network security architecture should enable a more decentralized approach for authentication and authorization processes. This paper proposes a novel decentralized authentication architecture that supports flexible and low-cost local authentication with the awareness of context information of network elements such as user equipment and virtual network functions. Based on a Markov model for backhaul link quality as well as a random walk mobility model with mixed mobility classes and traffic scenarios, numerical simulations have demonstrated that the proposed approach is able to achieve a flexible balance between the network operating cost and the MEC reliability.
The number of sensors used in modern devices is rapidly increasing, and the interaction with sensors demands analog-to-digital data conversion (ADC). A conventional ADC in leading-edge technologies faces
many issues due to signal swings, manufacturing deviations, noise, etc. Designers of ADCs are moving to the
time domain and digital designs techniques to deal with these issues. This work pursues a novel self-adaptive
spiking neural ADC (SN-ADC) design with promising features, e.g., technology scaling issues, low-voltage
operation, low power, and noise-robust conditioning. The SN-ADC uses spike time to carry the information.
Therefore, it can be effectively translated to aggressive new technologies to implement reliable advanced sensory electronic systems. The SN-ADC supports self-x (self-calibration, self-optimization, and self-healing) and
machine learning required for the internet of things (IoT) and Industry 4.0. We have designed the main part of
SN-ADC, which is an adaptive spike-to-digital converter (ASDC). The ASDC is based on a self-adaptive complementary metal–oxide–semiconductor (CMOS) memristor. It mimics the functionality of biological synapses,
long-term plasticity, and short-term plasticity. The key advantage of our design is the entirely local unsupervised
adaptation scheme. The adaptation scheme consists of two hierarchical layers; the first layer is self-adapted, and
the second layer is manually treated in this work. In our previous work, the adaptation process is based on 96 variables. Therefore, it requires considerable adaptation time to correct the synapses’ weight. This paper proposes a
novel self-adaptive scheme to reduce the number of variables to only four and has better adaptation capability
with less delay time than our previous implementation. The maximum adaptation times of our previous work
and this work are 15 h and 27 min vs. 1 min and 47.3 s. The current winner-take-all (WTA) circuits have issues, a
high-cost design, and no identifying the close spikes. Therefore, a novel WTA circuit with memory is proposed.
It used 352 transistors for 16 inputs and can process spikes with a minimum time difference of 3 ns. The ASDC
has been tested under static and dynamic variations. The nominal values of the SN-ADC parameters’ number
of missing codes (NOMCs), integral non-linearity (INL), and differential non-linearity (DNL) are no missing
code, 0.4 and 0.22 LSB, respectively, where LSB stands for the least significant bit. However, these values are
degraded due to the dynamic and static deviation with maximum simulated change equal to 0.88 and 4 LSB and
6 codes for DNL, INL, and NOMC, respectively. The adaptation resets the SN-ADC parameters to the nominal
values. The proposed ASDC is designed using X-FAB 0.35 µm CMOS technology and Cadence tools.