Kongress- und Tagungsbeiträge

Ultrasound Computed Tomography (UCT) is challenging due to phenomena such as strong refraction, multiple scattering, and mode conversion. In NDT, large speed of sound contrasts lead to strong artifacts if such phenomena are not modeled correctly; however, enhanced models are computationally expensive. In this work, a two-step framework for Compressed UCT based on the integral approach to the solution of the Helmholtz equation is presented. It comprises a physically motivated forward step and an imaging step that solves a suitable inverse problem. Multiple scattering is accounted for through the use of Neumann series. Convergence problems of Neumann series in high contrast settings are addressed via Padé approximants. Compressed sensing is employed to reduce the computational complexity of the reconstruction procedure by reducing data volumes directly at the measurement step, avoiding redundancy in the data and allowing the ability to steer the admissible computational effort at the expense of reconstruction quality. The proposed method is shown to yield high quality reconstructions under heavy subsampling in the frequency and spatial domains.

Energy efficiency has recently drawn significant attention in diverse applications, such as vehicle-to-everything (V2X) communications. This paper investigates a joint energy efficiency and sum-rate maximization problem in autonomous resource selection in the 5G new radio (NR) vehicular communication while catering for reliability and latency requirements. An autonomous resource allocation problem is formulated as a ratio of sum-rate to energy consumption, where the objective is to maximize the total energy efficiency of power-saving users subject to the reliability and latency requirements. The energy efficiency problem is a mixed-integer programming optimization problem that is computationally complex when the number of users increases. Therefore, a heuristic algorithm, density of traffic-based resource allocation (DeTRA), is proposed to solve the problem. The traffic density per traffic type is considered a metric to split the radio resources and trigger an appropriate resource selection strategy. The simulation results show that the proposed algorithm outperforms the existing schemes in terms of energy efficiency.

This paper describes a field-programmable gate array (FPGA)-based implementation of a switched multiple input multiple output (MIMO) channel sounder realization by use of software-defined radio (SDR) hardware (NI USRP-2954, X310 series with UBX 160 daughterboard). Essential basic functionalities are the synchronous switching of the antenna elements at both link ends and an integrated automatic gain control (AGC) at the receiver. To meet the high timing requirements in the switched MIMO setup, an FPGA-based AGC is introduced. The detector of the AGC is based on a sample-by-sample calculation of the average and maximum of the I/Q samples within a sliding window. The used SDR hardware allows a minimum AGC update interval of approx. 14 [my]s and a timing accuracy of the antenna switching of 5 ns. Our setup demonstrates the applicability of state-of-the-art SDRs as a sounding system for continuous acquisition of the time-variant, directional mobile radio channel.

The statistical study of target detectability is crucial in radar system design. In this regard, signal-to-noise ratio (SNR) of the received signal at the radars receiver is a key parameter and therefore every influence on SNR should be taken into account. One of the main influences is the fluctuation of the target scattering/reflectivity to the incident electromagnetic wave. Consequently, the target fluctuation models and their accuracy become important. For monostatic radar system, various models can be found in the literature. In contrast, this paper studies a case of vehicular sensing scenario with multistatic configuration for an urban crossroad and proposes a modelling method of the target fluctuation by taking into account the target information, such as size, shape and composed materials, and the wave information, such as polarizations and aspect angles. Furthermore, the derived target fluctuation models are then applied directly to the formulation of the probability of detection for multistatic radar system. These probabilities of detection are also compared to that of monostatic radar system.