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Stefan Zelenbaba

Publications and source records attributed to Stefan Zelenbaba.

3 recordsLinked to original sources

Real-Time Vehicular Wireless System-Level Simulation

Future automation and control units for advanced driver assistance systems (ADAS) will exchange sensor and kinematic data with nearby vehicles using wireless communication links to improve traffic safety. In this paper we present an accurate real-time system-level simulation for multi-vehicle communication scenarios to support the development and test of connected ADAS systems. The physical and data-link layer are abstracted and provide the frame error rate (FER) to a network simulator. The FER is strongly affected by the non-stationary doubly dispersive fading process of the vehicular radio communication channel. We use a geometry-based stochastic channel model (GSCM) to enable a simplified but still accurate representation of the non-stationary vehicular fading process. The propagation path parameters of the GSCM are used to efficiently compute the time-variant condensed radio channel parameters per stationarity region of each communication link during run-time. Five condensed radio channel parameters mainly determine the FER forming a parameter vector: path loss, root mean square delay spread, Doppler bandwidth, $K$-factor, and line-of-sight Doppler shift. We measure the FER for a pre-defined set of discrete grid points of the parameter vector using a channel emulator and a given transmitter-receiver modem pair. The FER data is stored in a table and looked up during run-time of the real-time system-level simulation. We validate our methodology using empirical measurement data from a street crossing scenarios demonstrating a close match in terms of FER between simulation and measurement.

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Towards Cell-Free Massive MIMO: A Measurement-Based Analysis

Cell-free widely distributed massive multiple-input multiple-output (MIMO) systems utilize radio units spread out over a large geographical area. The radio signal of a user equipment (UE) is coherently detected by a subset of radio units (RUs) in the vicinity of the UE and processed jointly at the nearest baseband processing unit (BPU). This architecture promises two orders of magnitude less transmit power, spatial focusing at the UE position for high reliability, and consistent throughput over the coverage area. All these properties have been investigated so far from a theoretical point of view. To the best of our knowledge, this work presents the first empirical radio wave propagation measurements in the form of time-variant channel transfer functions for a linear, widely distributed antenna array with 32 single antenna RUs spread out over a range of 46.5 m. The large aperture allows for valuable insights into the propagation characteristics of cell-free systems. Three different co-located and widely distributed RU configurations and their properties in an urban environment are analyzed in terms of time-variant delay-spread, Doppler spread, path loss and the correlation of the local scattering function over space. For the development of 6G cell-free massive MIMO transceiver algorithms, we analyze properties such as channel hardening, channel aging as well as the signal to interference and noise ratio (SINR). Our empirical evidence supports the promising claims for widely distributed cell-free systems.

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Multi-Node Vehicular Wireless Channels: Measurements, Large Vehicle Modelling, and Hardware-in-the-Loop Evaluation

Understanding multi-node vehicular wireless communication channels is crucial for future time-sensitive safety applications for human-piloted as well as partly autonomous vehicles on roads, railways and in the air. These highly dynamic wireless communication channels are characterized by rapidly changing channel statistics. In this paper we present the first fully mobile multi-node vehicular wireless channel sounding system, which is capable of simultaneously capturing multiple channel frequency responses, ensuring that measurement conditions are identical for all observed links. We use it to analyze road scenarios with multiple vehicles and a large obstructing double-decker bus. The empirical measurement data is used to parametrize a model for the large obstructing vehicle within a geometry-based stochastic channel model. We compare the time-variant channel statistics obtained from our channel model with the ones from the measurement campaign. By means of a channel emulator we obtain the packet error rates of commercial modems for the measured and the simulated wireless communication channels and compare them, in order to validate the model at the link level. We find that the path loss, the root mean square (RMS) delay spread, and the RMS Doppler spread deviate by less than $3.6\,\mathrm{dB}$, $78\,\mathrm{ns}$, and $52\,\mathrm{Hz}$, respectively, for $80\%$ of the total simulation duration. The PER obtained from measured data is within the maximum and minimum bounds of our model for $86\%$ of the simulation duration.

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