Mehmet Emin Arslan

Reconfigurable intelligent surfaces (RISs) play a significant role in 6G wireless communications by dynamically controlling the reflections of electromagnetic (EM) waves. In this work, p-i-n diodes are used to achieve the necessary phase shifts in the 1-bit RIS unit cells. In order to characterize these diodes over a frequency range from 10 to 30 GHz, de-embedding structures are carefully designed and analytically modeled. By de-embedding the test structure and matching the model parameters with empirical measurements, the behavior of p-i-n diodes within RIS unit cells is accurately determined. The developed characterization method can be easily adapted to other RF measurement tasks involving complex designs at high frequencies, thus broadening its applicability.

With the rising need for robustness and safety in 5G / 6G backhaul communication between radio units, the significance of reconfigurable intelligent surfaces (RIS) becomes crucial. While several studies have addressed RIS application scenarios between radio unit and user equipment, there is currently a lack of published research on implementing RIS in a wireless backhaul system, strategically managed by a software-defined network (SDN). This paper investigates the factors that influence RIS realization and application, such as gain, far field, losses and communication metrics. Moreover, application and scaled-down demo scenarios are proposed: 2m × 2m for real-life backhaul applications, and 10cm × 10cm for the demo case operating at 28 GHz. The paper also explores application scenarios, including enhancing physical layer security, improving system resilience, and temporarily increasing capacity by deploying RIS in a wireless backhaul system. Additionally, the study explores the dynamic SDN aspects of controlling the entire wireless backhaul system, offering a comprehensive perspective on RIS integration. These findings underscore the importance of RIS in addressing key challenges in wireless communications.

In this work, different analytical methods for calculating the mechanical stresses in the rotors of permanent magnet machines are presented. The focus is on interior permanent magnet machines. First, an overview of eight different methods from the literature is given. Specific differences are pointed out, and a brief summary of the analytical approach for each method is provided. For reference purposes, a finite element model is created and simulated for each rotor geometry studied. A total of seven rotors rom representative automotive powertrains are considered in their specific speed range. The analytical methods are used to determine the maximum mechanical stress concentration factors for the seven rotor geometries, in which we are determined to find maximum mechanical stress as a final step of the analytical process. For each geometry and each respective operating speed range, the deviations from the finite element reference are determined. In addition, the error in the selected geometry variations is evaluated. A recommendation for the method with the lowest error considering all cases studied is given specifically for the stress in the airgap bridge and the central bridge.