arXiv subjects

Heinz Mathis

Publications and source records attributed to Heinz Mathis.

3 recordsLinked to original sources

arXiv2025

Reducing Simulation Effort for RIS Optimization using an Efficient Far-Field Approximation

Optimization of Reconfigurable Intelligent Surfaces (RIS) via a previously introduced method is effective, but time-consuming, because multiport impedance or scatter matrices are required for each transmitter and receiver position, which generally must be obtained through full-wave simulation. Herein, a simple and efficient far-field approximation is introduced, to extrapolate scatter matrices for arbitrary receiver and transmitter positions from only a single simulation while still maintaining high accuracy suitable for optimization purposes. This is demonstrated through comparisons of the optimized capacitance values and further supported by empirical measurements.

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arXiv2024

Validating Convex Optimization of Reconfigurable Intelligent Surfaces via Measurements

Reconfigurable Intelligent Surfaces (RISs) can be designed in various ways. A previously proposed semidefinite relaxation-based optimization method for maximizing power transfer efficiency showed promise, but earlier results were only theoretical. This paper evaluates a small RIS at 3.55GHz, the center of the 5G band "n78", for practical verification of this method. The presented results not only empirically confirm the desired performance of the optimized RIS, but also affirm the optimality of the resulting reactance values. Additionally, this paper discusses several practical aspects of RIS design and measurement, such as the operation of varactor diodes and time gating to omit the direct line-of-sight (LOS) path.

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arXiv2023

Investigating Sparse Reconfigurable Intelligent Surfaces (SRIS) via Maximum Power Transfer Efficiency Method Based on Convex Relaxation

Reconfigurable intelligent surfaces (RISs) are widely considered to become an integral part of future wireless communication systems. Various methodologies exist to design such surfaces; however, most consider or require a very large number of tunable components. This not only raises system complexity, but also significantly increases power consumption. Sparse RISs (SRISs) consider using a smaller or even minimal number of tunable components to improve overall efficiency while maintaining sufficient RIS capability. The versatile semidefinite relaxation-based optimization method previously applied to transmit array antennas is adapted and applied accordingly, to evaluate the potential of different SRIS configurations. Because the relaxation is tight in all cases, the maximum possible performance is found reliably. Hence, with this approach, the trade-off between performance and sparseness of SRIS can be analyzed. Preliminary results show that even a much smaller number of reconfigurable elements, e.g. only 50%, can still have a significant impact.

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