Description
The reconfigurable intelligent surface (RIS) shown in this work is a programmable metasurface integrated with a dedicated microcontroller that redirects an impinging signal to the desired direction. Its characteristic allows the RIS to act as a mirror for microwave signals. Unlike a perfect electric conductor (PEC), the RIS has much more flexibility in redirecting signals. This work involves the measurement of a passive, fixed beam, 25x32 element mmWave RIS that operates at 28.5 GHz. Bistatic and monostatic measurement setups are both used to find the radar cross section (RCS) of the RIS. The process of creating the measurement setups and the final measurement results is discussed. The measurement setup is further characterized using the High-Frequency Structure Simulator (HFSS) software and the final measurement results are compared to analytical solutions computed using MATLAB. The first prototype of the RIS has a loss of 8.4 dB when compared to a PEC and is physically curved. There is also a side lobe at the boresight of the RIS board that is only 8 dB less than the main beam in best-case scenario. This curvature causes issues with the monostatic measurement because it changes the phase that arrives at the RIS. The second prototype of the RIS has only 5.84 dB of loss compared to PEC. This measurement setup behaves mostly as expected when comparing the measurement results to the analytical solutions and given the limitations of the setup. A collimating lens was used as a part of the setup which reflects part of the incoming signal. The edge of the lens also causes diffraction. These factors contribute to multipath interference arriving at the receive antenna and increases measurement error. The lens also creates unequal amplitude illumination across the surface of the RIS which changes the RCS pattern. Using the lens allows a more space-efficient setup while still obtaining relatively constant phase illuminating across the RIS board.
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Details
Title
- Beamforming Characterization of a Millimeter-wave Reconfigurable Intelligent Surface
Contributors
- Tjahjadi, Brian (Author)
- Trichopoulos, Georgios C (Thesis advisor)
- Aberle, James T (Committee member)
- Imani, Seyedmohammadreza F (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2022
Resource Type
Collections this item is in
Note
- Partial requirement for: M.S., Arizona State University, 2022
- Field of study: Electrical Engineering