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Giuseppe Michetti’s PhD Dissertation Defense
November 8, 2022 @ 3:30 pm - 4:30 pm
“RF Front-End Components based on Linear-Time-Variant Modulation of Piezoelectric MEMS Resonators”
Throughout the last decade, radio frequency (RF) components for over-the-air communication and sensing have been subject to sustained market pressure to adapt to the novel trends such as spectrum sharing, programmability, and low-power operation. When these features are required in chip-scale RF hardware, innovative solutions are necessary as conventional materials and techniques become bottlenecks for next-generation radios. In this work, we explore advanced wave manipulation circuital techniques such as Linear-Time-Variant (LTV) networks in conjunction with high-performance RF passives based on Micro-Electro-Mechanical Systems (MEMS) to address some of these challenges. Leveraging the unique spectral characteristic of RF MEMS resonators, we show some components based on LTV concepts, for novel RF systems with advanced spectral efficiency and real-time reconfigurability.
Using AlN and ScAlN thin film MEMS resonators as building blocks, we propose a design technique for MEMS-based LTV Circulators and Self Interference Cancelers, enabling chip-scaled RF full-duplex systems to enable efficient use of the RF spectrum with up to 47.5 dB cancellation in an 8 % bandwidth (BW) at 450 MHz. We introduce and validate experimentally MEMS-based LTV BW-tunable filters with high linearity (>30 dBm), and 5:1 BW tunability, designed for several bands from 100 MHz to 2.7 GHz for emerging paradigms such as software-defined-radios and cooperative networks. We also introduce MEMS-based near-zero energy RF front-end for the Internet-of-Things (IoT), implementing RF energy harvesting to power up a resonant Wake-Up Receiver circuit, with an experimental demonstration at (800 MHz) for deployment in remote sensor networks and emerging IoT wearable applications.
Along with the experimental validation of the proposed components, analytical and numerical tools are also discussed for future development and research.
Prof. Matteo Rinaldi (Advisor)
Prof. Cristian Cassella
Prof. Andrea Alù