Taming the Waves: Mixed-Signal Integrated Circuits for Next-Generation Communications, Sensing, and Imaging

Next-generation communication, sensing, and imaging systems will open up more applications with various data rates from 10 Kbit/s to 10 Tbit/s. These heterogeneous networks with increasing data volume will enable many distinct future applications. However, we start to see the total power consumption increase dramatically with massive data transmission. On the other hand, conventional sensing and imaging technologies, including nuclear magnetic resonance (NMR) spectrometers and magnetic resonance imaging (MRI), are bulky and power-hungry. Therefore, innovations from semiconductor devices, integrated circuits (IC), and hardware architectures are critical for enabling energy-efficient communications, sensing, and imaging.

In this talk, I will present my explorations on novel mixed-signal integrated circuits techniques to address the increasing power consumption in various wireless hardware systems. Starting from IC design, I will first discuss a new “mixed-signal transmitter family”, the subharmonic switching digital transmitter architecture that vastly enhances power amplifier and transmitter efficiency from RF to mm-wave frequencies. Based on the proposed architecture, I will walk the audience through several benchmarking designs with silicon prototypes and measurement results. Secondly, I will introduce the non-uniform sampling receiver architecture, high-speed low-power ADCs, and new computing platforms with two-dimensional semiconductor devices by leveraging digital signal processing and mixed-signal circuits techniques to further reduce the power consumption in the receiver path. Then I will switch gears to sensing systems. I will discuss the miniaturized CMOS and GaN-based on-chip sensing systems for NMR molecular fingerprinting, MRI, and quantum sensing. The proposed sensing and imaging systems can largely minimize the size of commercial MRI machines and improve the sensing resolution capable of J-resolved spectroscopy and single-cell volume imaging. Finally, I will conclude this talk with my vision of future research directions for developing mixed-signal circuits techniques in next-generation communications, new circuit topologies with two-dimensional devices, and chip-scale sensing systems for quantum sensing, biotechnology, and subsurface imaging.

Dr. Aoyang Zhang

Post-doctoral Fellow, Harvard University on March 10, 2023 at 10:15 AM in EB2 3002

Aoyang Zhang is currently a postdoctoral fellow at Harvard University. He received the B.S. degree from Zhejiang University, Hangzhou, China, in 2014 and the Ph.D. degree from the University of Southern California, Los Angeles, in 2020, all in electrical engineering.

His current research interests include threefold. First, Analog/Mixed-Signal/RF integrated circuits (IC) design for energy efficient communications. Second, scalable nuclear magnetic resonance (NMR) and electron spin resonance (ESR) based CMOS and GaN chip-scale quantum sensing and wireless sensing integrated systems for biological sensing, molecular fingerprinting, and subsurface imaging. Third, new circuit architecture with two-dimensional (2D) memristive devices to overcome technological limitations in computational complexity and power consumption.

Dr. Zhang was the recipient of the 2022 Harvard Teaching Award, 2021 USC Best Dissertation Award in Electrical Engineering, 2020-2021 IEEE Solid-State Circuits Society (SSCS) Predoctoral achievement award, Ming Hsieh Institute Scholar in 2020, IEEE SSCS Student Travel Grant Award (STGA) in 2018, Best Bachelor Thesis Award in 2014, and the first prize of Chinese National Mathematical Competition in 2010.

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