Capacitive-Gap MEMS Resonator-Based Oscillator Systems for Low-Power Signal Processing

Thura Lin Naing

EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2017-14
May 1, 2017

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-14.pdf

Wireless technology, which already plays a major part in our daily lives, is expected to further expand to networks of billions of autonomous sensors in coming years: the so-called Internet of Things. In one vision, sensors employing low-cost, low-power wireless motes collect and transmit data through a mesh network while operating only on scavenged or battery power. RF MEMS provides one approach to the stringent power and performance required by sensor networks.

This dissertation presents improvement to these MEMS technologies and introduces new approaches for wireless communication in low power wireless networks. First, this work presents oscillators based on the capacitive-gap transduced MEMS resonator. As wireless radio needs at least one such oscillator, the space and power savings offered by these MEMS oscillators make them compelling alternatives over bulky quartz-based devices. The high quality factors (Q) > 100,000 possible in these on-chip resonators allow for phase noise performance of the oscillator exceeding even the challenging GSM specifications using less than 100 uW of power consumption. Despite their small size and tiny capacitive gaps, MEMS-based oscillators are found to be insensitive to vibration and achieve only a few ppm shift in frequency over 10 months of measurement: the performance shown is on par or better than the off-the-shelf crystal oscillators. Interestingly, exploiting nonlinearities in the MEMS resonators also allows multiple simultaneous oscillation frequencies using one amplifier. Combined with electrical stiffness-based frequency tuning, this enables Frequency-Shift Keyed modulation of the output waveform, offering a space and power-efficient multichannel transmitter, as desired for mobile applications requiring long battery life.

Intrinsically, oscillator systems involve positive feedback loops, which regeneratively amplify signals in the loop. Taking advantage of this property, MEMS oscillator systems may be used for other wireless signal processing applications. This dissertation explores such systems applied to: 1) a narrow channel-select filter with low insertion loss unachievable using passive resonators only and 2) a super-regenerative amplification-based channel-selecting radio transceiver. Finally, this dissertation presents two capacitive-gap transduced micromechanical resonator designs which can achieve the high Q at GHz frequencies needed for many wireless communication standards. The methods and solutions provided here pave a path towards realization of future low-power wireless technologies.

Advisor: Clark Nguyen and Elad Alon


BibTeX citation:

@phdthesis{Naing:EECS-2017-14,
    Author = {Naing, Thura Lin},
    Title = {Capacitive-Gap MEMS Resonator-Based Oscillator Systems for Low-Power Signal Processing},
    School = {EECS Department, University of California, Berkeley},
    Year = {2017},
    Month = {May},
    URL = {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-14.html},
    Number = {UCB/EECS-2017-14},
    Abstract = {Wireless technology, which already plays a major part in our daily lives, is expected to further expand to networks of billions of autonomous sensors in coming years: the so-called Internet of Things. In one vision, sensors employing low-cost, low-power wireless motes collect and transmit data through a mesh network while operating only on scavenged or battery power. RF MEMS provides one approach to the stringent power and performance required by sensor networks.

This dissertation presents improvement to these MEMS technologies and introduces new approaches for wireless communication in low power wireless networks. First, this work presents oscillators based on the capacitive-gap transduced MEMS resonator. As wireless radio needs at least one such oscillator, the space and power savings offered by these MEMS oscillators make them compelling alternatives over bulky quartz-based devices. The high quality factors (Q) > 100,000 possible in these on-chip resonators allow for phase noise performance of the oscillator exceeding even the challenging GSM specifications using less than 100 uW of power consumption. Despite their small size and tiny capacitive gaps, MEMS-based oscillators are found to be insensitive to vibration and achieve only a few ppm shift in frequency over 10 months of measurement: the performance shown is on par or better than the off-the-shelf crystal oscillators. Interestingly, exploiting nonlinearities in the MEMS resonators also allows multiple simultaneous oscillation frequencies using one amplifier. Combined with electrical stiffness-based frequency tuning, this enables Frequency-Shift Keyed modulation of the output waveform, offering a space and power-efficient multichannel transmitter, as desired for mobile applications requiring long battery life.

Intrinsically, oscillator systems involve positive feedback loops, which regeneratively amplify signals in the loop. Taking advantage of this property, MEMS oscillator systems may be used for other wireless signal processing applications. This dissertation explores such systems applied to: 1) a narrow channel-select filter with low insertion loss unachievable using passive resonators only and 2) a super-regenerative amplification-based channel-selecting radio transceiver. Finally, this dissertation presents two capacitive-gap transduced micromechanical resonator designs which can achieve the high Q at GHz frequencies needed for many wireless communication standards. The methods and solutions provided here pave a path towards realization of future low-power wireless technologies.}
}

EndNote citation:

%0 Thesis
%A Naing, Thura Lin
%T Capacitive-Gap MEMS Resonator-Based Oscillator Systems for Low-Power Signal Processing
%I EECS Department, University of California, Berkeley
%D 2017
%8 May 1
%@ UCB/EECS-2017-14
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-14.html
%F Naing:EECS-2017-14