System-level characterization of bias noise effects on electrostatic RF MEMS tunable filters
Date of this Version
1-23-2011Citation
System-level characterization of bias noise effects on electrostatic RF MEMS tunable filters Xiaoguang Liu; Kenle Chen; Linda P. B. Katehi; William J. Chappell; Dimitrios Peroulis 2011 IEEE 24th International Conference on Micro Electro Mechanical Systems Year: 2011 Pages: 797 - 800
Abstract
This paper presents the first system-level characterization of the effects of bias noise on the performance of high-Q electrostatic RF MEMS tunable filters. By looking at the system-level performance of such a tunable filter, this paper shows that bias noise, if not well controlled, can degrade the RF performance of the tunable filter. Quantified by error vector magnitude measurement, such system level degradation due to bias noise is found to be dependent on the frequency and amplitude of the noise signals.
Discipline(s)
Nanoscience and Nanotechnology