Statistical design and optimization for adaptive post-silicon tuning of MEMS filters

Large-scale process variations can significantly limit the practical utility of microelectro-mechanical systems (MEMS) for RF (radio frequency) applications. In this paper we describe a novel technique of adaptive post-silicon tuning to reliably design MEMS filters that are robust to process variations. Our key idea is to implement a number of redundant MEMS resonators to form an array and then optimally select a subset of these resonators to achieve the desired frequency response. Several new CAD algorithms and methodologies are proposed to optimize and configure the design variables of the proposed MEMS resonator array. A MEMS design example demonstrates that the proposed post-silicon tuning is able to reduce the ripple of the channel filter gain by 7× over other traditional approaches. Categories and Subject Descriptors B.7.2 [Integrated Circuits]: Design Aids – Verification General Terms Algorithms Keywords MEMS Filter, Process Variation

• Type: Journal
• Year: 2012
• Where: DAC
• Authors: Fa Wang, Gokce Keskin, Andrew Phelps, Jonathan Rotner, Xin Li, Gary K. Fedder, Tamal Mukherjee, Lawrence T. Pileggi
• Keywords: Computer Architecture, DAC 2012, Integrated Circuits Design, Radio Frequency Applications, Rf Radio Frequency