X-Band Miniature Filters Using Lithium Niobate Acoustic Resonators and Bandwidth Widening Technique

Yansong Yang, Liuqing Gao, Songbin Gong

Research output: Contribution to journalArticlepeer-review

Abstract

This work presents a class of micro-electro-mechanical system (MEMS)-driven radio frequency filters in the X-band. The X-band center frequencies are achieved by resorting to the third-order antisymmetric Lamb wave mode (A3) in a 650-nm-thick Z-cut lithium niobate thin film. A novel bandwidth (BW) widening technique based on using the self-inductance of the top interdigital transducers and bus lines is proposed to overcome the limitations set by the electromechanical coupling ( {k} _{t}^{2} ) and satisfy the demands in miniaturization and wide BW. Four different designs of the filters are designed and fabricated to show the trade-off among BW, insertions loss (IL), out-of-band rejections, and footprint. Due to the spurious-free and high- {Q} performance of the A3 lithium niobate resonators, the fabricated A3 lithium niobate filters have demonstrated small in-band ripples and sharp roll-offs. One of these fabricated has demonstrated a 3-dB BW of 190 MHz, an IL of 1.5 dB, and a compact footprint of 0.56 mm2. Another design is fabricated to demonstrate a 3-dB BW of 170 MHz, an IL of 2.5 dB, an out-of-band rejection of 28 dB, and a compact footprint of 1 mm2.

Original languageEnglish (US)
Article number9337207
Pages (from-to)1602-1610
Number of pages9
JournalIEEE Transactions on Microwave Theory and Techniques
Volume69
Issue number3
DOIs
StatePublished - Mar 2021

Keywords

  • 5G wireless communications
  • Acoustic filters
  • Internet of things
  • antisymmetric lamb waves
  • bandwidth (BW) widening
  • lithium niobate
  • micro-electro-mechanical system (MEMS)
  • self-inductance

ASJC Scopus subject areas

  • Radiation
  • Condensed Matter Physics
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'X-Band Miniature Filters Using Lithium Niobate Acoustic Resonators and Bandwidth Widening Technique'. Together they form a unique fingerprint.

Cite this