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<p>This paper introduces a state-of-the-art K-band radio-frequency microelectromechanical systems (RF MEMS) reconfigurable front-end architecture that integrates a low-actuation-voltage capacitive shunt switch with adaptive filter and beam-steering phased array capabilities. The proposed design presents a new graphene–polymer nanodielectric layer, which has ultralow pull-in voltages less than 15 V and has the best RF characteristics, including greater than 50&#xa0;dB isolation and less than 0.2 dB insertion loss up to 27 GHz. The electromechanical model built by adopting modified Euler–Bernoulli beam theory and coupled-field electrostatic analysis can precisely predict the dynamic switching response of the device, as well as its capacitance tunability, and provides a profound understanding of the stability and reliability of the operation of the device. The experimental results indicate a high degree of correlation between model and experimental results and the performance of the nanodielectric integration, which confirms the strength of the novel design. The MEMS switches are additionally integrated into a tunable bandpass filter network, which is center-frequency-reconfigurable between 20 GHz and 26 GHz and has a tuning bandwidth of up to 600 MHz. Furthermore, cascaded switch networks are used in beam steering (digitally controlled phase shifters), which can be finely phase-resolved at 11.25°/bit with a ±60° angular range. Experimental verification was validated by electromagnetic and multiphysics simulation, demonstrating outstanding linearity, compactness, and spectral agility throughout the K-band. The given system, therefore, creates a new low-voltage and high-linearity platform for next-generation adaptive radar, satellite communication, and high-resolution imaging systems, and deals with essential issues involving the design of scalable, reconfigurable RF front-end modules.</p>

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Hybrid Nanocomposite Enhanced RF MEMS Shunt Switches integrated into a Modular Reconfigurable Tunable Filter Architecture for Beam-Steerable Phased Arrays

  • 期刊论文

  • 发表日期：

    2026年1月12日

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  • Y. Anusha,
  • Koushik Guha,
  • Kavicharan Mummaneni,
  • Jagadeesh Thati

摘要

This paper introduces a state-of-the-art K-band radio-frequency microelectromechanical systems (RF MEMS) reconfigurable front-end architecture that integrates a low-actuation-voltage capacitive shunt switch with adaptive filter and beam-steering phased array capabilities. The proposed design presents a new graphene–polymer nanodielectric layer, which has ultralow pull-in voltages less than 15 V and has the best RF characteristics, including greater than 50 dB isolation and less than 0.2 dB insertion loss up to 27 GHz. The electromechanical model built by adopting modified Euler–Bernoulli beam theory and coupled-field electrostatic analysis can precisely predict the dynamic switching response of the device, as well as its capacitance tunability, and provides a profound understanding of the stability and reliability of the operation of the device. The experimental results indicate a high degree of correlation between model and experimental results and the performance of the nanodielectric integration, which confirms the strength of the novel design. The MEMS switches are additionally integrated into a tunable bandpass filter network, which is center-frequency-reconfigurable between 20 GHz and 26 GHz and has a tuning bandwidth of up to 600 MHz. Furthermore, cascaded switch networks are used in beam steering (digitally controlled phase shifters), which can be finely phase-resolved at 11.25°/bit with a ±60° angular range. Experimental verification was validated by electromagnetic and multiphysics simulation, demonstrating outstanding linearity, compactness, and spectral agility throughout the K-band. The given system, therefore, creates a new low-voltage and high-linearity platform for next-generation adaptive radar, satellite communication, and high-resolution imaging systems, and deals with essential issues involving the design of scalable, reconfigurable RF front-end modules.