LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Automatic Extraction of Measurement-Based Large-Signal FET Models by Nonlinear Function Sampling

Photo from wikipedia

A new method is proposed for the accurate experimental characterization and fully automated extraction of compact nonlinear models for field-effect transistors (FETs). The approach, which leads to a charge-conservative description,… Click to show full abstract

A new method is proposed for the accurate experimental characterization and fully automated extraction of compact nonlinear models for field-effect transistors (FETs). The approach, which leads to a charge-conservative description, is based on a single large-signal measurement under a two-tone sinusoidal wave excitation. A suitable choice of tone frequencies, amplitudes, and bias allows to adequately characterize the transistor over the whole safe operating region. The voltage-controlled nonlinear functions describing the two-port FET model can be computed over an arbitrarily dense voltage domain by solving an overdetermined system of linear equations. These equations are expressed in terms of a new nonlinear function sampling operator based on a biperiodic Fourier series description of the acquired frequency spectra. The experimental validation is carried out on a 0.25- $\mu \text{m}$ gallium nitride (GaN) on silicon carbide (SiC) high-electron-mobility transistor (HEMT) under continuous-wave (CW) and two-tone excitation (intermodulation distortion test).

Keywords: nonlinear function; large signal; extraction; measurement; function sampling

Journal Title: IEEE Transactions on Microwave Theory and Techniques
Year Published: 2020

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.