RF and Microwave Modeling and Measurement Techniques for Field Effect Transistors
This book is an introduction to microwave and RF signal modeling and measurement techniques for field effect transistors. It assumes only a basic course in electronic circuits and prerequisite knowledge for readers to apply the techniques and improve the performance of integrated circuits, reduce design cycles and increase their chance at first time success. The first chapters offer a general overview and discussion of microwave signal and noise matrices, and microwave measurement techniques. The following chapters address modeling techniques for field effect transistors and cover models such as: small signal, large signal, noise, and the artificial neural network based.
Inspec keywords: measurement systems; microwave field effect transistors
Other keywords: parameter extraction; RF modeling; microwave modeling; compound semiconductor FET; field effect transistors; electronic circuits; small signal; measurement techniques; nonlinear modeling; circuit concepts
Subjects: Solid-state microwave circuits and devices; Insulated gate field effect transistors; Instrumentation and measurement systems
- Book DOI: 10.1049/SBEW027E
- Chapter DOI: 10.1049/SBEW027E
- ISBN: 9781891121890
- e-ISBN: 9781613530900
- Format: PDF
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Front Matter
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1 Introduction
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Semiconductor material systems can be categorized into silicon-based and III-V-compound-semiconductor-based devices. Silicon-based semiconductor devices, with their low-cost, high-volume production, have improved frequency response significantly as the channel length is made smaller and up to 45 nm. In contrast, compound semiconductor-based devices take advantages of their intrinsic material properties and offer superior device performance in high-frequency applications such as monolithic microwave integrated circuits (MMICs). The III-V semiconductor industries have also increased their production yield and integration scale in response to the increasing demand of RF circuits in terrestrial and mobile wireless communications.
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2 Representation of Microwave Two-Port Network
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The microwave signal and noise matrix analysis techniques are the basis of representation of the microwave network, and are the important tools of the radio frequency (RF) and microwave semiconductor modeling and parameter extraction. RF and microwave device, circuit and components can be classified as one-, two-, three-, and N-port networks. A majority of circuits under analysis are two-port networks. Therefore, we focus in this chapter primarily on two-port characterization and study its representation in terms of a set of parameters that can be cast into a matrix format. The definition of a two-port network is that a network that has only two access ports: one for input or excitation and one for output or response. This chapter introduces the important linear parameters (including signal and noise parameters) that are currently used to characterize two-port networks. These parameters enable manipulation and optimization.
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3 Microwave and RF Measurement Techniques
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Three kinds of microwave and RF measurement techniques are commonly used and have been introduced in this chapter. One is the S-parameters measurement technique for small signal device and circuit characterization. The vector network analyzer is the key instrument, and its calibration can be carried out by using error model with SOLT, TRL and LRM methods. Noise figure is a figure of merit in RF systems and components, and can be determined from noise measurement technique by using the Y-factor method. Then the power measurement technique, which includes the power gain compression, harmonic distortion and inter-modulation distortion measurements is introduced.
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4 FET Small Signal Modeling and Parameter
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In this chapter, we introduce small-signal modeling and parameter extraction technique for FETs, an III-V compound semiconductor device pseudomorphic high electron-mobility transistor (PHEMT) is used as an example. The parameter extraction includes pad capacitances, extrinsic inductances, extrinsic resistances, and intrinsic elements extractions.
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5 FET Nonlinear Modeling and Parameter Extraction
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In this chapter, we will introduce the nonlinear model for FETs previously mentioned, and focus on the empirical equivalent-circuit-based model, which consists of the drain-current DC model and nonlinear intrinsic capacitances models.
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6 Microwave Noise Modeling and Parameter
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In this chapter, we introduced the noise modeling and parameter extraction methods for FET device, as well as how to determine noise parameters, including the tuner-based method and the noise figure-based method.
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7 Artificial Neural Network Modeling Technique for FET
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Accurate small-signal and large-signal equivalent-circuit models of microwave active devices (e.g., diodes, FETs and HBTs) are very useful for device performance analysis (e.g., noise, gain) in designing microwave circuits and characterizing the device technological process. Nonlinear models of microwave devices are commonly in terms of state functions such as closed-form equations, Volterra series, or look-up tables. These quantities are classically determined via a small signal detour based on multi-bias S-parameters and DC measurements. The linear equivalent-circuit model is generally more accurate than a linearized nonlinear model for predicting the S-parameters.
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Back Matter
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