2018Unpublished venueRequires access

Non-Quasi-Static Large-Signal Model for RF LDMOS Power Transistors

Lei Zhang, Hernan Rueda, Kevin Kim, Peter H. Aaen

Open publisher page 2 citations

Abstract

In this paper, we propose a non-quasi-static large-sig-nal model to capture the high-frequency dispersion exhibited by laterally diffused metal-oxide semiconductor (LDMOS) devices. We show that industry-standard nonlinear large-signal models for LDMOS based on quasi-static assumptions are not sufficient for high-efficiency designs at frequencies higher than 2 GHz. This dispersive behavior results from the combination of high-frequency operation and the lengthened drain extension region that is needed to support high-voltage operation. To improve the model accuracy, higher-order current and charge components, which are directly integrated from bias-dependent S-parameter data, are included in the model. The non-quasi-static large-signal model improves the efficiency and gain predictions by 10% and 0.5 dB at 3.5 GHz. These improvements in accuracy are essential for power amplifier designers to achieve the performance targets necessary for 4G and upcoming 5G designs.

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What this paper is about

In this paper, we propose a non-quasi-static large-sig-nal model to capture the high-frequency dispersion exhibited by laterally diffused metal-oxide semiconductor (LDMOS) devices. We show that industry-standard nonlinear large-signal models for LDMOS based on quasi-static assumptions are not sufficient for high-efficiency designs at frequencies higher than 2 GHz. This dispersive behavior results from the combination of high-frequency operation and the lengthened drain extension region that is needed to support high-voltage operation. To improve the model accuracy, higher-order current and charge components, which are directly integrated from bias-dependent S-parameter data, are included in the model. The non-quasi-static large-signal model improves the efficiency and gain predictions by 10% and 0.5 dB at 3.5 GHz. These improvements in accuracy are essential for power amplifier designers to achieve the performance targets necessary for 4G and upcoming 5G designs.

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Available abstract

In this paper, we propose a non-quasi-static large-sig-nal model to capture the high-frequency dispersion exhibited by laterally diffused metal-oxide semiconductor (LDMOS) devices. We show that industry-standard nonlinear large-signal models for LDMOS based on quasi-static assumptions are not sufficient for high-efficiency designs at frequencies higher than 2 GHz. This dispersive behavior results from the combination of high-frequency operation and the lengthened drain extension region that is needed to support high-voltage operation. To improve the model accuracy, higher-order current and charge components, which are directly integrated from bias-dependent S-parameter data, are included in the model. The non-quasi-static large-signal model improves the efficiency and gain predictions by 10% and 0.5 dB at 3.5 GHz. These improvements in accuracy are essential for power amplifier designers to achieve the performance targets necessary for 4G and upcoming 5G designs.

Key concepts: LDMOS, Large-signal model, Amplifier, Transistor, SIGNAL (programming language), Quasistatic process, Nonlinear system, Radio frequency

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