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Proceedings ArticleDOI

Small-Signal Modeling of mm- Wave MOSFET up to 110 GHz in 22nm FDSOI Technology

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TLDR
In this paper, a comprehensive analysis on small-signal modeling of mm-wave transistor in 22nm FDSOI technology is presented based on experimental S-parameters up to 110 GHz of a 22FDX® thick-oxide n-MOSFET and analytical parameter extraction approach.
Abstract
In this paper, a comprehensive analysis on small-signal modeling of mm-wave transistor in 22nm FDSOI technology is presented. The model is constructed based on experimental S-parameters up to 110 GHz of a 22FDX® thick-oxide n-MOSFET and analytical parameter extraction approach. The non-quasi static effect is addressed thoroughly in the equivalent circuit model for high frequency validity. The bias-dependent series source and drain resistances are considered to account for the overlap regions between the gate and the highly doped source/drain regions. In addition, a simple RC network is included at the output to model the innegligible substrate coupling at mm-wave frequencies. Excellent agreements between model prediction and measurement are observed in the interested bandwidth for various bias conditions.

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Citations
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Proceedings ArticleDOI

W-Band Noise Characterization with Back-Gate Effects for Advanced 22nm FDSOI mm-Wave MOSFETs

TL;DR: In this paper, the W-band noise performance of the 22nm FDSOI CMOS technology is characterized comprehensively in terms of device geometries using the tuner-based noise measurement approach.
Proceedings ArticleDOI

RF Characterization and Small Signal Extraction of 28nm FDSOI MOSFETs up to 110GHz

TL;DR: In this article , a hybrid cascade de-embedding method was applied to deembed the on-chip external elements of the device test structure associated with the RF pads and access interconnect lines, and the complete extrinsic and intrinsic small-signal parameters were extracted at multi bias points based on the direct parameter extraction approach.
Journal ArticleDOI

Systematic characterization for RF small-signal parameter extraction of 28 nm FDSOI MOSFETs up to 110 GHz

TL;DR: In this paper , two-step and hybrid de-embedding methodologies have been applied and compared for the accurate deembedding of the on-chip RF test pads and access interconnect line elements.
References
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Proceedings ArticleDOI

22nm FDSOI technology for emerging mobile, Internet-of-Things, and RF applications

TL;DR: 22FDX™ is the industry's first FDSOI technology architected to meet the requirements of emerging mobile, Internet-of-Things (IoT), and RF applications and achieves the power and performance efficiency of a 16/14nm FinFET technology in a cost effective, planar device architecture that can be implemented with ∼30% fewer masks.
Journal ArticleDOI

A New Approach for SOI Devices Small-Signal Parameters Extraction

TL;DR: In this article, a method for small-signal parameters determination for a conventional MOSFET high-frequency model and somewhat inspired from methods applied to MESFET technology is presented.
Journal ArticleDOI

MOSFET bias dependent series resistance extraction from RF measurements

TL;DR: In this article, a simple technique to determine MOSFET gate-bias dependent source and drain series resistances from experimental S-parameters is presented, using the measured data of a single device.
Journal ArticleDOI

Assessment of 28 nm UTBB FD-SOI technology platform for RF applications: Figures of merit and effect of parasitic elements

TL;DR: In this paper, a detailed study of 28-nm fully-depleted silicon-on-insulator (FD-SOI) planar ultra-thin body and box (UTBB) MOSFETs for high frequency applications is presented.
Journal ArticleDOI

A method to determine the gate bias-dependent and gate bias-independent components of MOSFET series resistance from S-parameters

TL;DR: In this article, an S-parameter measurement-based procedure for the extraction of the bias dependent and bias independent components of the MOSFET series resistance is presented, which allows the direct and analytical determination of these components from measurements performed on a single device.
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