G. Ma

Stanford University, Stanford, CA, United States

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Publications (6)2.24 Total impact

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    ABSTRACT: LDMOS technologies based in G. Ma et al. (1996) and H. Brech et al. (2003) have been in dominate position in wireless base station applications for frequencies ranging from 450MHz to 2.7GHz for the last 10 years due to performance, cost, reliability, and power capability advantages. This paper reviews the leading edge LDMOS development at Infineon and discusses future potential and limitation for LDMOS technologies in general; benchmarking with alternative technologies is also presented
    Full-text · Conference Paper · Jan 2006
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    ABSTRACT: Linearity is one of the most important characteristics for current and next-generation RF power devices for wireless communication. In this work, linearity of power LDMOS devices is analysed by using a unique harmonic balance device simulator. Sweet-spots in the third order intermodulation distortion product (IM3) are explained and found to be in agreement with measurements and compact modeling. For demonstration of the simulation methodology, a change in the lightly doped drain (LDD) region doping concentration was performed and the effect on linearity was analysed.
    No preview · Conference Paper · Oct 2005
  • F.M. Rotella · G. Ma · Z. Yu · R.W. Dutton
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    ABSTRACT: This paper describes how device simulation may be used for the modeling, analysis, and design of radio-frequency (RF) laterally diffused metal-oxide-semiconductor (LDMOS) transistors. Improvements to device analysis needed to meet the requirements of RF devices are discussed. Key modeling regions of the LDMOS device are explored and important physical effects are characterized. The LDMOS model is compared to dc and small-signal ac measurements for calibration purposes. Using the calibrated model, large-signal accuracy is verified using harmonic distortion simulation, and intermodulation analysis. Predictive analysis and a study of the structure's parasitic components are also presented. Load-pull simulation is used to analyze matching network effects to determine the best choices for device impedance matching
    No preview · Article · Jul 2000 · IEEE Transactions on Microwave Theory and Techniques
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    ABSTRACT: The rapid growth of wireless systems at radio frequencies (RF) is driving the need for improved analog circuit and device analysis at gigaHertz frequencies. This includes: low noise front ends, linear amplifiers, mixers, and power amplifiers. Moreover, the parasitic effects of capacitance and inductance, both on- and off-chip, require careful extraction and characterization in support of predictive modeling. While time-domain techniques work well for digital systems, often the spectral and dynamic range requirements for communications systems necessitate accurate analysis of harmonic content with frequency differences of a thousandfold or more. This paper demonstrates the applicability and unique strengths of device-level harmonic balance (HB) in the simulation and physical modeling of RF circuits
    Preview · Conference Paper · Jan 1998
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    ABSTRACT: This paper discusses a harmonic balance simulation involving a high power LDMOS device, bias circuitry and matching network. The paper begins with a discussion of the device and circuit configuration as well as the requirements for simulation. Next the paper describes the simulation algorithms and simulator structure in order to meet the requirements. PISCES is used as the basis and around it are added libraries for harmonic balance simulation and circuit boundary conditions. Finally, simulation results are presented. The experimental and simulated response of the power gain and power added efficiency of an RF power amplifier are shown
    Preview · Conference Paper · Oct 1997
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    ABSTRACT: This paper discusses the modeling and simulation of power MOSFET's using large signal device simulation. In order lo provide an accurate representation of an LDMOS MOSFET, a model for the intrinsic device and the cxtrinsie parasitic components is developed. The RF performance of the model is then verified with experimental data. With the proven model, the effect of parasitic components is analyzed and the matching networks arc optimized for the desired response.
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