U. Erdogan

Bio: U. Erdogan is an academic researcher from Texas Instruments. The author has contributed to research in topics: Scalability. The author has an hindex of 1, co-authored 1 publications receiving 119 citations.

RF MOSFET modeling accounting for distributed substrate and channel resistances with emphasis on the BSIM3v3 SPICE model

Abstract: A r.f. MOSFET model generated for use in LIBRA simulation typically applies to only one bias point. The model and its parameters can be unphysical. It is desirable to establish a physical, scalable model capable of simulating both d.c. and r.f. characteristics and applicable to all the bias ranges. BSIM3 is a potential candidate, having demonstrated accuracy and scalability in the devices' d.c. characteristics. When it is applied to simulate the s-parameters at r.f., we find BSIM3 to be somewhat problematic and two modifications are necessary to obtain a good fit. The first modification involves the addition of a bulk resistive network, achievable with a simple circuit extension to the existing BSIM3 model. The second improvement accounts for the finite channel resistance, whose origin lies in a nonquasi-static analysis. Since BSIM3 employs a quasi-static assumption, this improvement, while important, involves some changes in the BSIM3 source code.

Charge-Based MOS Transistor Modeling - The EKV Model for Low-Power and RF IC Design

Abstract: Foreword. Preface. List of Symbols. 1. Introduction. 1.1 The Importance of Device Modeling for IC Design. 1.2 A Short History of the EKV MOST Model. 1.3 The Book Structure. PART I: THE BASIC LONG-CHANNELINTRINSIC CHARGE-BASED MODEL. 2. Introduction. 2.1 The N-channel Transistor Structure. 2.2 Definition of charges, current, potential and electric fields. 2.3 Transistor symbol and P-channel transistor. 3. The Basic Charge Model. 3.1 Poisson's Equation and Gradual Channel Approximation. 3.2 Surface potential as a Function of Gate Voltage. 3.3 Gate Capacitance. 3.4 Charge Sheet Approximation. 3.5 Density of Mobile Inverted Charge. 3.6 Charge-Potential Linearization. 4. Static Drain Current. 4.1 Drain Current Expression. 4.2 Forward and Reverse Current Components. 4.3 Modes of Operation. 4.4 Model of Drain Current Based on Charge Linearization. 4.5 Fundamental Property: Validity and Application. 4.6 Channel Length Modulation. 5. The Small-Signal Model. 5.1 The Static Small-Signal Model. 5.2 A General Non-Quasi-Static Small-Signal Model. 5.3 The Quasi-Static Dynamic Small-Signal Model. 6. The Noise Model. 6.1 Noise Calculation Methods. 6.2 Low-Frequency Channel Thermal Noise. 6.3 Flicker Noise. 6.4 Appendices. Appendix : The Nyquist and Bode Theorems. Appendix : General Noise Expression. 7. Temperature Effects and Matching. 7.1 Introduction. 7.2 Temperature Effects. PART II: THE EXTENDED CHARGE-BASED MODEL. 8. Non-Ideal Effects Related to the Vertical Dimension. 8.1 Introduction. 8.2 Mobility Reduction Due to the Vertical Field. 8.3 Non-Uniform Vertical Doping. 8.4 Polysilicon Depletion. 8.4.1 Definition of the Effect. 8.5 Band Gap Widening. 8.6 Gate Leakage Current. 9. Short-Channel Effects. 9.1 Velocity Saturation. 9.2 Channel Length Modulation. 9.3 Drain Induced Barrier Lowering. 9.4 Short-Channel Thermal Noise Model. 10. The Extrinsic Model. 10.1 Extrinsic Part of the Device. 10.2 Access Resistances. 10.3 Overlap Regions. 10.4 Source and Drain Junctions. 10.5 Extrinsic Noise Sources. PART III: THE HIGH-FREQUENCY MODEL. 11. Equivalent Circuit at RF. 11.1 RF MOS Transistor Structure and Layout. 11.2 What Changes at RF?. 11.3 Transistor Figures of Merit. 11.4 Equivalent Circuit at RF. 12. The Small-Signal Model at RF. 12.1 The Equivalent Small-Signal Circuit at RF. 12.2 Y-Parameters Analysis. 12.3 The Large-Signal Model at RF. 13. The Noise Model at RF. 13.1 The HF Noise Parameters. 13.2 The High-Frequency Thermal Noise Model. 13.3 HF Noise Parameters of a Common-Source Amplifier. References. Index.

MOS transistor modeling for RF IC design

Abstract: This paper presents the basis of the modeling of the MOS transistor for circuit simulation at RF. A physical equivalent circuit that can easily be implemented as a Spice subcircuit is first derived. The subcircuit includes a substrate network that accounts for the signal coupling occurring at HF from the drain to the source and the bulk. It is shown that the latter mainly affects the output admittance Y22. The bias and geometry dependence of the subcircuit components, leading to a scalable model, are then discussed with emphasis on the substrate resistances. Analytical expressions of the Y parameters are established and compared to measurements made on a 0.25-/spl mu/m CMOS process. The Y parameters and transit frequency simulated with this scalable model versus frequency, geometry, and bias are in good agreement with measured data. The nonquasi-static effects and their practical implementation in the Spice subcircuit are then briefly discussed. Finally, a new thermal noise model is introduced. The parameters used to characterize the noise at HF are then presented and the scalable model is favorably compared to measurements made on the same devices used for the S-parameter measurement.

Improved three-step de-embedding method to accurately account for the influence of pad parasitics in silicon on-wafer RF test-structures

Abstract: In order to model the RF behavior of a device-under-test (DUT), e.g., active and passive devices, dedicated on-wafer test-structures are required. However, parasitic components in the test-structure stemming from the contact pads, the metal interconnections and the silicon substrate, largely influence the RF behavior of the actual DUT. They need to be subtracted from the measurement results if one wants to model the RF behavior of the actual DUT accurately. This subtraction procedure is referred to as de-embedding. In this paper, we propose an improved three-step de-embedding method to subtract the influence of parasitics. The de-embedding method has been applied not only to S-parameter measurement results on MOSFETs but also, for the first time, to large-signal vectorial RF measurements.

An MOS transistor model for RF IC design valid in all regions of operation

Abstract: This paper presents an overview of MOS transistor modeling for RF integrated circuit design. It starts with the description of a physical equivalent circuit that can easily be implemented as a SPICE subcircuit. The MOS transistor is divided into an intrinsic part, representing mainly the active part of the device, and an extrinsic part responsible for most of the parasitic elements. A complete charge-based model of the intrinsic part is presented. The main advantage of this new charge-based model is to provide a simple and coherent description of the DC, AC, nonquasi-static (NQS), and noise behavior of the intrinsic MOS that is valid in all regions of operation. It is based on the forward and reverse charges q/sub f/ and q/sub r/ defined as the mobile charge densities, evaluated at the source and at the drain. This intrinsic model also includes a new simplified NQS model that uses a bias and frequency normalization allowing one to describe the high-order frequency behavior with only two simple functions. The extrinsic model includes all the terminal access series resistances, and particularly the gate resistance, the overlap, and junction capacitances as well as a substrate network. The latter is required to account for the signal coupling occurring at RF from the drain to the source and the bulk, through the junction capacitances. The noise model is then presented, including the effect of the substrate resistances on the RF noise parameters. All the aspects of the model are validated for a 0.25-/spl mu/m CMOS process.

An effective gate resistance model for CMOS RF and noise modeling

Abstract: A physics-based effective gate resistance model representing the non-quasi-static (NQS) effect and the distributed gate electrode resistance is proposed for accurately predicting the RF performance of CMOS devices. The accuracy of the model is validated with 2D simulations and experimental data. In addition, the effect of the gate resistance on the device noise behavior has been studied with measured data. The result shows that an accurate gate resistance model is essential for the noise modeling.