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This paper presents a black-box model that can be applied to characterize the nonlinear dynamic behavior of power amplifiers (PAs), including strong nonlinearities and memory effects. Feedforward time-delay Neural Networks (TDNN) are used to extract the model from a large-signal input-output time-domain characterization in a given bandwidth; furthermore, explicit formulas to derive Volterra kernels from the TDNN parameters are also presented. The TDNN and related Volterra models can predict the amplifier response to different frequency excitations in the same bandwidth and power sweep. As a case study, a PA, characterized with a two-tone power swept excitation, is modeled and simulations are found in good agreement with training measurements; moreover, a model validation with two tones of different frequencies and spacing is also performed. © 2007 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2007. [ABSTRACT FROM AUTHOR]

A new method for characterization of HEMT distortion parameters, which extracts the coefficents of a Taylor series expansion of Ids(Vgs, Vds), including all cross-terms, is developed from low-frequency harmonic measurements. The extracted parameters will be used either in a Volterra series model around a fixed bias point for 3rd-order characterization of small-signal Ids nonlinearity, or in a large-signal model of Ids characteristic, where its partial derivatives are locally characterized up to the 3rd order in the whole bias region, using a novel neural-network representation. The two models are verified by one-tone and two-tone intermodulation distortion (IMD) tests on a PHEMT device. © 2006 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2006. [ABSTRACT FROM AUTHOR]

In this work, we revisit a tunable optical-receiver configuration based on nontunable wavelength demultiplexing and electronic channel selection. Compared to previous designs, our novel electronic selector circuit provides a significant reduction in the average noise current, while simultaneously achieving the high tuning speed required at the optical network unit (ONU) of packet-switched WDM-PON networks. Also, for the first time (to our knowledge), this kind of circuit is demonstrated to operate well above one GB/s. © 2004 Wiley Periodicals, Inc. Microwave Opt Technol Lett 42: 373–377, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.20308 [ABSTRACT FROM AUTHOR]

This paper reports circuit design improvements with respect to classical distributed transimpedance amplifiers for optical receiver front ends to obtain the highest gain and bandwidth performances using a low-cost MMIC technology. The design issues have been applied to the design of a front-end amplifier for optical links up to 10 Gb/s, and an effective transimpedance gain of 48 dBΩ and a bandwidth from dc to 9 GHz are achieved. © 2003 Wiley Periodicals, Inc. Microwave Opt Technol Lett 39: 190–193, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.11165 [ABSTRACT FROM AUTHOR]

This article presents a detailed procedure to learn a nonlinear model and its derivatives to as many orders as desired with multilayer perceptron (MLP) neural networks. A modular neural network modeling a nonlinear function and its derivatives is introduced. The method has been used for the extraction of the large-signal model of a power MESFET device, modeling the nonlinear relationship of drain-source current Ids as well as gate and drain charge Qg and Qd with respect to intrinsic voltages Vgs and Vds over the whole operational bias region. The neural models have been implemented into a user-defined nonlinear model of a commercial microwave simulator to predict output power performance as well as intermodulation distortion. The accuracy of the device model is verified by harmonic load-pull measurements. This neural network approach has demonstrated to predict nonlinear behavior with enough accuracy even if based only on first-order derivative information. © 2003 Wiley Periodicals, Inc. Int J RF and Microwave CAE 13: 276–284, 2003. [ABSTRACT FROM AUTHOR]

Artificial neural networks (ANNs) are presented for the technology-independent modeling of active devices in MMICs. ANNs trained with S-parameter and DC measurements over the entire bias and frequency operational band are used for the small-signal bias-dependent modeling of a low-noise GaAs HEMT device, without the need of the equivalent circuit parameter extraction. ANNs are also used within the large-signal model of a power MESFET device, modeling the drain-source current Ids and charges Qg and Qd obtained from integration of their partial derivatives. After training and testing, the ANN models have been implemented as two-port networks into a microwave circuit simulator. This enabled the ANN models to be used in the design, analysis, and optimization of microwave/mm-wave circuits. Improved techniques in network building to provide not only accurate but also fast simulation models have been applied. © 2002 John Wiley & Sons, Inc. Int J RF and Microwave CAE 12: 71–78, 2002. [ABSTRACT FROM AUTHOR]

An advanced design procedure for MMIC GaAs direct-coupled transimpedance amplifier for gigabit/second-rate optical communication systems is presented. A transimpedance gain of 67 dBΩ up to 2.5 GHz has been demonstrated. A complete set of simulated and measured results are presented to confirm the effectiveness of the design approach. The design and the realization have been performed within the framework of ESPRIT Project No. 5018 COSMIC. [ABSTRACT FROM AUTHOR]