On overview on the state of the art and future trends in physics-based electron device modelling for the computer-aided design of monolithic microwave ICs is provided. After a review of the main physics-based approaches to microwave modeling, special emphasis is placed on innovative developments relevant to circuit-oriented device performance assessment, such as efficient physics-based noise and parametric sensitivity analysis. The use of state-of-the-art physics-based analytical or numerical models for circuit analysis is discussed, with particular attention to the role of intermediate behavioral models in linking multidimensional device simulators with circuit analysis tools. Finally, the model requirements for yield-driven MMIC design are discussed, with the aim of pointing out the advantages of physics-based statistical device modeling; the possible use of computationally efficient approaches based on device sensitivity analysis for yield optimization is also considered.

Physics-based electron device modelling and computer-aided MMIC design / F., Filicori; Ghione, Giovanni; Naldi, Carlo. - In: IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES. - ISSN 0018-9480. - 40:7(1992), pp. 1333-1352. [10.1109/22.146317]

Physics-based electron device modelling and computer-aided MMIC design

GHIONE, GIOVANNI;NALDI, Carlo
1992

Abstract

On overview on the state of the art and future trends in physics-based electron device modelling for the computer-aided design of monolithic microwave ICs is provided. After a review of the main physics-based approaches to microwave modeling, special emphasis is placed on innovative developments relevant to circuit-oriented device performance assessment, such as efficient physics-based noise and parametric sensitivity analysis. The use of state-of-the-art physics-based analytical or numerical models for circuit analysis is discussed, with particular attention to the role of intermediate behavioral models in linking multidimensional device simulators with circuit analysis tools. Finally, the model requirements for yield-driven MMIC design are discussed, with the aim of pointing out the advantages of physics-based statistical device modeling; the possible use of computationally efficient approaches based on device sensitivity analysis for yield optimization is also considered.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/1403629
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