The accuracy of high-frequency models of passive RF devices, e.g., inductors or transformers, presents one of the most challenging problems for RF integrated circuits. Accuracy limitations lead RF designers to time-consuming iterations with electromagnetic simulators. This paper will explore and compare two advanced modeling techniques. The first one is based on the segmented model approach, in which each device segment is characterized with a lumped element model. The second technique is based on the generation of surrogate models from the electromagnetic simulation of a set of device samples. Different modeling strategies (frequency separation, filtering according to self-resonance frequency, etc.) will be considered. Efficiency and accuracy of both, physical and surrogate, modeling techniques will be compared using a Si process technology.

This paper discusses the use of symbolic methods applied to the design automation of SI data converters. The proposed approach is an extension of an already proved methodology, for the symbolic synthesis of linear and nonlinear data converters. This is performed by introducing SI characteristics in modified signal flow graph representation of conversion algorithms, including a new set of functional and electrical structures in the system library and, finally, defining an appropriate sizing mechanism for the new structures. The design process is here exemplified for a well known data conversion algorithm.

A knowledge-based approach for the automatic symbolic characterization of SC circuits is presented considering the effect of non-ideal finite gain operational amplifiers. This includes conventional filtering structures above second order as well as generalized multirate structures with switching waveforms performing multiple sampling-discharge operations per clock period.

Signal flow graphs (SFG's) are a powerful technique to analyze switched-capacitor (SC) circuits in a way that provides in-depth information about their operation and direct access to the corresponding symbolic z-transfer functions. Due to lengthy and error-prone symbolic manipulations this is manually manageable for simple first- or second-order circuits, but becomes unpractical for manipulating higher-order circuits which can not be decomposed into first- and second-order ones. Hence, there is an important need to provide designers with a computer-aided tool for the SFG symbolic analysis of a broad class of SC filtering networks, as described in this paper. Rule-based techniques are employed to capture from arbitrary circuit schematic and timing diagrams the corresponding symbolic SFG leading to the automatic generation of the associated z-transfer function. Symbols can then be instantiated to numerical values to obtain measurable data on a variety of performance indicators such as total capacitor area and capacitance spread as well as the resulting nominal frequency response and its variability against component errors. This is illustrated considering a variety of examples of SC filtering networks including, besides the more traditional filters, both finite and infinite impulse response decimators.>