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Pereira, P., M. H. Fino, and F. V. Coito, "Using discrete-variable optimization for CMOS spiral inductor design", Proc. Int Microelectronics (ICM) Conf, pp. 324–327, 2009. Abstract

In this paper a discrete-variable optimization methodology for the automatic design of CMOS integrated spiral inductors is introduced. The use of discrete variable optimization procedure offers the designer the possibility for exploring the design space exclusively in those points available for the technology under use. Further user-defined constraints between layout parameters may also be incorporated as a way of taking into account design heuristics. A comparison between using discrete-variable optimization and a continuous optimization procedure followed by a discretization of the results is presented, where the benefits of the proposed methodology are presented. An application using the proposed methodology was developed in Matlab and the optimization toolbox is used. For the sake of simplicity the pi-model has been used for characterizing the inductor. The validity of the design results is checked against circuit simulation with ASITIC.

Almeida, P., P. Pereira, and H. Fino, "Using Variable Width RF Integrated Inductors for Quality Factor Optimization", Technological Innovation for the Internet of Things, vol. 394: Springer Berlin Heidelberg, pp. 619-627, 2013. Abstract

The advancement of CMOS technology led to the integration of more complex functions. In the particular of wireless transceivers, integrated LC tanks are becoming popular both for VCOs and integrated filters [1]. For RF applications the main challenge is still the design of integrated inductors with the maximum quality factor. For that purpose, tapered, i.e., variable width inductors have been proposed in the literature. In this paper, analytical expressions for the determination the pi-model parameters, for the characterization of variable width integrated inductors are proposed. The expressions rely exclusively on geometrical and technological parameters, thus granting the rapid adaptation of the model to different technologies. The results obtained with the model are compared against simulation with ASITIC, showing errors below 10%. The model is then integrated into an optimization procedure where inductors with a quality factor improvement in the order of 20-30% are obtained, when compared with fixed width inductors.