Expedite EM-driven generation of Pareto-optimal trade-off curves for variable-turn on-chip inductors
Abstract
This work presents a novel approach to computationally efficient Pareto front identification for variable-turn on-chip inductors. The final outcome is a set of solutions that correspond to the best trade-offs between conflicting design objectives. Here, we consider minimising inductor area and, simultaneously, maximising its quality factor, while maintaining a specified inductance value at a given operating frequency. As opposed to the typically used population-based metaheuristics requiring massive computational resources to generate the entire Pareto front in a single algorithm run, the proposed method reduces the number of necessary structure evaluations by exploiting a point-by-point strategy for determining the consecutive trade-off designs. The original design problem is a mixed-integer task involving integer and non-integer variables (here, the number of inductor windings and its geometry parameters). For the sake of computational efficiency, we develop a separate kriging interpolation model for each considered case of winding turns, and use it, instead of expensive electromagnetic simulations, to obtain the initial Pareto fronts. The non-dominated part of the concatenated initial Pareto sets is subsequently elevated (accuracy-wise) to the level of an electromagnetic analysis by means of a response correction technique. Our considerations are illustrated using a 3.5-nH variable-turn on-chip inductor realised in 65-nm CMOS technology.
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- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
-
IET Microwaves Antennas & Propagation
no. 12,
edition 7,
pages 1205 - 1210,
ISSN: 1751-8725 - Language:
- English
- Publication year:
- 2018
- Bibliographic description:
- Kozieł S., Kurgan P.: Expedite EM-driven generation of Pareto-optimal trade-off curves for variable-turn on-chip inductors// IET Microwaves Antennas & Propagation. -Vol. 12, iss. 7 (2018), s.1205-1210
- DOI:
- Digital Object Identifier (open in new tab) 10.1049/iet-map.2017.0298
- Verified by:
- Gdańsk University of Technology
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