A Particle Swarm Optimization Technique used for the Improvement of Analogue Circuit Performances

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A Multi-objective Simulation Based Tool: Application to the Design of High Performance LC-VCOs

Part 16: Optimization Techniques in EnergyInternational audienceThe continuing size reduction of electronic devices imposes design challenges to optimize the performances of modern electronic systems, such as: wireless services, telecom and mobile computing. Fortunately, those design challenges can be overcome thanks to the development of Electronic Design Automation (EDA) tools. In the analog, mixed signal and radio-frequency (AMS/RF) domains, circuit optimization tools have demonstrated their usefulness in addressing design problems taking into account downscaling technological aspects. Recent advances in EDA have shown that the simulation-based sizing technique is a very interesting solution to the ‘complex’ modelling task in the circuit design optimization problem. In this paper we propose a multi-objective simulation-based optimization tool. A CMOS LC-VCO circuit is presented to show the viability of this tool. The tool is used to generate the Pareto front linking two conflicting objectives, namely the VCO Phase Noise and Power Consumption. The accuracy of the results is checked against HSPICE/RF simulations

Behavioral Modeling of Mixed-Mode Integrated Circuits

Open Access.-- et al.This work is partially supported by CONACyT through the grant for the sabbatical stay of the first author at University of California at Riverside, during 2009-2010. The authors acknowledge the support from UC-MEXUS-CONACYT collaboration grant CN-09-310; by Promep México under the project UATLX-PTC-088, and by Consejeria de Innovacion Ciencia y Empresa, Junta de Andalucia, Spain, under the project number TIC-2532. The third author thanks the support of the JAE-Doc program of CSIC, co-funded by FSE.Peer Reviewe

Design of second-generation current conveyors employing bacterial foraging optimization

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Multiobjective Differential Evolution Algorithm using Crowding Distance for the Optimal Design of Analog Circuits

This paper details the Multiobjective Differential Evolution algorithm (MODE) using crowding distance for the sizing of analog circuits. MODE is used to compute the Pareto front of a biobjective optimization problem, namely maximizing the high current cut-off frequency and minimizing the parasitic input resistance of a second generation current conveyor. To highlight performances of MODE, comparisons with the non-sorting genetic algorithm (NSGA-II) were performed. These comparisons show that MODE outperforms NSGA-II in terms of quality of the optimal solutions, diversity of those solutions along the Pareto front, and computing time

Metamodelling Techniques for the Optimal Design of Low-Noise Amplifiers

In this article we deal with the optimal sizing of low-noise amplifiers (LNAs) using newly proposed metamodeling techniques. The main objective is to construct metamodels of main performances of the LNAs (namely, the third intercept point (IIP3), the scattering parameters (Sij), and the noise figure (NF)) and use them inside an optimization kernel for maximizing the circuits’ performances. The kriging surrogate modelling technique is used for constructing these models. The particle swarm optimization (PSO) technique is considered as the optimization metaheuristic. Two CMOS amplifiers are considered: a UMTS LNA and a multistandard LNA. Obtained results show that, at the considered working frequencies, the first LNA exhibits at 2.14 GHz a noise figure of 1.30 dB, an S21 of 16.01 dB, an S11 of −12.60 dB, and an IIP3 of 8.30 dBm. At 2 GHz, the second LNA has a noise figure of 1.24 dB, an S21 of 17.16 dB, an S11 of −13.74 dB, and an IIP3 of 4.30 dBm. Comparisons between results obtained using the constructed models and those of the simulation are presented to show the perfect agreement between them