Fábio Passos

An inductor modeling and optimization toolbox for RF circuit design

Abstract This paper describes the SIDe-O toolbox and the support it can provide to the radio-frequency designer. SIDe-O is a computer-aided design toolbox developed for the design of integrated inductors based on surrogate modeling techniques and the usage of evolutionary optimization algorithms. The models used feature less than 1% error when compared to electromagnetic simulations while reducing the simulation time by several orders of magnitude. Furthermore, the tool allows the creation of S-parameter files that accurately describe the behavior of inductors for a given range of frequencies, which can later be used in SPICE-like simulations for circuit design in commercial environments. This toolbox provides a solution to the problem of accurately and efficiently optimizing inductors, which alleviates the bottleneck that these devices represent in the radio-frequency circuit design process.

Lumped element model for arbitrarily shaped integrated inductors — A statistical analysis

In this paper a model based in lumped elements is presented for the characterization of integrated inductors. The model allows the modelling of integrated inductors for a wide range of frequencies and different inductor topologies, thus granting the evaluation of important design parameters such as inductance, quality factor and self-resonance frequency. The model will be explained in detail and compared against electromagnetic simulations for a 0.35-μm and 0.13-μm CMOS technologies. Results for square and octagonal geometries are presented. A statistic analysis is also presented for the octagonal topology in order to validate the model over a wide range of geometric variables in 0.35-μm CMOS technology.

New mapping strategies for pre-optimized inductor sets in bottom-up RF IC sizing optimization

This paper presents new indexing and mutation operators, in the context of bottom-up hierarchical multi-objective optimization of radio frequency integrated circuits, for pre-optimized sets of solutions from the hierarchical sub-levels when moving up in hierarchy. Two ideas, one based on a Voronoi decomposition and another based on the nearest neighborhood, are explored, where, and unlike previous approaches that are based on sorting, the distance between elements determines the probability of decisions taken during optimization. Three implementations of those ideas were tried in AIDAs NSGAII evolutionary kernel, and successfully used in the optimization of a Voltage Controlled Oscillator and a Low Noise Amplifier with pre-optimized inductor sets obtained using the SIDeO toolbox, showing their strengths when compared to previous state-of-the-art mapping strategies.

Systematic design of a voltage controlled oscillator using a layout-aware approach

This paper focuses on the systematic design of voltage controlled oscillators (V CO), a commonly used radiofrequency (RF) electronic circuit. RF circuits are among the most difficult analog circuits to design due to its trade-offs and high operation frequencies. At such operation frequencies, layout parasitics and accurate passive component characterization become of upmost importance, causing re-design iterations if they are not considered by the designer. To avoid this problem, and reduce the design time, this paper presents a systematic design of a VCO, entailing layout parasitics and accurate characterization of passive components from early design stages. Results clearly illustrate the benefit of this strategy.

Radio-frequency inductor synthesis using evolutionary computation and Gaussian-process surrogate modeling

Abstract In recent years, the application of evolutionary computation techniques to electronic circuit design problems, ranging from digital to analog and radiofrequency circuits, has received increasing attention. The level of maturity runs inversely to the complexity of the design task, less complex in digital circuits, higher in analog ones and still higher in radiofrequency circuits. Radiofrequency inductors are key culprits of such complexity. Their key performance parameters are inductance and quality factors, both a function of the frequency. The inductor optimization requires knowledge of such parameters at a few representative frequencies. Most common approaches for optimization-based radiofrequency circuit design use analytical models for the inductors. Although a lot of effort has been devoted to improve the accuracy of such analytical models, errors in inductance and quality factor in the range of 5%–25% are usual and it may go as high as 200% for some device sizes. When the analytical models are used in optimization-based circuit design approaches, these errors lead to suboptimal results, or, worse, to a disastrous non-fulfilment of specifications. Expert inductor designers rely on iterative evaluations with electromagnetic simulators, which, properly configured, are able to yield a highly accurate performance evaluation. Unfortunately, electromagnetic simulations typically take from some tens of seconds to a few hours, hampering their coupling to evolutionary computation algorithms. Therefore, analytical models and electromagnetic simulation represent extreme cases of the accuracy-efficiency trade-off in performance evaluation of radiofrequency inductors. Surrogate modeling strategies arise as promising candidates to improve such trade-off. However, obtaining the necessary accuracy is not that easy as inductance and quality factor at some representative frequencies must be obtained and both performances change abruptly around the self-resonance frequency, which is particular to each device and may be located above or below the frequencies of interest. Both, offline and online training methods will be considered in this work and a new two-step strategy for inductor modeling is proposed that significantly improves the accuracy of offline methods The new strategy is demonstrated and compared for both, single-objective and multi-objective optimization scenarios. Numerous experimental results show that the proposed two-step approach outperforms simpler application strategies of surrogate modelling techniques, getting comparable performances to approaches based on electromagnetic simulation but with orders of magnitude less computational effort.

Frequency-dependent parameterized macromodeling of integrated inductors

Integrated inductors are one of the most important passive elements in radio frequency design, due to their wide usage in wireless communication circuits. Typically, electromagnetic simulators are used in order to estimate the inductors performance with high accuracy as a function of the inductor geometrical and electrical parameters. Such simulations offer high-accuracy, but are computationally expensive and extremely time consuming. In this paper, a frequency-dependent parameterized macromodeling technique is adopted in order to overcome this problem. The proposed approach offers a high degree of automation, since it is based on sequential sampling algorithms, high efficiency and flexibility: a continuous frequency-domain model is given for each value of the chosen inductors parameters in the design space.

Enhanced systematic design of a voltage controlled oscillator using a two-step optimization methodology

Abstract In this paper a design strategy based on bottom-up design methodologies is used in order to systematically design a voltage controlled oscillator. The methodology uses two computer-aided design tools: AIDA, a multi-objective multi-constraint circuit optimization tool, and SIDe-O, a tool that characterizes and optimizes integrated inductors with high accuracy (around 1% when compared to electromagnetic simulations). By using such tools, the difficult trade-offs inherent to radio-frequency circuits can be explored efficiently and accurately. Furthermore, with the capability that AIDA has at considering process parameter variations during the optimization, the resulting methodology is able to obtain truly robust circuit designs.

Layout-aware challenges and a solution for the automatic synthesis of radio-frequency IC blocks

In this paper, the major methodologies proposed in the last years to speed-up the synthesis of radio-frequency integrated circuits blocks are overviewed. The challenges to automate this task are discussed, and, to avoid non-systematic iterations between circuit and layout design steps, the architecture of an innovative solution is proposed. The proposed tool exploits the full capabilities of most established computer-aided design tools available nowadays, i.e., off-the-shelf circuit simulator, electromagnetic simulator and layout extractor. The approach intends to bypass the two major bottlenecks of RF-design: the design of reliable integrated inductors and accurate layout parasitic estimates since the early stages of design process.

A strategy to efficiently include electromagnetic simulations in optimization-based RF circuit design methodologies

The use of electromagnetic simulations is crucial in radiofrequency and microwave circuits since accurate estimations of parasitics and performances are essential. In addition, design methodologies based on optimization algorithms have been used in order to design such circuits, while efficiently exploring its design trade-offs. However, due to the high computational cost, optimization-based methodologies seldom use electromagnetic simulation. In order to overcome this issue, this paper demonstrates an optimization-based design methodology for radiofrequency circuits which can incorporate electromagnetic simulations without efficiency loss.

An algorithm for a class of real-life multi-objective optimization problems with a sweeping objective

This paper describes a class of real-life optimization problems that has not been addressed before: a multi-objective optimization in which one objective is neither minimized nor maximized but uniformly swept over a wide range. The limitations of conventional multi-objective optimization algorithms to deal with this kind of problems are illustrated via the optimization of radiofrequency inductors. For the first time, an algorithm is proposed that provides sets of solutions for this kind of problems.