Abstract
This paper presents an innovative yield-aware synthesis strategy based on a hierarchical bottom-up methodology that uses a multiobjective evolutionary optimization algorithm to design a complete radiofrequency integrated circuit from the passive component level up to the system level. Within it, performances’ calculation aims for the highest possible accuracy. A surrogate model calculates the performances for the inductive devices, with accuracy comparable to full electromagnetic simulation; and, an electrical simulator calculates circuit- and system-level performances. Yield is calculated using Monte-Carlo (MC) analysis with the foundry-provided models without any model approximation. The computation of the circuit yield throughout the hierarchy is estimated employing parallelism and reducing the number of simulations by performing MC analysis only to a reduced number of candidate solutions, alleviating the computational requirements during the optimization. The yield of the elements not accurately evaluated is assigned using their degree of similitude to the simulated solutions. The result is a novel synthesis methodology that reduces the total optimization time compared to a complete MC yield-aware optimization. Ultimately, the methodology proposed in this work is compared against other methodologies that do not consider yield throughout the system’s complete hierarchy, demonstrating that it is necessary to consider it over the entire hierarchy to achieve robust optimal designs.
Highlights
The design of radiofrequency (RF) integrated circuits (ICs) and systems in nanometer-scale technologies is challenging due to their high operating frequencies, passive component design, and degrading effects of parasitics and variability
The low-noise amplifier (LNA) was implemented with asymmetrical inductors, whereas symmetrical inductors are used for the voltage-controlled oscillator (VCO)
The LNA and VCO are considered for optimization in the second level, whereas the Gilbert cell MIX is considered at the system level for impedance matching purposes
Summary
The design of radiofrequency (RF) integrated circuits (ICs) and systems in nanometer-scale technologies is challenging due to their high operating frequencies, passive component design, and degrading effects of parasitics and variability. Automatic design methodologies that promote the optimal design of RF ICs support circuit designers, with several optimization-based methodologies for simple circuits reported in the literature. Scaling these approaches to more complex circuits or systems is not trivial as the optimization time does not scale well with the circuit size/complexity. Most proposed optimizationbased approaches are only adequate for tackling simple blocks, and hierarchical automation tools still show severe limitations, when considering variability effects. Many reported approaches had used first-order equations for circuit/system performances and analytical models for passives to speed up the VOLUME XX, 2017
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