Multiport Analytical Pixel Electromagnetic Simulator (MAPES) for AI-assisted RFIC and Microwave Circuit Design

TL;DR

MAPES is a new analytical EM simulator that efficiently predicts microwave and RFIC performance for arbitrary pixel configurations, significantly reducing simulation time while maintaining high accuracy, thus aiding AI-assisted circuit design.

Contribution

The paper introduces MAPES, an innovative multiport analytical framework extending IMPM for pixel-based EM simulation, requiring minimal full-wave simulations for accurate predictions.

Findings

Achieves 600-2000x speedup over CST simulations

Requires only about 1% of full-wave simulations for dataset construction

Provides accurate EM predictions across various fabrication technologies

Abstract

This paper proposes a novel analytical framework, termed the Multiport Analytical Pixel Electromagnetic Simulator (MAPES). MAPES enables efficient and accurate prediction of the electromagnetic (EM) performance of arbitrary pixel-based microwave (MW) and RFIC structures. Inspired by the Integrated Internal Multiport Method (IMPM), MAPES extends the concept to the pixel presence/absence domain used in AI-assisted EM design. By introducing virtual pixels and diagonal virtual pixels and inserting virtual ports at critical positions, MAPES captures all horizontal, vertical, and diagonal electromagnetic couplings within a single multiport impedance matrix. Only a small set of full-wave simulations (typically about 1% of the datasets required by AI-assisted EM simulators) is needed to construct this matrix. Subsequently, any arbitrary pixel configuration can be evaluated analytically using a closed-form multiport relation without additional full-wave calculations. The proposed approach eliminates data-driven overfitting and ensures accurate results across all design variations. Comprehensive examples for single- and double-layer CMOS processes (180 nm and 65 nm) and PCBs confirm that MAPES achieves high prediction accuracy with 600- 2000x speed improvement compared to CST simulations. Owing to its efficiency, scalability and reliability, MAPES provides a practical and versatile tool for AI-assisted MW circuit and RFIC design across diverse fabrication technologies.