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All Journal International Journal of Reconfigurable and Embedded Systems (IJRES)
Ramavathu Ramesh Naik
Chaitanya Deemed to be University
Economics, Econometrics & Finance

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AI-driven co-optimization of ONOFIC circuits and multiband antennas for low-power VLSI Ramavathu Ramesh Naik; Donapati Ramakrishna Reddy; Krishnanaik Vankdoth
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 15, No 2: July 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v15.i2.pp306-319

Abstract

This paper presents an artificial intelligence (AI)-assisted optimization framework for on-off current feedback controlled (ONOFIC)-enhanced domino circuits implemented in advanced fin field-effect transistor (FinFET) and carbon nanotube field-effect transistor (CNTFET) technologies. The framework integrates artificial neural network (ANN) surrogate modeling with evolutionary optimization (genetic algorithm (GA), particle swarm optimization (PSO), and NSGA-II) to reduce leakage, improve energy efficiency, and enhance robustness under process voltage temperature (PVT) variations, aging effects (bias temperature instability (BTI)/hot carrier injection (HCI)), and antenna-induced parasitic coupling. By replacing repeated HSPICE simulations with fast ANN predictions, the proposed methodology reduces computational cost by more than 90% while achieving up to 30–35% gains in leakage and power-delay product (PDP)/energy-delay product (EDP) performance. The results demonstrate that ANN-assisted evolutionary optimization provides a scalable and technology-agnostic workflow suitable for next-generation internet of thing (IoT), radio frequency (RF)-integrated, and low-power very large scale integration (VLSI) platforms.
Co-Authors Donapati Ramakrishna Reddy Krishnanaik Vankdoth