AI-Driven Co-Optimization of ONOFIC-Enhanced FinFET/CNTFET Nano Domino Circuits and Multiband Antenna Design for Subthreshold Leakage Minimization and PVT-Robust Low-Power VLSI Systems
Year: 2025
Type: preprint
Abstract: The scaling of semiconductor devices and the integration of RF functionalities in VLSI systems have intensified challenges related to subthreshold leakage, energy efficiency, and process-voltage-temperature (PVT) variability in nanoelectronic circuits. ONOFIC (On-Off Current Feedback Controlled) methodology has proven effective in mitigating leakage in FinFET- and CNTFET-based nano domino circuits, but its performance is sensitive to transistor sizing, biasing, dynamic voltage scaling, and interactions with embedded multiband antennas. This paper presents a novel AI-driven co-optimization framework that jointly optimizes ONOFIC-enhanced FinFET/CNTFET circuits and multiband antenna design for low-power, PVT-robust VLSI systems. The framework employs artificial neural networks (ANNs) trained on HSPICE simulations as surrogate models and integrates evolutionary algorithms (GA, PSO, NSGA-II) to efficiently explore the design space. Key parameters—including feedback transistor bias, device sizing, nanotube count, voltage scaling, and antenna geometrical and electrical characteristics—are tuned to minimize leakage while maintaining optimal delay, power-delay product (PDP), energy-delay product (EDP), and robustness under PVT and aging variations. Simulation results show leakage reductions of 38–52%, PDP/EDP improvements of 30%, and stable operation under thermal, process, and RF-induced variations. The proposed approach establishes a scalable, AI-assisted methodology for designing integrated low-power VLSI systems with multiband antennas, paving the way for next-generation IoT, 5G, and 6G applications.
Authors: R. Ramesh Naik, D. Ramakrishna Reddy, Krishnanaik Vankdoth
Institution: Chaitanya
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4415020140
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