Optimized meta-heuristic VCO-based ADC design and analysis

Abstract

The ADC (Analog to Digital Converter) has become essential for interfacing analog signals with the digital domain, particularly in applications requiring high resolution and low voltage operations. Recent advancements in technology have led to reduced signal power and voltage through supply voltage scaling, which has posed significant challenges for ADC performance, including increased area, narrow input range, and process variation. To address these issues, this study has proposed a VCO (Voltage Controlled Oscillator)-based ADC integrated with an ACO-PSO (Ant Colony Optimization– Particle Swarm Optimization) algorithm, thereby enhancing stability, reliability, and effectiveness in chip design. The proposed system has utilized real-time input sources, specifically solar PV (Photo Voltaic) and wind energy, and has incorporated a SEPIC (Single-Ended Primary Inductance Converter) to deliver a controlled output voltage. The ACO-PSO algorithm has optimized the values obtained from the VCO-based ADC and has selected the best solutions to achieve improved performance. The efficiency of the framework has been assessed by measuring gain and delay through Verilog simulations, and the results have been obtained using MATLAB/Simulink. The circuit has occupied an area of 0.012 μm² and has achieved a Mean Square Error (MSE) of 0.2 and a Peak Signal-to-Noise Ratio (PSNR) of 52 dB, thereby demonstrating superior efficiency compared to conventional methods.