DOI: 10.3390/jlpea16040053 ISSN: 2079-9268

MATLAB-Assisted EKV-gm/ID Design Procedure for Two-Stage Miller-Compensated CMOS OTAs Starting from Closed-Loop Specifications

Marcello De Matteis

This paper presents a MATLAB-assisted EKV–gm/ID methodology for the systematic synthesis of fully differential two-stage Miller-compensated CMOS OTAs. A sensitivity-based analysis maps the required closed-loop gain, bandwidth, and noise into OTA-level targets. An EKV-inspired analytical model, independently calibrated for nMOS and pMOS devices, provides continuous ID/W, gm/W and gm/ID characteristics with errors below 5% in the design region. Noise-driven sizing explicitly accounts for the different carrier mobilities of the pMOS differential pair and nMOS active load. Transistor parasitic capacitances are estimated from bias-dependent Cgg–VGS characteristics, thereby capturing the reduced gate capacitance of devices operating in moderate or weak inversion. The framework automatically generates transistor dimensions, bias conditions, and Miller-compensation components. These parameters are transferred directly from MATLAB to CADENCE without simulator-assisted resizing or optimization, except for width quantization into 5 μm/300 nm fingers. In 0.18 μm CMOS implementation, MATLAB and nominal CADENCE simulations predict, respectively, 61.80 and 59.27 dB DC gain, 430.78 and 431.52 MHz unity-gain bandwidth, 69.24° and 68.81° phase margin, 5.0 and 5.3 nV/√Hz input-referred noise at 100 MHz, and 1.426 and 1.314 mW core power. Robustness is assessed over 45 process-voltage-temperature corners, where the nominal solution remains close to the center of the evaluated performance distributions. The results confirm accurate nominal prediction and stable transistor-level behavior across PVT conditions and demonstrate that the proposed methodology accurately designs the OTA operating point, small-signal dynamics, and noise behavior, enabling transistor-level sizing directly from system-level specifications without iterative simulator-assisted optimization.

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