To address limitations in the modulation-quality analysis of high-order Quadrature Amplitude Modulation (QAM) signals, including insufficient timing synchronization accuracy, challenges in carrier recovery, and coupling between synchronization errors and parameter estimation, a cascaded digital baseband processing framework tailored for measurement scenarios is proposed. The proposed framework is designed to integrate synchronization recovery and parameter measurement. In the timing synchronization stage, a feedforward open-loop structure based on the Oerder–Meyr (OM) algorithm is employed to estimate the optimal sampling instants rapidly. In the carrier synchronization stage, a two-stage recovery structure is constructed, comprising coarse frequency offset estimation based on polarity decision and fine synchronization using an improved frequency–phase detector (FPD), thereby achieving both robust acquisition of large frequency offsets and high-precision compensation of residual errors. On this basis, a unified modulation quality evaluation model is established, enabling the joint estimation of the Error Vector Magnitude (EVM) and the Modulation Error Ratio (MER), as well as amplitude, phase, and frequency errors, within a consistent analytical framework. System-level validation of 256QAM and 1024QAM signals is conducted using a MATLAB R2021b -based simulation platform. The results demonstrate that stable synchronization recovery can be achieved under timing, frequency, and phase perturbations, yielding well-defined constellation diagrams. In terms of parameter estimation, the relative errors of all evaluated metrics are maintained within 2%, which is significantly below the conventional 5% measurement criterion. Further analysis indicates that the proposed method maintains strong robustness across varying signal-to-noise ratios (SNRs) and sampling rates. The results confirm that the proposed cascaded processing framework effectively unifies synchronization recovery and modulation quality analysis, significantly improving parameter estimation accuracy while maintaining high synchronization precision. This approach provides a practical and efficient solution for high-order QAM signal testing and measurement systems.
Sun et al. (Mon,) studied this question.