Quantized CMA equalization for shaped signal constellations

Constellation shaping introduced to maximize channel capacity is detrimental to the performance of many cost function-based blind equalization algorithms including the constant modulus algorithm (CMA). We propose a new multimodulus algorithm closely related to CMA, but robust against changes in the statistical nature of the signal due to constellation shaping. While CMA behaves properly only for sub-Gaussian distributions, the algorithm we develop is applicable to a broad class of distributions including Gaussian and super-Gaussian.