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A new digital predistortion technique based on a direct learning architecture is proposed for linearising power amplifiers (PAs) with nonlinear memory effects. It is based on the non‐uniform memory polynomial (MP) model and with a quadratically interpolated LUT. There are mainly two innovations. First, compared with the conventional MP model, the non‐uniform MP model achieves the same modelling accuracy with less coefficients. Secondly, compared with the linearly interpolated LUT, the quadratically interpolated LUT has higher accuracy, which is adopted to realise a part of the mathematical computations in the predistortion. The proposed solution is validated on a real PA ZFL‐2500. It reduces the number of the model's coefficients and achieves a spectrum regrowth suppression of about 15 dB with a table size of only 8. [ABSTRACT FROM AUTHOR]

A new digital predistortion technique based on a direct learning architecture is proposed for linearising power amplifiers (PAs) with nonlinear memory effects. It is based on the non-uniform memory polynomial (MP) model and with a quadratically interpolated LUT. There are mainly two innovations. First, compared with the conventional MP model, the non-uniform MP model achieves the same modelling accuracy with less coefficients. Secondly, compared with the linearly interpolated LUT, the quadratically interpolated LUT has higher accuracy, which is adopted to realise a part of the mathematical computations in the predistortion. The proposed solution is validated on a real PA ZFL-2500. It reduces the number of the model's coefficients and achieves a spectrum regrowth suppression of about 15 dB with a table size of only 8. [ABSTRACT FROM AUTHOR]