Abstract
This letter presents an improved digital predistortion (DPD) method to optimize the linearization of power amplifiers (PAs) when an under-sampled feedback loop is used in the transmitter. The proposed approach is based on an adaptive piecewise Lagrange (APL) basis digital predistorter and a variable fractional-delay (VFD) finite-length impulse response (FIR) filter. A normalized least mean square (NLMS) algorithm with a direct learning structure is used to update the DPD parameters, and the VFD FIR filter is used to periodically vary the fractional-delay of the transmitted signal. This changes the initial phase of the under-sampled feedback signal to preserve the peak power information from the full sampling rate signal. Experiment results show that there is 10 dB improvement in the normalized mean square error (NMSE) for a 70 MHz Long Term Evolution-advanced signal, even when the sampling rate of feedback is reduced from 491.52 Msps to 122.88 Msps.
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