SCALABLE DIGITAL PREDISTORTION SYSTEM

摘要

The scalable digital predistortion system provides a behavioral model that can be used to model and compensate for the nonlinear distortions of power amplifiers and transmitters. The predistorter and update algorithms make the model/DPD scalable in terms of signal bandwidth and average power, allowing for low complexity update following changes in the signal's bandwidth and/or power level. Experimental validation carried on a 300 Watt Doherty power amplifier shows that the scalable model and the predistorter architecture achieve performance similar to their conventional counterpart. However, the present model/predistorter requires the update of up to 50% fewer coefficients than the conventional model/predistorter.

主权项

1. A scalable digital predistortion method for linearizing a power amplifier, comprising the steps of:
establishing a memoryless look-up table bank stored in computer readable memory, the memoryless look-up table bank having a set of memoryless predistortion functions stored therein indexed by average power values; storing memory polynomial size parameters indexed by bandwidth in the computer readable memory, the size parameters including nonlinearity order and memory depth; receiving a signal; estimating an average power of the signal; measuring bandwidth of the signal; determining a nonlinearity order and a memory depth of a memory polynomial function associated with the bandwidth of the signal from the memory polynomial size parameters stored in the computer readable memory; applying the memory polynomial function to the signal to generate a first modified signal; determining a memoryless predistortion function associated with the estimated average power of the signal from the memoryless look-up table bank; applying the memoryless predistortion function to the first modified signal to generate a second modified signal; inputting the second modified signal to a power amplifier to produce an amplified signal; outputting the amplified signal from the power amplifier; and estimating a set of coefficients of the memory polynomial function based on the nonlinearity order, the memory depth, the first modified signal and the amplified signal to define the memory polynomial function.