A robust digital baseband predistorter constructed using memory polynomials

Power amplifiers (PAs) are inherently nonlinear devices and are used in virtually all communications systems. Digital baseband predistortion is a highly cost-effective way to linearize PAs, but most existing architectures assume that the PA has a memoryless nonlinearity. 

For wider bandwidth applications such as wideband code-division multiple access (WCDMA) or wideband orthogonal frequency-division multi-plexing (W-OFDM), PA memory effects can no longer be ignored, and memoryless predistortion has limited effectiveness. 

In this paper, instead of focusing on a particular PA model and building a corresponding predistorter, we focus directly on the predistorter structure. In particular, we propose a memory polynomial model for the predistorter and implement it using an indirect learning architecture. Linearization performance is demonstrated on a three-carrier WCDMA signal.