Systems and methods for multiband linearization architecture using kernel regression

Abstract

Systems and methods for multiband linearization using kernel regression are provided. In some embodiments, a method includes, for each band of the multiband transmitter: transforming a group of input signals from one or more bands into a constructed input vector space to provide transformed input signals; predistorting the transformed input signals to provide a respective group of predistorted input signals in accordance with a Radial Basis Function (RBF) kernel regression; and transmitting the respective group of predistorted input signals. In this way, some advantages include a semi blind approach as one need not to account for the non-linearity order as in Volterra-based DPD for example, only the memory depth is needed to be incorporated to the input vector space. The computational complexity of DPD is reduced compared to Volterra-based DPD. Implementation complexity is relaxed by means of using a 1D Lookup Table implementation regardless of the number of bands.