Low-rate identification of memory polynomials

We propose a new approach for the low-rate identification of memory polynomials (MPs), which are frequently used to model RF power amplifiers (PAs). Based on ideas from the finite rate of innovation framework, we find the coefficients of the MP in the frequency domain, which requires a relatively small number of measurements (samples), commensurate with the degrees of freedom in the model. By choosing a random set of frequency components, the stability of the identification is ensured. We show that the method can be used directly for special input signals, such as one used for orthogonal frequency division multiplexing, and extend the idea for arbitrary inputs. Experiments using measured data from a class-AB PA demonstrate the effectiveness of the approach. The sampling rate for identifying this PA is reduced by a factor of 1024 (from 107.52MHz to 105 kHz).