A Dual Frequency Predistortion Adaptive Sparse Signal Reconstruction Algorithm

Abstract

To solve the problem of a high sampling rate in the dual-frequency power amplifier predistortion system, a dual frequency predistortion adaptive sparse signal reconstruction algorithm is proposed. Firstly, a memory effect compensator based on piecewise polynomial model is adopted. The signal fusion is interpreted as the problem of Compressed Sensing sampling reconstruction. In the predistortion feedback loop, the missing fifth-order and high-order cross-modulation signals are reconstructed accurately by using the adaptive sparse algorithm. The minimum mean square solution of coefficient weight approximates the optimal value, and the acquisition error is reduced to improve the linearization effect. The experimental results show that it is of great significance to reduce the sampling rate of dual band predistortion and improve the linearity of power amplifier.

Keywords

• adaptive reconstruction algorithm
• compressed sensing
• dual frequency amplifier
• predistortion
• subspace tracking