A Dual Frequency Predistortion Adaptive Sparse Signal Reconstruction Algorithm

oleh: Mingming Gao, Shaojun Fang*, Jinling Wang, Xueman Zhang, Yuan Cao

Format: Article
Diterbitkan: Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek 2022-01-01

Deskripsi

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.