基于压缩感知的欠采样预失真研究

Research of compressed sensing for predistortion with relatively low sampling frequency

为解决欠采样行波管功率放大器(TWTA)预失真问题,一般工程上采用查找表结合间接学习结构数字预失真方法,但是系统复杂度在一定程度上会增加。针对这种工程问题,提出了一种基于压缩感知技术的欠采样预失真技术,在简化系统实现、提高工作稳定性的同时,可以获得较好的非线性失真优化效果。

In order to improve the TWTA digital predistortion linearizer with relatively low sampling frequency, the LUT and indirect learning architecture were used, which was cumbersome. A digital predistortion linearizer with compressed sensing technology was presented, which can provide good linearity improvement with simple and stable way.