适用于DLA结构的新型功率放大器数字预失真算法

数字预失真技术通过在功率放大器的前端级联数字预失真器来补偿功放的非线性失真,而直接学习结构(Direct Learning Architecture,DLA)作为一种广泛使用的自适应数字预失真算法结构,因其预失真性能优良,前景最为看好.传统DLA预失真算法需要求得功率放大器高精度模型,其结构复杂且计算量大.针对这一问题...

Novel DLA-Based Digital Predistortion Algorithm for Power Amplifiers

The digital predistortion technique compensates for the nonlinear distortion of the power amplifier by cascading a predistortion model at the front end of the amplifier. Direct learning architecture(DLA) is one of the most widely used predistorters. However, available adaptive preditorters using direct learning architecture needs to obtain the high-precision model of the power amplifier, which is complicated in structure and requires a lot of computation. In this paper, we first propose the instantaneous complex gain(ICG) to simplify the pre-distortion structure and reduce the computational complexity. Through the simulation and experimental verification, the running time of the new pre-distortion algorithm is reduced by 35. 8% and 32. 1%, and the power ratio of the two algorithms in the adjacent channel at high and low frequencypoints is reduced by 14. 8 dB and 23. 5 dB respectively compared with that without pre-distortion.