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在间接学习结构的数字预失真技术中,需要使用自适应算法来更新查找表(LUT,Look UpTable)。在各种自适应算法中,RLS算法收敛快但是复杂度高。为降低其计算复杂度,这里提出采用二维坐标下降的RLS(RLS_DCD,RLS using Dichotomous Coordinate Descent)算法更新查找表,达到在数字预失真器系数的预测过程中以较低的运算量实现快速收敛的目的。仿真结果和分析表明,与采用RLS的自适应查找表更新算法比较,在邻信道功率比(ACPR,Adjacent Channel Power Ratio)改善指标相当的情况下,采用RLS_DCD的自适应查找表更新算法能大幅度降低其运算量。
In the digital pre-distortion technique of indirect learning architecture, an adaptive algorithm is needed to update the Look Up Table (LUT). Among various adaptive algorithms, the RLS algorithm converges quickly but with high complexity. In order to reduce the computational complexity, we propose to update the look-up table using the RLS using DLS (Coordinated Descent) RLS (RLS_DCD) algorithm to reduce the computation complexity of the digital predistorter the goal of. The simulation results and analysis show that, compared with the adaptive lookup table update algorithm using RLS, the adaptive lookup table update algorithm using RLS_DCD can significantly reduce the adjacent channel power ratio (ACPR, Adjacent Channel Power Ratio) Reduce the amount of computation.