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提出一种低复杂度的带限记忆多项式模型,通过对由低阶带限滤波器构成的带限记忆多项式模型的建模误差进行前向弥补,可以有效地降低模型所需的滤波器阶数和提高模型的建模精度,从而降低模型的复杂度。实验中,采用一款功率为35W的AB类Ga N功放和带宽为60MHz的OFDM信号证明这种方法的优越性,实验结果表明,提出的方法与传统的带限记忆多项式模型相比,复杂度更低且精度更高。
A low complexity polynomial model with limited memory is proposed. By making up for the modeling error of the limited memory polynomial model composed of low-order band-pass filters, the filter order required for the model can be effectively reduced And improve the modeling accuracy of the model, thus reducing the complexity of the model. Experimental results show that the proposed method is superior to that of a class-Ga Ga amplifier with power of 35W and an OFDM signal with a bandwidth of 60MHz. The experimental results show that compared with the traditional limited memory polynomial model, the complexity Lower and more accurate.