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间接学习结构数字基带预失真器的实现需要估计模拟链路延时,而链路延时估计算法存在估计误差,此误差对预失真器性能的影响目前未有相关研究。该文以邻近信道功率比(ACPR)和归一化均方误差(NM SE)两项指标作为衡量标准,研究了延时估计误差对间接学习结构预失真器补偿性能的影响。结果表明,间接学习结构预失真器对延时估计误差敏感,在N yqu ist采样的预失真器系统中,只有当估计误差不超过系统采样间隔的1/64时,才能保证此预失真器能够有效地实现功放线性化。
The implementation of the digital baseband predistorter in indirect learning architecture needs to estimate the delay of the analog link, but there is an estimation error in the link delay estimation algorithm. The impact of this error on the performance of the predistorter is not studied at present. In this paper, two indicators of adjacent channel power ratio (ACPR) and normalized mean square error (NM SE) are taken as the standard to study the influence of delay estimation error on compensation performance of indirect learning structure predistorter. The results show that the predistorter of indirect learning structure is sensitive to the delay estimation error. In the Nyquist sampling predistorter system, the predistorter can be guaranteed only when the estimation error does not exceed 1/64 of the system sampling interval Effective amplifier linearization.