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Low Complexity Coefficient Estimation for Concurrent Dual-Band Digital Predistortion

机译:并发双频数字预失真的低复杂度系数估计

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Dual-band or multi-band RF power amplifiers (PAs) have attracted a lot of attention in recent years as they rise to the challenge of segmented spectrum allocation in wireless systems. Adaptive digital predistortion (DPD) for concurrent dual-band PAs evolves from existing DPD for single-band PAs. In this paper, we derive the baseband dual-band Volterra model from the corresponding passband model. In addition, the computational complexity of the DPD estimation algorithm increases dramatically as the number of coefficients for dual-band DPD is much larger than that for single-band DPD. In this paper, we propose a low complexity DPD coefficient estimation algorithm for concurrent dual-band PAs based on polar decomposition of the general Volterra model. By dividing complex-valued coefficient estimation into amplitude estimation and phase estimation separately, the proposed algorithm achieves at most 75% computational complexity reduction. Moreover, the proposed algorithm can achieve similar performance with the conventional coefficient estimation method. Simulation and measured results validate performance of the proposed algorithm for a solid-state PA.
机译:近年来,双频带或多频带RF功率放大器(PA)引起了无线系统中分段频谱分配的挑战,引起了人们的广泛关注。并发双频段PA的自适应数字预失真(DPD)是从单频段PA的现有DPD演变而来的。在本文中,我们从相应的通带模型推导了基带双带Volterra模型。另外,由于双频DPD的系数数量远大于单频DPD的系数数量,因此DPD估计算法的计算复杂度急剧增加。在本文中,我们提出了一种基于通用Volterra模型的极性分解的并发双频PA的低复杂度DPD系数估计算法。通过将复数值系数估计分别分为幅度估计和相位估计,该算法最多可减少75%的计算复杂度。此外,所提出的算法可以实现与常规系数估计方法相似的性能。仿真和实测结果验证了该算法对固态PA的性能。

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