In this paper, new digital predistortion (DPD) solutions for power amplifier (PA) linearization are proposed, with particular emphasis on reduced processing complexity in future 5G and beyond wideband radio systems. The first proposed method, referred to as the spline-based Hammerstein (SPH) approach, builds on complex spline-interpolated lookup table (LUT) followed by a linear finite impulse response (FIR) filter. The second proposed method, the spline-based memory polynomial (SMP) approach, contains multiple parallel complex spline-interpolated LUTs together with an input delay line such that more versatile memory modeling can be achieved. For both structures, gradient-based learning algorithms are derived to efficiently estimate the LUT control points and other related DPD parameters. Large set of experimental results are provided, with specific focus on 5G New Radio (NR) systems, showing successful linearization of multiple PA samples as well as a 28 GHz active antenna array, incorporating channel bandwidths up to 200 MHz. Explicit performance-complexity comparisons are also reported between the SPH and SMP DPD systems and the widely-applied ordinary memory-polynomial (MP) DPD solution. The results show that the linearization capabilities of the proposed methods are very close to that of the ordinary MP DPD, particularly with the proposed SMP approach, while having substantially lower processing complexity.

中文翻译：

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用于低复杂度数字预失真的梯度自适应样条插值 LUT 方法

在本文中，提出了用于功率放大器 (PA) 线性化的新型数字预失真 (DPD) 解决方案，特别强调降低未来 5G 及以后宽带无线电系统中的处理复杂性。第一个提出的方法，称为基于样条的 Hammerstein (SPH) 方法，建立在复杂的样条插值查找表 (LUT) 和线性有限脉冲响应 (FIR) 滤波器的基础上。第二种提出的方​​法，即基于样条的内存多项式 (SMP) 方法，包含多个并行复样条插值 LUT 以及输入延迟线，以便可以实现更通用的内存建模。对于这两种结构，基于梯度的学习算法被推导出来有效地估计 LUT 控制点和其他相关的 DPD 参数。提供了大量的实验结果，特别关注 5G 新无线电 (NR) 系统，展示了多个 PA 样本的成功线性化以及 28 GHz 有源天线阵列，合并了高达 200 MHz 的信道带宽。还报告了 SPH 和 SMP DPD 系统与广泛应用的普通内存多项式 (MP) DPD 解决方案之间的显式性能复杂性比较。结果表明，所提出方法的线性化能力与普通 MP DPD 的线性化能力非常接近，尤其是所提出的 SMP 方法，同时具有显着降低的处理复杂度。还报告了 SPH 和 SMP DPD 系统与广泛应用的普通内存多项式 (MP) DPD 解决方案之间的显式性能复杂性比较。结果表明，所提出方法的线性化能力与普通 MP DPD 的线性化能力非常接近，尤其是所提出的 SMP 方法，同时具有显着降低的处理复杂度。还报告了 SPH 和 SMP DPD 系统与广泛应用的普通内存多项式 (MP) DPD 解决方案之间的显式性能复杂性比较。结果表明，所提出方法的线性化能力与普通 MP DPD 的线性化能力非常接近，尤其是所提出的 SMP 方法，同时具有显着降低的处理复杂度。