Weighted Least Squares With Orthonormal Polynomials and Numerical Integration for Estimation of Memoryless Nonlinearity
Weighted Least Squares With Orthonormal Polynomials and Numerical Integration for Estimation of Memoryless Nonlinearity
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正交多项式加权最小二乘法和数值积分用于估计无记忆非线性
DOI：
10.1109/lwc.2020.3017807
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发表时间：
2020
影响因子：
6.3
通讯作者：
Uehara Hideyuki
中科院分区：
文献类型：
--
作者：
Komatsu Kazuki;Miyaji Yuichi;Uehara Hideyuki
放大器的非线性是无线通信中的主要缺陷之一。本文提出了一种基于加权最小二乘法的无记忆放大器非线性估计方法，并给出了该方法在复高斯信号下的理论误差分析。在所提出的方法中，输入信号和权值通过数值积分公式获得。仿真结果表明，该方法可以实现足够低的重建误差与10个测量样本的13阶非线性估计。此外，仿真结果与理论计算结果基本一致。
The nonlinearity of amplifiers is one of the major impairments in wireless communications. In this letter, we propose a novel estimation method for the memoryless nonlinearity of amplifiers using weighted least squares and provide its theoretical error analysis on complex Gaussian signals. In the proposed method, the input signal and weight value are obtained via numerical integration formulas. Simulation results show that the proposed method can achieve a sufficiently low reconstruction error with 10 measurement samples on the estimation of the 13th-order nonlinearity. In addition, the simulation and theoretical results are consistent with each other.
基于正交多项式的自适应预失真技术
DOI：
10.1109/acssc.2010.5757879
发表时间：
2010
期刊：
2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers
影响因子：
--
作者：
R. Dallinger;Henri Ruotsalainen;R. Wichman;M. Rupp
通讯作者：
M. Rupp