Weighted Least Squares With Orthonormal Polynomials and Numerical Integration for Estimation of Memoryless Nonlinearity
| Autor: | Hideyuki Uehara, Yuichi Miyaji, Kazuki Komatsu |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
nonlinear distortion
Amplifier 020208 electrical & electronic engineering Monte Carlo method 020206 networking & telecommunications 02 engineering and technology Transfer function Signal Communication system nonlinearities Complex normal distribution Numerical integration complex Gaussian process least squares Nonlinear system Control and Systems Engineering Convergence (routing) numerical integration 0202 electrical engineering electronic engineering information engineering Applied mathematics Electrical and Electronic Engineering Mathematics |
| Zdroj: | IEEE Wireless Communications Letters. 9:2197-2201 |
| ISSN: | 2162-2345 2162-2337 |
| DOI: | 10.1109/lwc.2020.3017807 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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