电子学报2024，Vol.52Issue(12)：3976-3984,9.DOI:10.12263/DZXB.20230993
基于高阶矩特征选择和权值优化的信噪比估计
Estimation of Signal-to-Noise Ratio Based on Feature Selection and Weight Optimization of High-Order Moments
摘要
Abstract
As an important part of signal parameter estimation,signal-to-noise ratio(SNR)estimation can provide pri-or information for power control,modulation classification,channel estimation,and dynamic mode switching,etc.Recently,high-order moments(HOMs)based algorithms have been widely concerned due to the advantages of low computational complexity and high real-time property.However,the estimation performance of the HOMs-based algorithms is still con-strained in extremely low or high SNR regions.In this paper,a SNR estimation algorithm based on feature selection and lin-ear combination of HOMs is designed,according to the distribution characteristics of HOMs.Firstly,the HOMs are screened by analyzing the relationship between different moments and SNR values.Based on this,we resort to the linear combination of the selected HOMs to estimate SNR.And the weights of linear combination are calculated by designing an optimization problem.The simulation results show that the proposed SNR estimation scheme makes a tradeoff among the estimation performance of high and low SNR regions.Compared with the existing HOMs-based algorithms,the proposed al-gorithm has a more comprehensive performance in the range of-10 dB to 20dB.关键词
信噪比估计/高阶矩/Nakagami衰落信道/特征选择/权值优化Key words
estimation of signal-to-noise ratio/high-order moment/Nakagami-fading channel/feature selection/op-timization of weights分类
信息技术与安全科学引用本文复制引用
李涛,苏楠,韦荻山,李勇朝,朱若楠,赵新玉,周帅..基于高阶矩特征选择和权值优化的信噪比估计[J].电子学报,2024,52(12):3976-3984,9.基金项目
广州市基础与应用基础研究基金(No.2023A04J1740) Guangzhou Basic and Applied Basic Research Foundation(No.2023A04J1740) （No.2023A04J1740）
