.png){kind=icon}
返回
The probability density function of spectral correlation function estimates
.png){kind=icon}
OA
AI
DOI：10.1186/s13634-025-01241-8.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Since published in 1988, the FFT Accumulation Method (FAM) has been used extensively to compute the Spectral Correlation Function (SCF) and the Spectral Coherence Function (SCoF) to obtain or detect cyclic features of cyclostationary signals. When the input is a Gaussian random variable (r.v.), the SCF (or SCoF) estimates are also random variables with some probability density function (pdf). Although the FAM is considered the most computationally efficient method, there has been no in-depth statistical analysis of the algorithm. This paper analyzes the statistics of spectral estimates of the SCF using the FAM algorithm by obtaining the pdf for the points covering the frequency and cycle frequency f;alpha\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left(f;\alpha\right)$$\end{document} plane, and application examples with simulation results are provided. The method proposed in the paper can be extended to other algorithms, provided they can be given by a quadratic form.
Keyword:
FFT accumulation method (FAM)
Cyclostationary detection
Cognitive radio
Spectral correlation and spectral coherence functions (SCF and SCoF)
Spectrum sensing
Constant false alarm rate (CFAR) detectors
期刊
E
IF:
1.9
论文数:
74
被引数:
3.0K
机构
引用论文
Non-Cooperative Spectrum Sensing Based on Cyclostationary Model of Digital Signals in the Context of Cognitive Radio.png)
Engineering
EngineeringIF0
PREAI
分享收藏
查看更多内容