脈沖噪聲中基于指數(shù)函數(shù)的可變拖尾非線性變換設(shè)計(jì)

羅忠濤; 詹燕梅; 郭人銘; 張楊勇

doi:10.11999/JEIT190401

脈沖噪聲中基于指數(shù)函數(shù)的可變拖尾非線性變換設(shè)計(jì)

doi: 10.11999/JEIT190401

1.
重慶郵電大學(xué)通信與信息工程學(xué)院重慶 400065
2.
武漢船舶通信研究所武漢 430079

基金項(xiàng)目: 國(guó)家自然科學(xué)基金 (61701067, 61771085, 61671095)

詳細(xì)信息

作者簡(jiǎn)介:
羅忠濤：男，1984年生，講師，碩士生導(dǎo)師，研究方向?yàn)榻y(tǒng)計(jì)信號(hào)處理與數(shù)字圖像處理

詹燕梅：女，1995年生，碩士生，研究方向?yàn)榉歉咚乖肼曅盘?hào)處理理論與技術(shù)

郭人銘：男，1995年生，碩士生，研究方向?yàn)榇髿庠肼暦治雠c低頻通信技術(shù)

張楊勇：男，1983生年，高級(jí)工程師，研究方向?yàn)榈皖l通信技術(shù)與信號(hào)處理

通訊作者:
羅忠濤　luozt@cqupt.edu.cn

中圖分類號(hào): TN911
計(jì)量
- 文章訪問(wèn)數(shù): 2438
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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2019-06-05
- 修回日期: 2019-12-09
- 網(wǎng)絡(luò)出版日期: 2019-12-23
- 刊出日期: 2020-06-04

Variable Tailing Nonlinear Transformation Design Based on Exponential Function in Impulsive Noise

1.
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Wuhan Maritime Communication Research Institute, Wuhan 430079, China

Funds: The National Natural Science Foundation of China (61701067, 61771085, 61671095)

摘要

摘要:
針對(duì)脈沖噪聲中的信號(hào)檢測(cè)問(wèn)題，該文提出一種基于指數(shù)函數(shù)的非線性變換函數(shù)設(shè)計(jì)與優(yōu)化方法。該方法利用指數(shù)函數(shù)衰減速度可調(diào)的優(yōu)點(diǎn)，適用于脈沖噪聲的各種分布模型。通過(guò)引入效能函數(shù)，將非線性函數(shù)設(shè)計(jì)問(wèn)題轉(zhuǎn)化為以效能最大化為目標(biāo)的閾值與底數(shù)參數(shù)優(yōu)化問(wèn)題。由于效能是關(guān)于待優(yōu)化參數(shù)的連續(xù)可導(dǎo)且單峰函數(shù)，該優(yōu)化問(wèn)題可采用數(shù)值優(yōu)化方法如單純形法快速穩(wěn)健地求解。性能分析表明，針對(duì)脈沖噪聲常用的對(duì)稱α穩(wěn)定分布、Class A分布和高斯混合分布，該文方法均能取得基本最優(yōu)檢測(cè)性能，基于實(shí)測(cè)大氣噪聲仿真的通信誤碼率也明顯優(yōu)于傳統(tǒng)的削波器和置零器。因此，該文為各種分布的脈沖噪聲提供了一個(gè)統(tǒng)一的最優(yōu)抑制解決方法。
- 脈沖噪聲 /
- 非線性變換 /
- 指數(shù)函數(shù) /
- 優(yōu)化算法
Abstract:
A novel design of nonlinear transformation function for the signal detection in impulsive noise is proposed. The proposed method takes the advantage of adjustable fading factors of the exponential function, it can be effective for different models of impulsive noise. By introducing the efficacy as the objective function, nonlinear design is converted into the problem of optimizing the threshold and bottom parameters to maximize the efficacy. Since the efficacy is continuous, derivative, and unimodal, the optimization problem can be easily solved by the traditional optimization methods, such as the Nelder-Mead simplex method. Analysis shows that the proposed design can obtain the optimal performance in the widely-used models of impulsive noise, including the symmetric α-stable model, the Class A model, and the Gaussian mixture model. Simulation on real atmospheric noise demonstrates that the proposed design is obviously better than the traditional clipper and blanker. Thus, this paper proposes an optimal and uniform solution for suppressing impulsive noise of various models.
- Impulsive noise /
- Nonlinear transformation /
- Exponential function /
- Optimization algorithm

HTML全文

圖 1 非線性變換函數(shù)的3種模式示意圖

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圖 2 在${\rm{S}}\alpha {\rm{S}}$噪聲下的$E\left( {{g_X},T,a} \right)$曲面與曲線，$\alpha $=1.5, $\sigma $=1

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圖 3 ${\rm{S}}\alpha {\rm{S}}$噪聲中非線性函數(shù)比較

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圖 4 ${\rm{S}}\alpha {\rm{S}}$噪聲中非線性函數(shù)效能

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圖 5 Class A噪聲中非線性函數(shù)效能

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圖 6 在${\rm{S}}\alpha {\rm{S}}$噪聲$\alpha $變化時(shí)的最優(yōu)參數(shù)

下載: 全尺寸圖片幻燈片

圖 7 通信誤碼率與信噪比的關(guān)系

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表 1 高斯混合噪聲中非線性變換的效能

$(\varepsilon ,\sigma _2^2)$=	(0.3 10)	(0.3 100)	(0.3 1000)	(0.1 10)	(0.1 100)	(0.1 1000)	(0.01 10)	(0.01 100)	(0.01 1000)
局部最優(yōu)檢測(cè)	0.5198	0.5709	0.6338	0.7935	0.8316	0.8678	0.9695	0.9796	0.9846
最優(yōu)置零器	0.4637	0.5421	0.6196	0.7624	0.8160	0.8611	0.9647	0.9752	0.9837
最優(yōu)削波器	0.4592	0.3906	0.3662	0.7407	0.6958	0.6793	0.9568	0.9453	0.9409
GZMNL	0.5056	0.5674	0.6328	0.7883	0.8300	0.8672	0.9689	0.9774	0.9846
GGM	0.4540	0.4982	0.5791	0.7576	0.7924	0.8311	0.9620	0.9691	0.9773
X 軸平移模式	0.5079	0.5652	0.6313	0.7880	0.8286	0.8665	0.9686	0.9772	0.9845
Y 軸平移模式	0.4939	0.5044	0.5512	0.7626	0.7614	0.7858	0.9599	0.9557	0.9589
定點(diǎn)平移模式	0.5091	0.5282	0.5697	0.7776	0.7837	0.8032	0.9636	0.9618	0.9641

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