Nonlinearity Design With Power-Law Tails for Correlation Detection in Impulsive Noise
Impulsive noise plays an important role in power line communication among other applications. To improve the communication performance, this paper proposes a novel design of nonlinear processing which improves the fundamental performance of signal detection in impulsive noise. Power-law tails are fi...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9016243/ |
| _version_ | 1818557684458192896 |
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| author | Zhongtao Luo Edmond A. Jonckheere |
| author_facet | Zhongtao Luo Edmond A. Jonckheere |
| author_sort | Zhongtao Luo |
| collection | DOAJ |
| description | Impulsive noise plays an important role in power line communication among other applications. To improve the communication performance, this paper proposes a novel design of nonlinear processing which improves the fundamental performance of signal detection in impulsive noise. Power-law tails are firstly introduced in nonlinearity design to provide adjustable decay factors for different distributions. Four modes of nonlinearity functions are developed and analyzed. By taking the exponent and the threshold as two arguments, we formulate the nonlinearity design as an optimization problem of maximizing the efficacy function, which is the fundamental measurement for detecting a deterministic signal in impulsive noise. Given that the efficacy function is differentiable, unimodal but without closed-form derivatives, we propose to solve the optimization problem by derivative-free methods, e.g. the Nelder-Mead simplex method. As concept demonstration, our method is used for three commonly-used distribution examples. Results show that our nonlinearity design can achieve almost the same efficacy and detection performance as the locally optimal detector, with the advantage of easy-to-apply closed form expressions. |
| first_indexed | 2024-12-14T00:02:47Z |
| format | Article |
| id | doaj.art-8989d34476fa4e5bb41122c593a8e4f5 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T00:02:47Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-8989d34476fa4e5bb41122c593a8e4f52022-12-21T23:26:14ZengIEEEIEEE Access2169-35362020-01-018406674067910.1109/ACCESS.2020.29764999016243Nonlinearity Design With Power-Law Tails for Correlation Detection in Impulsive NoiseZhongtao Luo0https://orcid.org/0000-0003-4458-1698Edmond A. Jonckheere1https://orcid.org/0000-0002-7205-4273School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, ChinaMing Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, USAImpulsive noise plays an important role in power line communication among other applications. To improve the communication performance, this paper proposes a novel design of nonlinear processing which improves the fundamental performance of signal detection in impulsive noise. Power-law tails are firstly introduced in nonlinearity design to provide adjustable decay factors for different distributions. Four modes of nonlinearity functions are developed and analyzed. By taking the exponent and the threshold as two arguments, we formulate the nonlinearity design as an optimization problem of maximizing the efficacy function, which is the fundamental measurement for detecting a deterministic signal in impulsive noise. Given that the efficacy function is differentiable, unimodal but without closed-form derivatives, we propose to solve the optimization problem by derivative-free methods, e.g. the Nelder-Mead simplex method. As concept demonstration, our method is used for three commonly-used distribution examples. Results show that our nonlinearity design can achieve almost the same efficacy and detection performance as the locally optimal detector, with the advantage of easy-to-apply closed form expressions.https://ieeexplore.ieee.org/document/9016243/Impulsive noisesignal detectionnonlinearitypower-law tailnumerical optimization |
| spellingShingle | Zhongtao Luo Edmond A. Jonckheere Nonlinearity Design With Power-Law Tails for Correlation Detection in Impulsive Noise IEEE Access Impulsive noise signal detection nonlinearity power-law tail numerical optimization |
| title | Nonlinearity Design With Power-Law Tails for Correlation Detection in Impulsive Noise |
| title_full | Nonlinearity Design With Power-Law Tails for Correlation Detection in Impulsive Noise |
| title_fullStr | Nonlinearity Design With Power-Law Tails for Correlation Detection in Impulsive Noise |
| title_full_unstemmed | Nonlinearity Design With Power-Law Tails for Correlation Detection in Impulsive Noise |
| title_short | Nonlinearity Design With Power-Law Tails for Correlation Detection in Impulsive Noise |
| title_sort | nonlinearity design with power law tails for correlation detection in impulsive noise |
| topic | Impulsive noise signal detection nonlinearity power-law tail numerical optimization |
| url | https://ieeexplore.ieee.org/document/9016243/ |
| work_keys_str_mv | AT zhongtaoluo nonlinearitydesignwithpowerlawtailsforcorrelationdetectioninimpulsivenoise AT edmondajonckheere nonlinearitydesignwithpowerlawtailsforcorrelationdetectioninimpulsivenoise |