Algorithms for Modulation Recognition of Narrowband Power Line Carrier Communication Signals. Issue 1 (February 2021)
- Record Type:
- Journal Article
- Title:
- Algorithms for Modulation Recognition of Narrowband Power Line Carrier Communication Signals. Issue 1 (February 2021)
- Main Title:
- Algorithms for Modulation Recognition of Narrowband Power Line Carrier Communication Signals
- Authors:
- Li, Kun
Zhao, Hongjun
Wang, Yongjian - Abstract:
- Abstract: Automatic identification of modulated signals is an important technology of power line communication. Aiming at the problems of low signal recognition rate and characteristic parameter extraction in power line communication channel, this paper uses amplitude variance value of wavelet transform and higher order cumulant as the identification parameter, and designs a signal recognizer based on improved support vector machine. Under the condition of power line channel environment, the recognizer of this paper is less than the existing recognition method in the computational complexity, and has good robustness to power line noise. At the same time, it avoids the shortcomings of traditional neural network such as under-learning and over-learning. The simulation results show that when the SNR is 5 dB, power line communication signals through the recognizer, which the correct identification rate can reach 91%.
- Is Part Of:
- Journal of physics. Volume 1828:Issue 1(2021)
- Journal:
- Journal of physics
- Issue:
- Volume 1828:Issue 1(2021)
- Issue Display:
- Volume 1828, Issue 1 (2021)
- Year:
- 2021
- Volume:
- 1828
- Issue:
- 1
- Issue Sort Value:
- 2021-1828-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-02
- Subjects:
- Physics -- Congresses
530.5 - Journal URLs:
- http://www.iop.org/EJ/journal/1742-6596 ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1742-6596/1828/1/012031 ↗
- Languages:
- English
- ISSNs:
- 1742-6588
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5036.223000
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- 15937.xml