Machine learning based technique for detection of communication signal under noise floor
The goal of this dissertation is to try to apply artificial intelligence algorithms to the field of signal detection. First, I studied and simulated the communication channel and common digital communication modulations to construct the experimental environment. The traditional signal detection...
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2022
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sg-ntu-dr.10356-1622662022-10-11T05:56:11Z Machine learning based technique for detection of communication signal under noise floor Zhong, Hongrui Teh Kah Chan School of Electrical and Electronic Engineering EKCTeh@ntu.edu.sg Engineering::Electrical and electronic engineering::Wireless communication systems The goal of this dissertation is to try to apply artificial intelligence algorithms to the field of signal detection. First, I studied and simulated the communication channel and common digital communication modulations to construct the experimental environment. The traditional signal detection algorithms are applied to the simulated channel to observe the detection level of the traditional algorithm. These algorithms include: Envelope Detection, Correlation Detection and Power Spectrum Detection. Then Convolutional Neural Network (CNN) is mainly discussed, including the basic thinking of CNN, the adjustment of various parameters for the neural network, and the algorithm results. Keywords: Artificial Intelligence Algorithms, Signal Detection, Modulations, Envelope Detection, Correlation Detection, Power Spectrum Detection, Convolutional Neural Network. Master of Science (Communications Engineering) 2022-10-11T05:56:11Z 2022-10-11T05:56:11Z 2022 Thesis-Master by Coursework Zhong, H. (2022). Machine learning based technique for detection of communication signal under noise floor. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/162266 https://hdl.handle.net/10356/162266 en ISM-DISS-02424 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering::Wireless communication systems Zhong, Hongrui Machine learning based technique for detection of communication signal under noise floor |
description |
The goal of this dissertation is to try to apply artificial intelligence algorithms
to the field of signal detection.
First, I studied and simulated the communication channel and common digital
communication modulations to construct the experimental environment. The traditional
signal detection algorithms are applied to the simulated channel to observe
the detection level of the traditional algorithm. These algorithms include:
Envelope Detection, Correlation Detection and Power Spectrum Detection. Then
Convolutional Neural Network (CNN) is mainly discussed, including the basic
thinking of CNN, the adjustment of various parameters for the neural network,
and the algorithm results.
Keywords: Artificial Intelligence Algorithms, Signal Detection, Modulations, Envelope
Detection, Correlation Detection, Power Spectrum Detection, Convolutional
Neural Network. |
author2 |
Teh Kah Chan |
author_facet |
Teh Kah Chan Zhong, Hongrui |
format |
Thesis-Master by Coursework |
author |
Zhong, Hongrui |
author_sort |
Zhong, Hongrui |
title |
Machine learning based technique for detection of communication signal under noise floor |
title_short |
Machine learning based technique for detection of communication signal under noise floor |
title_full |
Machine learning based technique for detection of communication signal under noise floor |
title_fullStr |
Machine learning based technique for detection of communication signal under noise floor |
title_full_unstemmed |
Machine learning based technique for detection of communication signal under noise floor |
title_sort |
machine learning based technique for detection of communication signal under noise floor |
publisher |
Nanyang Technological University |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/162266 |
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1749179130955431936 |