Research on Modulation Recognition Method in Low SNR Based on LSTM Article Swipe

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Beiming Zhang , Guoping Chen , Chun Jiang ·

YOU? · · 2022 · Open Access · · DOI: https://doi.org/10.1088/1742-6596/2189/1/012003

Modulation mode recognition of radio signal is a committed step between signal detection and signal demodulation. At present, quite a lot studies have fully proved that deep learning algorithms can effectively identify the modulation pattern of radio signals. However, the sudden decline of recognition accuracy under the condition of low signal-to-noise ratio needs to be continuously studied and solved. Inspired by the excellent performance of recurrent neural network in signal recognition, this article optimizes and improves the existing system methods, realizes the noise reduction processing of low signal-to-noise ratio signals, and further solves the problem of low recognition accuracy. Through a large number of experimental tests using RML public dataset, the effectiveness of this paper is verified. The results show that the accuracy of modulation pattern recognition of low signal-to-noise ratio signals reaches an average of 27.2%. At last, the paper analyzes the existing problems and optimization points, and looks forward to the further research of relevant contents in the future.

Related Topics

Computer Science

Modulation (Music)

Artificial Intelligence

Concepts

Demodulation Computer science Modulation (music) SIGNAL (programming language) Noise (video) Artificial intelligence Pattern recognition (psychology) Speech recognition Signal-to-noise ratio (imaging) Noise reduction Artificial neural network Signal processing Telecommunications Acoustics Channel (broadcasting) Radar Programming language Physics Image (mathematics)

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Type: article
Language: en
Landing Page: https://doi.org/10.1088/1742-6596/2189/1/012003
OA Status: diamond
Cited By: 8
References: 6
Related Works: 10
OpenAlex ID: https://openalex.org/W4210987079

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DOI: https://doi.org/10.1088/1742-6596/2189/1/012003

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Title: Research on Modulation Recognition Method in Low SNR Based on LSTM

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Language: en

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Publication year: 2022

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Publication date: 2022-02-01

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Authors: Beiming Zhang, Guoping Chen, Chun Jiang

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Landing page: https://doi.org/10.1088/1742-6596/2189/1/012003

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Concepts: Demodulation, Computer science, Modulation (music), SIGNAL (programming language), Noise (video), Artificial intelligence, Pattern recognition (psychology), Speech recognition, Signal-to-noise ratio (imaging), Noise reduction, Artificial neural network, Signal processing, Telecommunications, Acoustics, Channel (broadcasting), Radar, Programming language, Physics, Image (mathematics)

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Cited by: 8

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Citations by year (recent): 2025: 1, 2024: 4, 2023: 1, 2022: 2

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abstract_inverted_index.accuracy.	99
abstract_inverted_index.committed	9
abstract_inverted_index.condition	48
abstract_inverted_index.detection	13
abstract_inverted_index.excellent	63
abstract_inverted_index.optimizes	74
abstract_inverted_index.recurrent	66
abstract_inverted_index.reduction	84
abstract_inverted_index.verified.	117
abstract_inverted_index.Modulation	1
abstract_inverted_index.algorithms	29
abstract_inverted_index.modulation	34, 125
abstract_inverted_index.processing	85
abstract_inverted_index.effectively	31
abstract_inverted_index.performance	64
abstract_inverted_index.recognition	3, 44, 98, 127
abstract_inverted_index.continuously	56
abstract_inverted_index.experimental	105
abstract_inverted_index.optimization	147
abstract_inverted_index.recognition,	71
abstract_inverted_index.demodulation.	16
abstract_inverted_index.effectiveness	112
abstract_inverted_index.signal-to-noise	51, 88, 130
cited_by_percentile_year.max	98
cited_by_percentile_year.min	89
corresponding_author_ids	https://openalex.org/A5054927807
countries_distinct_count	1
institutions_distinct_count	3
corresponding_institution_ids	https://openalex.org/I183067930
citation_normalized_percentile.value	0.81315758
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	False