A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Models

doi:10.1109/TCCN.2024.3520958

	A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Models
	Lu, Yao 1,2; Zhu, Yutao 1,2; Li, Yuqi 3; Xu, Dongwei 1,2; Lin, Yun 4; Xuan, Qi 2,5; Yang, Xiaoniu
	2025-08-01
发表期刊	IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING
ISSN	2332-7731
卷号	11 期号:4 页码:2123-2134
摘要	With the successful application of deep learning in communications systems, deep neural networks are becoming the preferred method for Automatic Modulation Recognition (AMR). Although these AMR models yield impressive results, they often come with high computational complexity and large model sizes, which hinders their practical deployment in communication systems. To address this challenge, we propose a novel layer pruning method, PSR. Specifically, we decompose the AMR model into several consecutive blocks, each containing consecutive layers with similar semantics. Then, we identify layers that need to be preserved within each block based on their contribution. Finally, we reassemble the pruned blocks and fine-tune the compact model. Extensive experiments on five datasets demonstrate the efficiency and effectiveness of PSR over a variety of state-of-the-art baselines, including layer pruning and channel pruning methods.
关键词	Computational modeling Deep learning Modulation Training Pattern classification Computational complexity Vectors Semantics Perturbation methods Indexes Automatic modulation recognition layer pruning deep learning edge devices
DOI	10.1109/TCCN.2024.3520958
收录类别	SCI
语种	英语
资助项目	Key R&D Program of Zhejiang[2022C01018] ; National Natural Science Foundation of China[U21B2001] ; National Natural Science Foundation of China[61973273]
WOS研究方向	Telecommunications
WOS类目	Telecommunications
WOS记录号	WOS:001547513900012
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/41757
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Xuan, Qi
作者单位	1.Zhejiang Univ Technol, Inst Cyberspace Secur, Coll Informat Engn, Hangzhou 310056, Peoples R China 2.Zhejiang Univ Technol, Binjiang Inst Artificial Intelligence, Hangzhou 310056, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing 100864, Peoples R China 4.Harbin Engn Univ, Coll Informat & Commun Engn, Harbin 150001, Peoples R China 5.Zhejiang Univ Technol, Inst Cyberspace Secur, Coll Informat Engn, Hangzhou 310023, Peoples R China
推荐引用方式 GB/T 7714	Lu, Yao,Zhu, Yutao,Li, Yuqi,et al. A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Models[J]. IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING,2025,11(4):2123-2134.
APA	Lu, Yao.,Zhu, Yutao.,Li, Yuqi.,Xu, Dongwei.,Lin, Yun.,...&Yang, Xiaoniu.(2025).A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Models.IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING,11(4),2123-2134.
MLA	Lu, Yao,et al."A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Models".IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING 11.4(2025):2123-2134.