A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Models
文献类型：期刊论文
| 作者 | Lu, Yao2,3; Zhu, Yutao2,3; Li, Yuqi4; Xu, Dongwei2,3; Lin, Yun5; Xuan, Qi1,3; Yang, Xiaoniu |
| 刊名 | IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING
 |
| 出版日期 | 2025-08-01 |
| 卷号 | 11期号:4页码:2123-2134 |
| 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 |
| ISSN号 | 2332-7731 |
| DOI | 10.1109/TCCN.2024.3520958 |
| 英文摘要 | 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. |
| 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 |
| 语种 | 英语 |
| WOS记录号 | WOS:001547513900012 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/41756]  |
| 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 310023, Peoples R China 2.Zhejiang Univ Technol, Inst Cyberspace Secur, Coll Informat Engn, Hangzhou 310056, Peoples R China 3.Zhejiang Univ Technol, Binjiang Inst Artificial Intelligence, Hangzhou 310056, Peoples R China 4.Chinese Acad Sci, Inst Comp Technol, Beijing 100864, Peoples R China 5.Harbin Engn Univ, Coll Informat & Commun Engn, Harbin 150001, 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. |
入库方式： OAI收割
来源：计算技术研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。