电讯技术2026，Vol.66Issue(1)：11-20,10.DOI:10.20079/j.issn.1001-893x.240911001
一种基于FL-TransCNN神经网络的水声智能频谱感知算法
An Underwater Acoustic Intelligent Spectrum Sensing Algorithm Based on FL-TransCNN Neural Network
摘要
Abstract
To improve the spectrum utilization,an underwater acoustic intelligent spectrum sensing algorithm based on federated learning(FL),Transformer and convolutional neural network(CNN)is proposed.Firstly,information sharing in a data isolation state is realized based on FL,and Paillier encryption technology is applied to guarantee weight encryption.Secondly,the local sensing data is constructed into a time-frequency spectrum by continuous wavelet transform.Finally,a TransCNN perceptron is constructed by combining CNN and Transformer,and high-precision perception is achieved through parallel branches.Compared with that of RepVGG,Swin-Transformer,YOLOv7,and MobileNet algorithms,the average detection probability of the proposed algorithm based on the FL-TransCNN neural network is improved by 4%to 10%and the average false alarm probability is reduced by 2%to 9%in-18 dB to 0 dB signal-to-noise ratio.关键词
海洋物联网/智能频谱感知/联邦学习/连续小波变换/深度可分离卷积Key words
marine Internet of Things/intelligent spectrum sensing/federated learning/continuous wavelet transform/depthwise separable convolution分类
信息技术与安全科学引用本文复制引用
李玉芳,王锴,张力良,徐凌伟,Thomas Aaron Gulliver..一种基于FL-TransCNN神经网络的水声智能频谱感知算法[J].电讯技术,2026,66(1):11-20,10.基金项目
国家自然科学基金资助项目(62201313) （62201313）
数字化学习技术集成与应用教育部工程研究中心创新基金项目(1321012) （1321012）
