基于可微分架构搜索的多载波信号自动调制识别  

Differentiable architecture search-based automatic modulation recognition for multi-carrier signals

作　　者：李杰[1] 李靖[1] 吕璐[1] 宫丰奎[1] LI Jie;LI Jing;LYU Lu;GONG Fengkui(State Key Laboratory of Integrated Service Networks,Xidian University,Xi’an 710071,China)

机构地区：[1]西安电子科技大学空天地一体化综合业务网全国重点实验室,陕西西安710071

出　　处：《通信学报》2024年第9期14-25,共12页Journal on Communications

基　　金：国家自然科学基金资助项目(No.62271368,No.62001354);陕西省重点研发计划基金资助项目(No.2023-YBGY-041);中国博士后科学基金资助项目(No.BX20190264,No.2019M650258)。

摘　　要：针对城市多径信道下缺乏多载波信号通用数据集,以及传统信号特征与网络模型难以有效识别低信噪比下失真信号调制类型的问题,提出一种基于可微分架构搜索的多载波信号自动调制识别算法。首先,产生了常见OFDM、FBMC与OTFS多载波信号经过典型城市多径信道的接收信号数据集,选取对调制参数不敏感的信号时频图作为特征向量来训练神经网络;其次,采用可微分架构搜索方法自动搜索最佳网络结构,避免了网络结构设计的反复验证工作;最后,在特征学习过程中引入联合注意力机制,将失真信号特征进行空间转换以降低多径干扰影响,同时计算特征图各通道信息权重并排序,以提升相关特征图通道的分类效果。仿真结果表明,所提算法不仅能提升在城市多径信道环境下尤其是低信噪比时的识别正确率,而且对调制参数变化和小样本场景具有更好的鲁棒性。Considering the lack of a general multi-carrier signal dataset in urban multipath channels,and the challenge of recognizing the modulation types of distorted signals at low signal-to-noise ratio(SNR),a differentiable architecture search-based(DARTS)automatic modulation recognition algorithm for multi-carrier signals was proposed.Firstly,the received signal datasets of commonly used multi-carrier signals,i.e.,orthogonal frequency division multiplexing,filter bank multi-carrier,and orthogonal time frequency space,were generated over typical urban multipath channels.The timefrequency images,which were insensitive to modulation parameters,were selected as feature vectors to train the neural network.Secondly,DARTS was employed to automatically search the optimal network architecture.Finally,a joint attention mechanism was introduced into the feature learning process.This mechanism spatially transforming distorted signal features to mitigate the impact of multipath interference,while also calculating and sorting the information weights for each channel of the feature maps to improve the recognition performance of the relevant feature map channels.Simulation results demonstrate that the proposed algorithm improves accuracy in urban multipath channels,especially at low SNR,while simultaneously providing better robustness to modulation parameter variations and small-sample scenarios.

关 键 词：可微分架构搜索 多载波信号 自动调制识别 城市多径信道 联合注意力机制 

分 类 号：TN92[电子电信—通信与信息系统]