Recognition of Non-cooperative Radio Communication Relationships Based on Transformer

Dejun He, Xinrong Wu, Lu Yu, Tianchi Wang
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Abstract

The recognition of communication relationships under Non-cooperative conditions is significant for understanding the network composition of unknown targets, inferring network topology, and identifying key nodes, which is a prerequisite and basis for conducting efficient electronic countermeasures. However, under Non-cooperative conditions, for prior knowledge related to the target network is difficult to obtain, the communication relationships recognition faces enormous challenges. To address this issue, we construct a system model, analyze the mechanism of wireless communication interaction, extract feature series of signals from spectrum monitoring data, and propose a Transformer-based algorithm for recognizing target network communication relationships. This paper conducts simulation experiments in different scenarios to compare the Transformer-based communication relation recognition algorithm with the other four methods, such as SVM, CNN-based recognition algorithm, ResNet-based recognition algorithm, and LSTM-based recognition algorithm, respectively. And results demonstrate that the proposed algorithm shows high recognition accuracy, good anti-interference performance, and robustness.
基于变压器的非合作无线电通信关系识别
非合作条件下通信关系的识别对于了解未知目标的网络构成、推断网络拓扑结构、识别关键节点具有重要意义,是进行有效电子对抗的前提和基础。然而,在非合作条件下,由于难以获得与目标网络相关的先验知识,通信关系识别面临巨大挑战。为了解决这一问题,我们构建了系统模型,分析了无线通信交互机制,从频谱监测数据中提取信号特征序列,提出了一种基于transformer的目标网络通信关系识别算法。本文通过不同场景的仿真实验,将基于transformer的通信关系识别算法与SVM、基于cnn的识别算法、基于resnet的识别算法、基于lstm的识别算法等四种方法进行对比。实验结果表明,该算法具有较高的识别精度、良好的抗干扰性和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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