A Deep Generative Model for Synthesizing Labeled Wireless Signals

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On September 7, 2026, a research paper titled “A Deep Generative Model for Synthesizing Labeled Wireless Signals” was published on arXiv cs.AI. This study proposed a deep generative model aimed at synthesizing labeled wireless signal data.

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Key entitiesKEY ENTITIES

IIns-GANInter-Instance Generative Adversarial NetworksUWBUltra-Wideband

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SignalsSIGNALS

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Inter-Instance Generative Adversarial Networks1
IIns-GAN1
Ultra-Wideband1
UWB1

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A arXiv cs.AI en 2026-09-07 12:00

针对无线传感领域位置相关标签数据获取成本高、传统环境模型合成方法泛化性差的问题，研究者提出了一种基于深度学习的 Inter-Instance Generative Adversarial Networks (IIns-GAN) 新方法以生成逼真的带标签无线信号。该方法生成的信号适应不同环境场景，适用于距离估计和环境识别等任务。在公共超宽带 (UWB) 数据集上的实验表明，IIns-GAN 生成的信号镜像了真实测量的物理特征，显著提升了多样化无线传感任务的模型训练效果。