研究人员开发了一种识别长距离跳频扩频（LR-FHSS）卫星物联网上行链路中复合干扰的新方法。该方法将干扰识别视为一个多实例、多标签学习问题，融合了时频域和频域的数据以提高准确性。该方法在单到复合干扰场景和少样本适应方面表现出显著的泛化能力提升，解决了现有方法在可扩展性和泛化性方面存在的局限性。 AI
影响 通过改进干扰缓解技术，增强了卫星物联网通信的可靠性。
排序理由 该集群包含一篇详细介绍特定应用领域新技术的学术论文。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
arXiv:2607.11488v1 Announce Type: cross Abstract: Long range-frequency hopping spread spectrum (LR-FHSS) is a promising uplink physical layer for massive low Earth orbit satellite Internet of Things, where low power terminals report short packets from wide area regions with limit…
Long range-frequency hopping spread spectrum (LR-FHSS) is a promising uplink physical layer for massive low Earth orbit satellite Internet of Things, where low power terminals report short packets from wide area regions with limited terrestrial infrastructure. However, satellite …