用多智能体架构让5G/6G基站实时感知环境障碍并自动调整信号。
CONVERGE: A Multi-Agent Vision-Radio Architecture for xApps
- 设计多智能体系统，融合视觉与无线信号数据。
- 感知延迟低于1毫秒，支持实时控制基站。
- 适合做智能通信与感知一体化的工程师或研究者。
通信与计算机视觉长期独立发展。随着高频无线链路主要采用视距传输，视觉数据可帮助预测信道变化，通过波束成形或切换技术克服障碍。本文提出一种新型多智能体架构，将实时无线电与视频感知信息输送至O-RAN xApps，引入新视频功能以生成遮挡信息，实现感知与通信的融合。实验表明，感知信息延迟保持在1毫秒以下，xApp可成功利用无线与视频感知信息实时调控5G/6G RAN。
原文摘要 · Abstract (English)
Telecommunications and computer vision have evolved independently. With the emergence of high-frequency wireless links operating mostly in line-of-sight, visual data can help predict the channel dynamics by detecting obstacles and help overcoming them through beamforming or handover techniques. This paper proposes a novel architecture for delivering real-time radio and video sensing information to O-RAN xApps through a multi-agent approach, and introduces a new video function capable of generating blockage information for xApps, enabling Integrated Sensing and Communications. Experimental results show that the delay of sensing information remains under 1\,ms and that an xApp can successfully use radio and video sensing information to control the 5G/6G RAN in real-time.
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