AI 中文总结
该研究提出一种将频谱异常检测与动态频谱管理集成的自愈式6G网络中网络架构，可实现网络自主适配以提升无线通信弹性，并通过现场演示验证了该方法的可行性。
AI 中文摘要
未来6G网络必须管理日益动态的无线电环境，在该环境中多个自治子网（SN）共享频率资源并适应不断变化的运行条件。在此类场景中，来自故障设备或有意干扰的干扰可能会中断正在进行的通信，因此快速且自主的网络适配至关重要。本演示提出了一种自愈式网络中网络（NiN）架构，该架构将频谱异常检测与动态频谱管理（DSM）紧密集成。频谱扫描器持续监测频谱，并将检测到的异常转发至DSM，DSM会自动识别合适的频率资源并重新配置受影响的SN。在现场演示中，参与者可发起受控中断，实时观察从异常检测到自主频率重分配及网络恢复的整个适配过程。该演示表明，将频谱监测与资源管理集成到单个控制回路中可提升未来NiN实现的弹性，并展示了一种自主、感知频谱的组网实用方法。
英文摘要
Future 6G networks must manage increasingly dynamic radio environments in which multiple autonomous sub-networks (SNs) share frequency resources and adapt to changing operating conditions. In such scenarios, interference from faulty devices or intentional jamming can disrupt ongoing communications, making rapid and autonomous network adaptation essential. This demonstration presents a self-healing networks-in-network (NiN) architecture that closely integrates the detection of spectrum anomalies with dynamic spectrum management. A spectrum scanner continuously monitors the frequency spectrum and forwards detected anomalies to the DSM, which automatically identifies suitable frequency resources and reconfigures the affected SN. During the live demonstration, participants can initiate controlled disruptions and observe the entire adaptation process in real time, from anomaly detection to autonomous frequency reallocation and network recovery. The demonstrator illustrates how integrating spectrum monitoring and resource management into a single control loop can improve the resilience of future NiN implementations and demonstrates a practical approach to autonomous, spectrum-aware networking.
Comments6 pages, 2 figures, demo paper
