面向工业物联网的基于语义推拉的目标导向通信与控制协同设计
Goal-Oriented Communication and Control Co-Design via Semantic Push-Pull in Industrial IoT
浏览论文内容
中文总结 AI 辅助
针对6G工业物联网，提出基于语义推拉的通信-控制协同设计框架，利用状态误差比和信噪比协调资源，在降低通信开销的同时保持控制精度。
中文摘要 AI 辅助
新兴的6G工业物联网架构需要无线网络控制系统，能够在严格受限的无线电资源上稳定各种控制回路。传统的周期性调度和基于信息年龄（AoI）的调度以持续的信道饱和为代价来保证有界的信息陈旧性。相反，纯事件触发（PureET）策略最小化传输次数，但当本地传感器侧阈值无法反映关键状态演变时，可能导致灾难性的静默恶化。为弥合这一差距，我们提出了一种由6G语义层管理的通信-控制协同设计框架，该语义层独立仲裁上行和下行资源。我们的架构不依赖信息新鲜度，而是使用状态误差比（SER）评估数据包的实际控制影响。我们将这种控制置信度与信道可靠性（以信噪比（SNR）表示）统一起来，以协调基于阈值的传感器推送和状态感知的控制器拉取机制。为确保在动态异构工厂之间公平分配资源，所提出的框架根据本地工厂动态显式调整执行器死区。在瑞利衰落信道上的仿真表明，该方法从根本上改变了传输速率与控制质量之间的帕累托前沿。所提出的方案在降低通信开销的同时实现了与周期性调度器相当的跟踪精度，同时减轻了PureET特有的估计误差。
英文摘要
Emerging 6G industrial IoT architectures require wireless networked control systems capable of stabilizing diverse control loops over tightly constrained radio resources. Conventional periodic and Age-of-Information (AoI) based scheduling guarantees bounded staleness at the cost of persistent channel saturation. Conversely, pure event-triggered (PureET) strategies minimize transmissions but risk catastrophic silent deterioration when local sensor-side thresholds fail to reflect critical state evolution. To bridge this gap, we propose a communication-control co-design framework governed by a 6G Semantic Layer that independently arbitrates uplink and downlink resources. Instead of relying on freshness, our architecture evaluates the actual control impact of a packet using the state-to-error ratio (SER). We unify this control confidence with channel reliability in terms of signal-to-noise ratio (SNR) to orchestrate a threshold-based sensor push and a state-aware controller pull mechanism. To ensure equitable resource allocation across dynamically heterogeneous plants, the proposed framework explicitly scales actuation deadbands according to local plant dynamics. Simulations over Rayleigh-faded channels demonstrate that this approach fundamentally shifts the Pareto frontier between transmission rate and control quality. The proposed scheme achieves tracking accuracy comparable to periodic schedulers at a reduced communication overhead, while mitigating the estimation errors characteristic of PureET.
发表机构
- Mid Sweden University（瑞典中部大学）
- University of L’Aquila（拉奎拉大学）
机构由 AI 辅助整理，请以论文原文为准。
