摘要
在工业网络系统中,控制中心经由无线网络收集现场设备的感知信息并执行状态估计以推测设备运行状态。然而,有限的频谱、能量资源和恶劣的工业无线电环境导致感知信息难以在规定的期限内到达控制中心,进而致使状态估计的性能显著恶化。针对上述问题,提出了能量感知的传感器调度和机会传输方案,以提升资源利用率和状态估计精度,并构建了频谱和能量资源约束的总成本最小化问题,以实现估计性能和资源消耗的有效折衷。为高效求解此混合整数非线性规划问题,设计了基于估计误差比率的传感器调度策略,并采用子问题迭代求解的方式以较低的复杂度获得原问题的近似最优解。仿真结果验证了所提方案在降低估计误差和能耗方面的优越性。
In industrial network systems,the control center collects sensory information from field devices via wireless networks and performs state estimation to conjecture the operating status of the device.However,limited spectrum,energy resources,and harsh industrial wireless environments make it difficult for sensory information to reach the control center within the prescribed deadline,resulting in a significant deterioration in the performance of state estimation.To address this issue,an energy-aware sensor scheduling and opportunistic transmission scheme is proposed to improve the resource utilization and state estimation accuracy,and an overall cost minimization problem with spectrum and energy resource constraints is formulated to achieve an effective trade-off between estimation performance and resource consumption.To efficiently solve this mixed-integer nonlinear programming problem,an estimation error ratio-based sensor scheduling strategy is designed,and an iterative method of subproblems is adopted to obtain the approximate optimal solution of the original problem with lower complexity.Simulation results verify the superiority of the proposed scheme in reducing the estimation error and energy consumption.
作者
乔泽鑫
吕玲
戴燕鹏
QIAO Zexin;LV Ling;DAI Yanpeng(School of Information Science and Technology,Dalian Maritime University,Dalian 116026,China)
出处
《移动通信》
2023年第8期16-21,共6页
Mobile Communications
基金
国家自然科学基金项目“面向工业网络系统感知与控制的边缘协作传输机制”,“立体密集网络连续覆盖的非正交多址协同接入方法”(62002042,62101089)
中国博士后科学基金项目“工业网络系统边缘协作传输与协调控制的联合优化”,“立体密集无线网络连续覆盖的空地多点协作方法”(2021M690022,2021M700655)。
关键词
工业网络系统
状态估计
传感器调度
机会式传输
Industrial network systems
state estimation
sensor scheduling
opportunistic transmission
