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In industrial automation, the state of process control could be monitored by spatially distributed sensors and 5G machine-type communication (MTC) enabled industrial Internet of things (IIoT). Thus, ultra-reliable MTC and high-accurate state estimation play important roles for ensuing system stabilization. However, it is challenging due to complex industrial wireless environments and limited communication resources. To address this issue, this paper first presents a transmission-estimation codesign framework to lay down the foundation for guaranteeing the prescribed estimation accuracy with limited communication resources. Under this framework, a hierarchical transmission-estimation approach is proposed to improve the transmission reliability and estimation accuracy according to system dynamics. The proposed approach is then optimized by formulating a constrained minimization problem, which is mixed integer nonlinear programming and solved efficiently with a block-coordinate-descent-based decomposition method. Finally, simulation results demonstrate that the proposed approach has superiorities in improving both the estimation accuracy and the energy efficiency.
Lyu et al. (Tue,) studied this question.
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