Research On NOMA Based Sensory Data Transmission Scheme In Industrial Network Systems

With the continuous development of information and communication technology,wireless networks have been widely used in intelligent manufacturing and integrated with industrial control systems to form industrial network systems.Usually,a large number of devices with sensing capability are deployed on site,and the collected sensing information is transmitted to the remote control center through a wireless network,and the remote control estimates the system state based on the sensing information,thereby realizing networked industrial monitoring.However,limited spectrum resources are difficult to meet the data transmission requirements of a large number of sensing devices in industrial sites.In order to solve this problem,this thesis adopts non-orthogonal multiple access technology to improve wireless network access capability and network capacity by using power domain multiplexing.Considering the differences in the perception capabilities of different devices,this thesis introduces the concept of data value to describe the effectiveness of the successful transmission of different perception information for the performance improvement of state estimation.This thesis aims to study the NOMA-based sensory data transmission mechanism,design an efficient resource allocation algorithm based on data value,alleviate the restriction of limited spectrum resources on the improvement of transmission performance,and provide satisfactory information transmission services for industrial network system state estimation.The main results of this thesis include:In the single-channel environment,this thesis studies the NOMA transmission scheme for state estimation in the single-channel environment of industrial wireless networks,which realizes the on-demand transmission of state-aware information under power and rate constraints,thereby ensuring accurate state estimation of industrial network systems under resource constraints.The intrinsic relationship between the probability of perceptual information loss and the accuracy of state estimation is firstly expressed analytically,and the problem of minimizing the mean square error of estimation under the constraints of transmission power and rate is constructed.Since the constructed constrained optimization problem is a mixed integer programming problem,a low-complexity priority-based NOMA ondemand transmission algorithm is designed.The algorithm defines the improvement of the estimation accuracy from the successful transmission of sensing information as a priority indicator variable,and schedules sensing devices and optimizes transmission parameters according to this variable.The simulation results show that the priority-based NOMA transmission scheme not only has low computational complexity,but also can perform adaptive on-demand transmission according to the need urgency of sensing information according to state estimation.In the multi-channel environment,based on the intrinsic relationship between the probability of perceptual information loss and the accuracy of state estimation,the problem of minimizing the mean square error of estimation is constructed.Firstly,an area division algorithm is designed to determine the set of sensing devices associated with the edge estimator.Secondly,a power allocation algorithm is designed so that the sensing devices participating in transmitting data meet the successive interference cancellation conditions in the power domain NOMA.Then,a channel allocation algorithm based on the marine predators algorithm is designed to allocate appropriate channels for sensing devices participating in data transmission,and on this basis,NOMA user groups are determined.Thirdly,a sensing device scheduling algorithm is designed to realize the on-demand transmission of sensing devices at any time.The simulation results show that the area division algorithm can associate the sensing device with the edge estimator with better channel conditions,and improving the performance of sensing information transmission.Furthermore,the simulation results verify the convergence of the power control algorithm and the channel allocation algorithm.Compared with the random channel allocation algorithm,the channel allocation algorithm proposed in this thesis can significantly improve the system throughput.Finally,compared with the random scheduling scheme,the sensor scheduling algorithm performs reasonable scheduling according to the urgency of device data transmission requirements,so as to realize the on-demand transmission of sensing information.