Research On 5G Resource Scheduling For Industrial Applications With Low Latency And High Reliability

The rise of industrial Internet implies that industrial networks need stronger capabilities to carry a variety of industrial applications and provide them with efficient and reliable communication services.The characteristics of 5G,such as high data rate,low latency,high reliability,make it the most potential choice of industrial communication technology.the diversified data fusion transmission of Industrial application brought by its diversified business is the main challenge for 5G network to support industrial use cases,in which efficient wireless resource scheduling to ensure that all kinds of data coexist without interference and reliable transmission is the key problem to be solved.In order to solve the problem of multi-service convergence transmission based on 5G communication technology in industrial application scenarios,a low latency and high reliability radio resource scheduling scheme for industrial applications is researched.The research mainly includes two parts:the research on the fusion transmission scheme of different services in 5G uplink and downlink transmission in the data transmission scenario of industrial diversified services1)In the uplink transmission,in order to solve the problem of periodic traffic and emergency traffic fusion transmission in wireless network,a resource allocation scheme based on ARMA(Auto-Regressive Moving Average Model,ARMA)prediction is proposed.In this scheme,in the stationary situation,the periodic service transmission adopts the grant-free scheme to reduce the end-to-end delay;in the emergency situation,the ARMA model is used to predict the emergency data activation rate of the next transmission cycle,and according to the predicted activation rate,the resources are dynamically reserved for the periodic data and emergency data,so as to minimize the impact on periodic data transmission under the premise of meeting the emergency data transmission conditions.Simulation results show that compared with the traditional resource allocation scheme,the proposed scheme can effectively reduce the impact of emergency data transmission on periodic data,and improve the utilization of spectrum resources.2)In the downlink transmission,in order to solve the fusion transmission problem of eMBB traffic and uRLLC traffic,a puncturing scheduling scheme based on RBF(Radial Basis Function)neural network prediction is proposed.In this scheme,the proportional fairness algorithm is used to allocate transmission resources for eMBB users fisrtly,and then the RBF neural network is used to predict the decoding success rate of eMBB users after being punctured by uRLLC traffic,and the throughput loss is calculated.Finally,according to the throughput loss and the number of punches,the priority of punching is determined to formulate an efficient punching strategy,which aims to minimize the impact of uRLLC user perforation on the performance of eMBB users,ensure the fairness of eMBB user perforation,and avoid repeated perforation of users with low channel quality.Simulation results show that the scheme can guarantee the QoS of uRLLC users and reduce the impact on the performance of embB users,and ensure the fairness of eMBB users.