The Network Optimization Algorithm of PLC Module Automatic Detection Pipeline

With the increase in the number of terminals and services on the PLC module automated detection pipeline, traditional wireless networks will face problems such as network redeployment and resource optimization. In this paper, the 5G network architecture of automatic detection pipeline for communication modules is first constructed, and the hybrid slicing resource allocation model of eMBB and URLLC in key detection units is established. The kernel-based reinforcement learning algorithm(KBRL) is used to realize the optimal allocation of slicing resources. Simulation results show that, compared with other algorithms, the proposed algorithm can effectively improve the slice resource utilization and provide 5G private network performance guarantee for the automated detection pipeline.