Edge-Driven Active Anti-Interference Strategy for PLC in Intelligent Warehousing Systems

With the development of intelligent warehouse systems towards automation and intelligence, PLC technology is facing severe challenges due to pulse interference, channel complexity, and real-time requirements in densely packed environments. Different from the passive interference suppression of traditional PLCs, this scheme realizes cross-layer active prediction and real-time compensation through edge nodes, and realizes active interference prediction and real-time compensation through a cross-layer optimization framework integrating spatiotemporal dynamic interference modeling, compressed sensing dimensionality reduction and LSTM prediction. Experimental results show that compared with the traditional OFDM and hierarchical optimization schemes, the proposed method reduces the BER and significantly improves the SNR, which effectively improves the communication reliability and operational efficiency of the intelligent warehouse system. This research provides a new antijamming paradigm of “perception-prediction-execution” for IIoT scenarios