Research on Efficient Channel Decoding Algorithm for Memory Channel and Short Packet Transmission in Smart Grid

Many smart factories use the grid for power system automation, and its wireless control technology requires low-time-delay high-reliability communication. Guessing random additive noise decoding algorithm has outstanding short packet error correction performance. In process, order of parameter combination affects delay. Aiming at communication problem in process factory supply distribution, this study analyzes characteristics original ranking algorithm. When steady-state flip probability is large, more search times are required to obtain correct parameters, which means that greater delay time-varying channel. To solve aforementioned problems, optimizes before mode arrangement proposes a predicting symbol string. First, channel perception completed by edge computing. Then, uses obtained soft information rank parameters. Simulation results show proposed better performance than sorting algorithm, especially when b 0.5. Finally, comparing BM Decoding Algorithm BCH with different algorithms decoding, environmental factory, so as improve reliability distribution.