A Relay Optimization Method for NOMA-Based Power Line Communication Systems - Lenian Zhang; Yuntao Yue; Peng Li; Dong Liu; Haoran Ren (Applied Sciences)
Power line communication (PLC) technology is investigated in this research. A PLC system model combining Orthogonal Frequency Division Multiplexing (OFDM) and Non-Orthogonal Multiple Access (NOMA) technologies is proposed to enhance spectral efficiency, extend transmission distance, and improve signal quality. We construct detailed models for the system, signal, and noise. Future Channel State Information (CSI) is predicted using a Long Short-Term Memory (LSTM) network, and an improved simulated annealing algorithm is employed to optimize power allocation and relay positioning in the system. Experiments validate the effectiveness of the LSTM model in predicting CSI data in a NOMA communication system, demonstrating generally good performance despite some prediction errors. Simulation results show that this approach significantly enhances system performance, reduces power consumption, and meets constraints on system capacity, bit error rate (BER), and signal-to-interference-plus-noise ratio (SINR) in complex PLC environments. Future research should focus on optimizing model parameters, expanding datasets, exploring alternative optimization algorithms, and testing the model in real-world scenarios to improve generalizability and practicality. In conclusion, the proposed multi-user PLC system provides an effective technical solution for future smart grid and Internet of Things (IoT) applications.