Industrial impulse noise in mining and other scenes can lead to burst data errors in wireless communication systems, significantly reducing data transmission reliability and communication quality. Most of the existing anti-impulse noise studies can only guarantee the effectiveness or reliability of communication systems. However, the task applications in industrial wireless communication scenes put forward high requirements on both effectiveness and reliability, and a single performance study cannot meet the needs. In order to solve the above problems, comprehensively considering the size of industrial equipment and design complexity, a multi-user multiple-input single-output (MU-MISO) orthogonal frequency division multiplexing (OFDM) system model combining receiver and transmitter design is established. At the transmitter, a precoding algorithm based on quadratic conversion is designed to maximize the system sum-rate. The quadratic type is used to decouple the coupled precoding vector to reduce computational complexity. At the receiver, a deep reduction impulse noise elimination scheme is designed to reduce the bit error rate and improve the reliability of industrial wireless communication. The simulation results show that under the Middleton Class A (MCA) noise model, the system and rate of the quadratic conversion-based precoding algorithm and the semi-definite relaxation (SDR) algorithm are very similar, verifying the effectiveness of the proposed precoding algorithm. Compared with the mainstream three nonlinear impulse noise elimination schemes of blanking, reduction and mixing, the deep reduction impulse noise elimination scheme has the highest output signal-to-noise ratio and the lowest bit error rate. The bit error rate is 24%, which is lower than that of the mainstream best scheme. The model has the optimal performance.
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