Channel Estimation Algorithm for IM/DD-OFDM/OQAM-PON System in Industrial Internet Based on Compressed Sensing

Abstract

High-quality and low-latency communication in the three major application scenarios of 5G mobile communication technology is a guide for future technological development. The Industrial Internet needs to deal with the data transmission tasks of large-traffic mobile bandwidth and ultra-low latency. Orthogonal Frequency Division Multiplexing/Offset Quadrature Amplitude Modulation (OFDM/OQAM) passive optical network (PON) systems are affected by inherent imaginary interference (IMI), part of which is generated by the chromatic dispersion (CD) of optical fiber systems. Another part is produced by polarization mode dispersion (PMD). This paper proposes a channel estimation (CE) algorithm based on compressed sensing (CS), where the signal exhibits sparsity through sparse representation, and the signal reconstruction algorithm of compressed sensing adopts the orthogonal matching pursuit algorithm (OMP). The channel transfer function (TF) can effectively reduce the IMI and make the signal accuracy of the receiving end higher. Simulation results show that CS-CE algorithm can improve the system performance, which is better than the traditional LS method. Compared to existing LS methods, the CS algorithm can accomplish a 20% improvement. The algorithm can reduce the bit error rate of the system and improve the reliability of the system.