Abstract
Abstract 5G mobile fronthaul (MFH) network requires data transmission with large bandwidth and ultra-low latency. Orthogonal frequency division multiplexing/offset quadrature amplitude modulation (OFDM/OQAM) passive optical network (PON) system is the 5G MFH solution with low spectrum efficiency and large bandwidth. The OFDM/OQAM-PON transmission performance will be undermined by intrinsic imaginary interference (IMI) induced by chromatic dispersion (CD) and polarization mode dispersion (PMD). In this paper, we proposed an artificial neural network (ANN) based channel estimation (CE) algorithm, which can effectively reduce IMI by estimation of channel transfer function (TF). Simulation results show that the proposed algorithm can optimize the system performance, compared with the conventional LS method, the proposed algorithm can improve bit error rate optimization capability by an order of magnitude.
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