Low spatial complexity adaptive artificial neural network post-equalization algorithms in MIMO visible light communication systems

Abstract

In this paper, we experimentally propose a feasible and low spatial complexity adaptive artificial neural network (AANN) post-equalization algorithm in MIMO visible light communication (VLC) systems. By introducing the power ratio and the MIMO least mean square (MIMO-LMS) post-equalization algorithm into the structure design process of the artificial neural network (ANN) post-equalization algorithm, we reduced the spatial complexity of the post-ANN equalization algorithm to less than 10%. At the same time, the bit error rate (BER) performance of AANNs did not decrease. Finally, we achieved a data rate of 2.1Gbps in the AANN equalized 16QAM superposition coding modulation (SCM) and carrier-less amplitude-phase (CAP) single-receiver MIMO (SR-MIMO) VLC system.