Adaptive Sparse Dictionary-Based Kernel Minimum Symbol Error Rate Post-Distortion for Nonlinear LEDs in Visible Light Communications

Visible light communications (VLC) has emerged as one of the prominent technologies to cater to the ever-increasing high-speed-data demand for proposed fifth-generation (5G) systems. However, two main issues affect the performance of VLC in an indoor environment: a) nonlinearity of light-emitting diode, which renders the overall system nonlinear; and b) intersymbol interference due to the propagation channel, which closes the eye diagram of the transmit constellation and, hence, causes it to be unsuitable for detection. To counter these artifacts, complex post-distortion receivers such as the Volterra-decision feedback equalizer (DFE) have been proposed to recover the transmit symbols. In this paper, the use of a reproducing kernel Hilbert space-based minimum symbol error rate equalizer is proposed that provides performance comparable to a long Volterra-DFE, with much less computational cost. Simulations have been carried over IEEE 802.15 personal area network (PAN) channels, which suggest that the proposed approach gives equivalent performance in an indoor VLC channel, as compared with Volterra-DFE with far fewer computations. An analytical expression for mean square error dynamics over these channels is also derived, and it is observed that the theoretically derived expression matches the simulation results for the considered IEEE 802.15 PAN indoor VLC channels.