Adaptive Precoding-Based Detection Algorithm for Massive MIMO Visible Light Communication

Abstract

Visible light communication (VLC) has emerged as a promising, green, and interference-free supplement to existing radio frequency-based communication systems. To enhance the capacity of existing VLC-based systems, using massive arrays of light emitting diodes (LEDs) at the transmitter and photodiodes at the receiver has been proposed recently, resulting in a massive multiple-input multiple-output (m-MIMO) VLC system. However, by increasing LED array pitch in m-MIMO, the VLC channel matrices are generally ill conditioned which makes them sensitive to small perturbations and degrades the overall bit error rate (BER) performance. To reduce the condition number of the overall channel matrix, a novel precoder using an exponent-based singular value decomposition is proposed for m-MIMO VLC system. Furthermore, a joint optimization problem is formulated to optimize the exponent and to detect symbols iteratively using the minimum symbol error rate criterion. Simulations show that the proposed adaptive precoding technique exhibits superior BER performance over existing techniques. Analytical upper bounds for BER are also derived and validated by simulations.