Superimposed training-based channel estimation for Visible Light Communications

Visible Light Communications (VLC) is considered one of the most promising technologies to guarantee the future demand of user wireless data rate. Since a DC value is needed for illumination, Direct Current-biased Optical Orthogonal Frequency Division Multiplexing (DCO-OFDM) is adopted as modulation technique in these environments. Channel estimation in VLC is quite different from the conventional radiofrequency (RF) counterparts because the indoor optical wireless channel model significantly differs from the traditional RF one. Previous proposals rely on dedicated pilot symbols to perform channel estimation what leads to a loss in efficiency. In this paper, we propose a novel approach of Superimposed Training (ST) for channel estimation in VLC scenarios.