Strong Noise Rejection in VLC Links under Realistic Conditions through a Real-Time SDR Front-End

Sensors (Basel). 2023 Feb 1;23(3):1594. doi: 10.3390/s23031594.

Abstract

One of the main challenges in the deployment of visible light communication (VLC) in realistic application fields, such as intelligent transportation systems (ITSs), is represented by the presence of large background noise levels on top of the optical signal carrying the digital information. A versatile and effective digital filtering technique is, hence, crucial to face such an issue in an effective way. In this paper, we present an extensive experimental evaluation of a complete VLC system, embedding a software-defined-radio (SDR)-based digital signal processing (DSP) filter stage, which is tested either indoors, in the presence of strong artificial 100-Hz stray illumination, and outdoors, under direct sunlight. The system employs low-power automotive LED lamps, and it is tested for baud rates up to 1 Mbaud. We experimentally demonstrate that the use of the DSP technique improves 10× the performance of the VLC receiver over the original system without the filtering stage, reporting a very effective rejection of both 100-Hz and solar noise background. Indoors, the noise margin in the presence of strong 100-Hz noise is increased by up to 40 dB, whilst in the outdoor configuration, the system is capable of maintaining error-free communication in direct sunlight conditions, up to 7.5 m, improving the distance by a factor of 1.6 compared to the case without filtering. We believe that the proposed system is a very effective solution for the suppression of various types of noise effects in a large set of VLC applications.

Keywords: Li-Fi; intelligent transportation systems; software-defined radios; visible light communication (VLC); wireless communication.

Grants and funding

This study received financial support through the following projects: MiUR PON 2017 ARS01_00917 “OK-INSAID”, CNR Progetti@CNR “FluoCom”, MiSE Centri di Competenza “ARTES4.0”, MiUR FOE Progetto Premiale 2015 “OpenLab 2”, and MiSE PRato Industrial SMart Accelerator “PRISMA”.