Software-defined implementation of a VLC-based positioning system

Abstract

This MSc Thesis presents the design, analysis and proof-of-concept implementation of a Visible Light Communication (VLC)-based positioning systems that uses Software-Defined Radios (SDRs) to take advantages of the unique properties of optical wireless channels in indoor environments. This indoor positioning system uses Orthogonal Frequency Division Multiplexing (OFDM) modulation in an indoor controlled environment to provide jointly wireless data connectivity and determine the exact position of a Photodetector (PD)-enabled VLC receiver. The proof-of-concept demonstration that was implemented uses on purpose blue and white Light-Emitting-Diodes (LEDs) as transmitters and a PD as the receiver, emphasizing the influence of the electrical frequency response of the LEDs on the measurements of Channel State Information (CSI). The experiment also demonstrates that the larger modulation bandwidth of the blue LEDs gives cleaner and more accurate CSI estimation for the different subcarriers when compared to white LEDs; the reason for this is the low-pass response of the white LED resulting from the slow time response of the phosphor layer. A distributed Multiple-Input Single-Output (MISO) configuration is also implemented to ensure robustness relying on spatial diversity to grant accurate positioning estimation under challenging ultra-densification conditions. The software-defined proof-of-concept implemented as part of this MSc Thesis integrates GNU Radio and Universal Software Radio Peripheral (USRP) hardware into one scalable and flexible platform for generating, transmitting, receiving, reconstructing and analyzing OFDM-modulated signals. The obtained results highlight the feasibility of VLC-based indoor positioning systems and their application in smart environments with potentially high accuracy.

The obtained experimental results have the potential to pave the way for 2D/3D indoor positioning and its integration with joint communication and sensing into the 6G landscape, thereby making it a very promising alternative for accurate indoor positioning in a secure way.