Currently, visible light positioning (VLP) enabling an illumination infrastructure requires a costly retrofit. Intensity modulation systems not only necessitate changes to the internal LED driving module, but decrease the LEDs’ radiant flux as well. This hinders the infrastructure’s ability to meet the maintained illuminance standards. Ideally, the LEDs could be left unmodulated, i.e., unmodulated VLP (uVLP). uVLP systems, inherently low-cost, exploit the characteristics of the light signals of opportunity (LSOOP) to infer a position. In this paper, it is shown that proper signal processing allows using the LED’s characteristic frequency (CF) as a discriminative feature in photodiode (PD)-based received signal strength (RSS) uVLP. This manuscript investigates and compares the aptitude of (future) RSS-based uVLP and VLP systems in terms of their feasibility, cost and accuracy. It demonstrates that CF-based uVLP exhibits an acceptable loss of accuracy compared to (regular) VLP. For point source-like LEDs, uVLP only worsens the trilateration-based median p50 and 90th percentile root-mean-square error p90 from 5.3cm to 7.9cm (+50%) and from 9.6cm to 15.6cm (+62%), in the 4m × 4m room under consideration. A large experimental validation shows that employing a robust model-based fingerprinting localisation procedure, instead of trilateration, further boosts uVLP’s p50 and p90 accuracy to 5.0cm and 10.6cm. When collating with VLP’s p50=3.5cm and p90=6.8cm, uVLP exhibits a comparable positioning performance at a significantly lower cost and at a higher maintained illuminance, all of which underline uVLP’s high adoption potential. With this work, a significant step is taken towards the development of an accurate and low-cost tracking system.

This letter presents an efficient algorithm for estimating the three-dimensional (3D) location of a photodiode (PD) receiver via visible light positioning. It solely works on measured powers from different light-emitting diode (LED) sources and does not require any prior knowledge of the PD receiver height. It is found that four LEDs are required that are not on the same circle, in order to unambiguously determine the 3D location. The algorithm is optimized towards a minimized calculation time in view of real-time operation on energy-constrained lightweight and mobile devices such as drones.

Visible Light Communication (VLC) is a short-range optical wireless communication technology that has been gaining attention due to its potential to offload heavy data traffic from the congested radio wireless spectrum. At the same time, wireless communications are becoming crucial to smart manufacturing within the scope of Industry 4.0. Industry 4.0 is a developing trend of high-speed data exchange in automation for manufacturing technologies and is referred to as the fourth industrial revolution. This trend requires fast, reliable, low-latency, and cost-effective data transmissions with fast synchronizations to ensure smooth operations for various processes. VLC is capable of providing reliable, low-latency, and secure connections that do not penetrate walls and is immune to electromagnetic interference. As such, this paper aims to show the potential of VLC for industrial wireless applications by examining the latest research work in VLC systems. This work also highlights and classifies challenges that might arise with the applicability of VLC and visible light positioning (VLP) systems in these settings. Given the previous work performed in these areas, and the major ongoing experimental projects looking into the use of VLC systems for industrial applications, the use of VLC and VLP systems for industrial applications shows promising potential.

This work was executed within LEDsTrack, a research project bringing together academic researchers and industry partners. The LEDsTrack project was co-financed by imec (iMinds) and received project support from Flanders Innovation & Entrepreneurship.

Optical Wireless Communication (OWC) is being explored for application in the next-generation broadcasting networks, where possessing accurately determined user locations becomes increasingly important. Received signal strength (RSS) Visible Light Positioning (VLP)-based localisation systems aim to deliver these centimetre-level location data at a low cost by featuring but a single photodiode (PD). Maximising the VLP accuracy requires optimising the LED transmitter locations, which is missing currently. An evolutionary optimisation algorithm is proposed to determine the optimal LED locations and the associated positioning error values for various configurations. The sensitivity of the planning on the number of VLP-enabled LEDs, the LEDs' characteristics, the room dimensions and the positioning parameters is investigated. Experimental data, i.e. two datasets with 157 2 measurement points each, serve to validate the simulations.

This paper presents a study of the performance of eight different cost metrics for RSS-based visible light positioning (VLP) under the presence of reflections. A channel model with first-order wall reflections is implemented, after which the distribution of the median (p 50 ) and maximal errors (p 95 ) in a typical room configuration are presented and compared for the different metrics. From the simulations, it appears that metrics yielding the lowest median errors correspond to the largest maximal errors, and vice versa. For the 5 m x 5 m room configuration, median errors range between 6.7 cm and 8.7 cm, and maximal errors between 11.6 and 25.4 cm. Further, a nearly linear increase in positioning error is observed when the wall reflectance coefficient is increased.

This paper presents a simulation study of the impact of Light Emitting Diode (LED) output power uncertainty on the accuracy of Received Signal Strength (RSS)-based two-dimensional (2D) and three-dimensional (3D) Visible Light Positioning (VLP). The actual emitted power of a LED is never exactly equal to the value that is tabulated in the datasheet, with possible variations (or tolerances) up to 20%. Since RSS-based VLP builds on converting estimated channel attenuations to distances and locations, this uncertainty will impact VLP accuracy in real-life setups. For 2D, a typical configuration with four LEDs is assumed here, and a Monte-Carlo simulation is executed to investigate the distribution of the resulting positioning errors for four tolerance values at seven locations. It is shown that median errors are the highest just below the LEDs, when using a traditional Least-Squares minimization metric. When tolerance values on the LED power increase from 5% to 20%, median errors vary from at most 2 cm to at most 10 cm. Maximal errors can be as high as 17 cm just below the LED, already for tolerance values of only 5%, and increase up to 40 cm for tolerance values of 20%. An alternative cost metric using normalized Least-Squares minimization makes the errors spatially more homogeneously distributed and reduces them by 35%. For a 3D case, median errors of around 5 cm for a tolerance value of 5% increase to as much as 22 cm for a tolerance value of 20%. As the receiver heights increase, positioning errors decrease significantly.

Whereas the impact of photodiode noise and reflections is heavily studied in Visible Light Positioning (VLP), an often underestimated deterioration of VLP accuracy is caused by tilt of the Light Emitting Diodes (LEDs). Small LED tilts may be hard to avoid and can have a significant impact on the claimed centimeter-accuracy of VLP systems. This paper presents a Monte-Carlo-based simulation study of the impact of LED tilt on the accuracy of Received Signal Strength (RSS)-based VLP for different localization approaches. Results show that trilateration performs worse than (normalized) Least Squares algorithms, but mainly outside the LED square. Moreover, depending on inter-LED distance and LED height, median tilt-induced errors are in the range between 1 and 6 cm for small LED tilts, with errors scaling linearly with the LED tilt severity. Two methods are proposed to estimate and correct for LED tilts and their performance is compared.