A Novel VL-Based Positioning Model for Obstacle Location Sensing and 3-D Shape Detection in Crowded Indoor Networks

The emergence of new communication systems, such as 5G and 6G, has led to increasing demand for various indoor communication and sensing services. However, effectively implementing indoor communication and sensing systems in crowded environments poses new design challenges, particularly in terms of obstacle localization (sensing) and identification. Visible light (VL) communication has emerged as a promising paradigm for utilizing VL in other indoor applications and services, such as obstacle sensing. In this letter, a novel VL-based positioning system is developed to provide accurate indoor localization of obstacles and sense their 3-D shapes in crowded indoor networks, such as shopping malls, warehouses, and industrial facilities. Specifically, the proposed model aims to estimate the 3-D parameters of an obstacle, including its stature and radius, along with its position in the existence of multiple obstacles. Furthermore, our model considers the profiling impacts on communication and localization to ensure its applicability in environments with multiple obstacles. Results illustrate that the presented VL positioning model accomplishes a cm-level position precision, which may be further improved at the cost of additional equipment. Moreover, the VL-based positioning system illustrates a precision of the order of 5 cm for localization and 12 cm in measuring the 3-D shape of obstacles in a given indoor network.