English

Unmodulated Visible Light Positioning: A Deep Dive into Techniques, Studies, and Future Prospects

Signal Processing 2025-11-05 v1

Abstract

Visible Light Positioning (VLP) has emerged as a promising technology for next-generation indoor positioning systems (IPS), particularly within the scope of sixth-generation (6G) wireless networks. Its attractiveness stems from leveraging existing lighting infrastructures equipped with light-emitting diodes (LEDs), enabling cost-efficient deployments and achieving high-precision positioning accuracy in the centimeter-todecimeter range. However, widespread adoption of traditional VLP solutions faces significant barriers due to the increased costs and operational complexity associated with modulating LEDs, which consequently reduces illumination efficiency by lowering their radiant flux. To address these limitations, recent research has introduced the concept of unmodulated Visible Light Positioning (uVLP), which exploits Light Signals of Opportunity (LSOOP) emitted by unmodulated illumination sources such as conventional LEDs. This paradigm offers a cost-effective, lowinfrastructure alternative for indoor positioning by eliminating the need for modulation hardware and maintaining lighting efficiency. This paper delineates the fundamental principles of uVLP, provides a comparative analysis of uVLP versus conventional VLP methods, and classifies existing uVLP techniques according to receiver technologies into intensity-based methods (e.g., photodiodes, solar cells, etc.) and imaging-based methods. Additionally, we propose a comprehensive taxonomy categorizing techniques into demultiplexed and undemultiplexed approaches. Within this structured framework, we critically review current advancements in uVLP, discuss prevailing challenges, and outline promising research directions essential for developing robust, scalable, and widely deployable uVLP solutions.

Keywords

Cite

@article{arxiv.2507.13080,
  title  = {Unmodulated Visible Light Positioning: A Deep Dive into Techniques, Studies, and Future Prospects},
  author = {Morteza Alijani and Wout Joseph and David Plets},
  journal= {arXiv preprint arXiv:2507.13080},
  year   = {2025}
}

Comments

This work has been submitted to the IEEE for possible publication

R2 v1 2026-07-01T04:06:00.168Z