⚡ electrical engineering

Adaptive Lighting Control in Visible Light Systems: An Integrated Sensing, Communication, and Illumination Framework

This paper proposes an adaptive integrated sensing, communication, and illumination (ISCI) framework for visible light systems that dynamically optimizes energy efficiency and signal uniformity by partitioning the receiving plane into activity and non-activity areas based on user location, achieving significant energy savings and improved performance without compromising visual comfort or localization accuracy.

Original authors: Xinyan Xie, Xuesong Wang, Xin Lai, Yongheng Wen, Fengrui Yang, Haoyang He, Lai Zhang, Dong Zhao

Published 2026-07-29

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CC BY 4.0

Original authors: Xinyan Xie, Xuesong Wang, Xin Lai, Yongheng Wen, Fengrui Yang, Haoyang He, Lai Zhang, Dong Zhao

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine your room is a giant, invisible web of light. In the world of future technology, this isn't just for seeing; it's for talking and feeling. This field is called Visible Light Communication (VLC), where the humble LED bulb becomes a super-fast Wi-Fi router, beaming data through the air using light instead of radio waves. Because light travels in straight lines and reacts instantly to anything it hits, these beams can also act like super-sensitive eyes, sensing where you are without needing a camera. This combination of talking, seeing, and lighting up a room is known as Integrated Sensing, Communication, and Illumination (ISCI). But here's the catch: to make these light-beams talk fast and see clearly, you usually have to crank the power up to maximum. That's like leaving a stadium floodlight on full blast just because someone is walking through the lobby. It wastes a ton of electricity and can be blindingly bright for your eyes. The big question scientists are asking is: Can we make this smart light system that knows exactly how much power to use, saving energy and keeping things comfortable, without losing its superpowers?

This paper proposes a clever solution called an "Adaptive ISCI Framework," which acts like a smart, mood-sensing light switch for the whole room. The researchers realized that not every part of a room needs the same level of attention. They split the floor into two zones: a "busy zone" (the activity area) where people are working or focusing, and a "chill zone" (the non-activity area) where people are just walking through. Think of it like a stage: the actors on stage get the bright, focused spotlights, while the audience in the aisles just gets enough light to see their way without being dazzled.

The system uses a special trick to know where you are. Instead of using cameras, it watches how the light bounces off your body and hits sensors on the ceiling. It's like a game of "hot and cold" played with light; by measuring tiny changes in the reflected light, the system can pinpoint your location with an average error of just 0.071 meters. Once it knows where you are, it instantly switches its strategy. If you are in the "chill zone," the system doesn't try to blast you with high-speed data; instead, it smooths out the light so the signal is even and steady everywhere, ensuring you don't lose connection as you walk. If you step into the "busy zone," the system cranks up the performance, guaranteeing super-fast data and bright, clear light exactly where you need it, while dimming everything else to save power.

The results from the computer simulations are quite impressive. By using this smart, adaptive approach, the system saved 53.59% of the energy compared to a traditional system that just keeps all the lights on at a fixed, high level. It also made the signal quality 57.79% more uniform across the room, meaning fewer dead spots and less flickering. Crucially, the system managed to do all this while keeping the room bright enough for work and maintaining that tiny 0.071-meter average error in tracking your location. The paper suggests that by treating energy savings as a primary goal alongside performance, we can have a lighting system that is not only fast and smart but also kind to the environment and your eyes.

Technical Summary: Adaptive Lighting Control in Visible Light Systems

Problem Statement
Indoor Visible Light Communication (VLC) is a promising candidate for sixth-generation (6G) networks, offering high data rates and natural suitability for Integrated Sensing and Communication (ISAC) due to the directional nature of optical signals. However, current research predominantly prioritizes maximizing data rates and sensing accuracy. This focus creates a conflict between high system performance, excessive energy consumption, and user visual comfort. Specifically, maintaining high performance often requires high transmit power, leading to unnecessary energy waste when users are not engaged in focused tasks and causing visual discomfort through excessive illumination. Existing studies largely overlook the trade-off between performance and energy efficiency, particularly in dynamic indoor environments where user requirements vary by location and activity.

Methodology
The paper proposes an Adaptive Integrated Sensing, Communication, and Illumination (ISCI) framework designed to resolve this conflict by treating energy savings as a primary system objective. The methodology relies on three core components:

Geometric Space Partitioning: The receiving plane is partitioned using a geometric methodology to match distinct user requirements.
- Activity Area ( $W$ ): Defined as the Maximum Inscribed Circle (MIC) of the convex hull formed by the 2D projections of the ceiling-mounted LEDs. This region represents the high-performance core where users typically engage in focused work.
- Non-Activity Area: The surrounding region within the Minimum Enclosing Circle (MEC) of the convex hull, representing areas with lower performance requirements and lower user activity density.
- Receiving Plane ( $I$ ): Defined as the intersection of the MEC and the physical boundaries of the space.
Non-Line-of-Sight (NLOS) Sensing for Localization: The system utilizes NLOS channels for real-time user localization. By analyzing the variation in optical power received by sensing photodiodes (PDs) caused by light reflected off a user's body, the system estimates user position. This process involves an offline phase (precomputing a reference dataset of power variations for candidate positions) and an online phase (calculating the Mean Squared Error between actual and predicted power variations to determine the user's location).
Adaptive Optimization Modes: Based on the detected user location, the system dynamically switches between three operational modes with distinct optimization objectives:
- No-User Mode: All LEDs operate at minimum power ( $P_{min}$ ) to maintain sensing capabilities while minimizing energy consumption.
- Uniformity Mode (Non-Activity Area): When a user is detected in the non-activity area, the system optimizes LED transmit powers to maximize Signal-to-Noise Ratio (SNR) uniformity across the receiving plane. This is formulated as a convex Quadratic Program (QP) to minimize SNR variance, ensuring stable service during movement without requiring high peak performance.
- Enhanced Mode (Activity Area): When a user is detected in the activity area, the system switches to minimizing total transmit power while strictly guaranteeing that all locations within the activity area meet specific SNR thresholds (for high-speed communication) and enhanced illuminance ranges (for focused work). This is formulated as a Linear Program (LP).

Key Contributions

Framework Design: The paper introduces an ISCI framework that integrates sensing, communication, and illumination control, explicitly prioritizing energy efficiency alongside performance.
Geometric Partitioning: A novel geometric approach is proposed to define activity and non-activity zones based on LED deployment geometry (using MEC and MIC), providing a computationally tractable method to differentiate user needs.
Dynamic Switching Mechanism: The system utilizes NLOS sensing to act as a dynamic switch, adapting the optimization objective (minimizing power vs. maximizing uniformity) in real-time based on user presence and location.
Mathematical Formulation: The optimization problems for both uniformity and enhanced modes are rigorously formulated as convex QP and LP problems, respectively, ensuring efficient solvability.

Numerical Results
Simulations were conducted in a $5 \times 5 \times 3$ m $^3$ indoor space with 8 randomly deployed LEDs and 8 sensing PDs. The results demonstrate:

Energy Efficiency: The adaptive ISCI approach achieved a 53.59% reduction in energy consumption compared to a non-adaptive system where all LEDs operate at fixed normal power.
SNR Uniformity: In the non-activity area, the system improved SNR uniformity by 57.79% (reducing SNR variance from 1.99 to 0.84) compared to unoptimized baselines.
Localization Accuracy: The system maintained a mean localization error of 0.071 m, with a maximum error of 0.689 m, despite using a non-optimized, random LED configuration.
Constraint Satisfaction: The framework successfully satisfied all illumination constraints (ranging from 300 lx to 2000 lx depending on the mode) and communication SNR thresholds.

Significance and Claims
The paper claims that this adaptive framework effectively resolves the inherent conflict between high-performance ISAC requirements and the practical needs for energy savings and visual comfort. By treating energy savings as a co-equal objective and utilizing user location as a dynamic control variable, the system avoids the "one-size-fits-all" high-power approach of current research. The authors assert that the framework provides a robust method for jointly managing ISCI performance and energy efficiency in indoor VLC systems. The work suggests that while the current results were achieved with random LED deployment, strategic deployment of LEDs and sensing PDs could further enhance localization accuracy and system performance. Future work is identified as extending the framework to complex multi-user environments and investigating transition algorithms to mitigate communication interruptions and flicker during mode switching.

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