Visible light positioning (VLP) has become one of the most important technologies for providing highly accurate location-based services. Despite this, line-of-sight (LOS) VLP systems have severe limitations when operating in complex and dynamic indoor environments. We propose a non-LOS VLP system based on an image sensor (IS) and pixel coordinate fingerprinting operating under shadowing and blocking. The system does not require communication between the transmitter and the receiver eliminating the need for a complex modulation process. For the first time, we utilize the highlighted center pixel coordinates on an IS as the fingerprint features and extract highlight center coordinates using the deep learning model Yolov8. Furthermore, we propose an Elastic Net regression with Weighted K-Nearest Neighbor Residual Correction algorithm to improve the positioning performance, which employs an Elastic Net for global prediction and a weight k-nearest neighbor algorithm to correct the global prediction residuals by leveraging the residual information from weighted neighboring samples. The experimental results show that the average positioning error and 90th percentile errors of the proposed system are 4.77 and 6.67 cm, respectively, with only 16 training points. In addition, the stability of the system is verified by arbitrary and diagonal sets.

Visible light positioning (VLP) is a low-cost, highly accurate alternative localization technology for indoor applications that makes use of existing light emitting diode (LED)-based lights, which is highly accurate and low costs. It is, however, a major challenge for the existing VLP systems to achieve line-of-sight (LOS) positioning in complex and variable indoor environments. We propose a non-LOS (NLOS) fingerprint-based VLP system based on a multipixel photon counter (MPPC) to address the problem of obstructed LOS paths. Using MPPC, very faint light can be detected with a very high sensitivity and excellent photon counting capability, which enhances the ability to recognize and detect signals in an NLOS environment. We propose a novel method of generating fingerprint database using the NLOS channel model, which construct the relationship between the received signal strength and the distance from MPPC to the virtual image of LED interpolated by only knowing the distance between the LED and the interpolation position. Furthermore, we propose an optimal parameter weighted K-nearest neighbor algorithm, which utilizes the mean absolute error (MAE) as the evaluation metric. In this algorithm, a grid search method is employed to determine the optimal number of neighbors and the distance metric for each test point, thereby enhancing the positioning accuracy. Using only 25 offline measurements, the measured average positioning error (PE) and 90th percentile error are 4.02 and 9.98 cm, respectively, when the MPPC height is 70 cm.

As part of Internet of Things networks, visible light communication (VLC) technology has excelled in recent years. Compared to radio frequency (RF) technologies, VLC offers unlicensed spectrum, low interference, high security, and energy efficiency, making it ideal for short-range communication. However, its performance is severely limited under the non-line-of-sight (NLOS) links. Intelligent reflecting surface (IRS), as an innovative technology, can dynamically and passively adjust the wireless environment. In this article, we propose the use of optical IRSs (OIRSs) to enhance VLC performance under NLOS scenarios. Specifically, we develop ZEMAX-based nonsequential ray tracing to accurately model light propagation in OIRS-assisted indoor VLC environments. Then, we establish a system model and formulate an optimization problem aimed at maximizing the received optical power. To solve this, we propose a genetic-enhanced sine–cosine algorithm with elite strategy and dynamic opposition learning (GESCA-ED), which optimizes the rotational degrees of freedom of each OIRS element. Furthermore, we design a hardware-based experimental platform featuring a configurable OIRS control system, which is integrated with GESCA-ED for real-time optimization in an actual NLOS environment. Experimental results demonstrate significant improvements in received optical power, bit error rate (BER), and transmission distance, achieving a BER of$1\times 10^{-6}$over a 3.8-m NLOS link. These results confirm that the proposed system effectively extends signal coverage, enabling communication between mobile users regardless of their spatial positions.

Channel State Information (CSI), characterizing real-time optical channel conditions, is critical for system optimization in visible light communication (VLC) systems. In VLC networks, CSI acquisition typically relies on uplink feedback mechanisms that require frequent updates due to rapid channel variations. As access point (AP) density increases, this feedback process incurs substantial overhead that scales with network size, becoming a major bottleneck for system scalability. ‌By decoupling static channel characteristics from dynamic user positions‌, this paper proposes a dual-step strategy decoupling offline channel quantization from online uplink positioning. This enables efficient downlink CSI reconstruction via pre-trained lookup tables, bypassing real-time computations. The feedback overhead scales as 1/M of conventional methods in M-AP systems, with experiments showing less than 3% spectrum efficiency loss for precoding-sensitive applications in high speed mobile scenarios. The framework’s adaptability to varying LED densities further supports practical deployment in large-scale networks.‌ This work resolves the CSI acquisition bottleneck, enabling scalable VLC systems with minimal performance degradation.

Visible light positioning (VLP) is one of the effective solutions for low-cost and high-precision indoor positioning due to its advantages of low cost, high energy efficiency, and immunity from radio frequency induced electromagnetic interference. However, severe performance limitations in occluded environments present a major challenge for the development of VLP. We propose a non-line-of-sight (NLOS) VLP system based on a multipixel photon counter (MPPC) to solve the problem of obstructed line-of-sight (LOS) paths. MPPC consists of multiple avalanche photodiodes operating in Geiger mode, which has very high sensitivity, excellent photon counting capability and can perform detection of very weak light at photon counting levels. It can effectively improve the recognition and detection of signals in NLOS environments. Using the NLOS channel model, we innovatively propose a NLOS-MPPC-VLP positioning theory, which utilizes the NLOS optical signals received by the MPPC to construct the relationship between the received signal strength and the distance from the MPPC to the virtual images of the light emitting diode (LED). Through this theory, the trilateration algorithm is used to calculate the position of the receiver. The experimental results show that the average positioning errors for the proposed system are 8.77 and 10.15 cm for 70 and 100-cm MPPC heights, respectively.

Visible light positioning (VLP) is playing a critical role in delivering better location-based services. However, traditional VLP systems rely on line-of-sight (LOS) paths and have a requirement for large numbers of light-emitting diodes (LEDs) and sensors, making them unprepared for various scenarios. This article proposes a 3-D non-line-of-sight (NLOS) VLP system using a single LED and an image sensor (IS) to address the problem of obstructed LOS paths. On the one hand, an optical camera communication (OCC) subsystem is designed to receive the transmitter’s position based on NLOS links. In contrast, two highlights are visible in the picture when the IS captures the reflected light from the floor. Using the proposed luminance distribution model (LDM), it can be demonstrated that the two highlights can be regarded as the projections formed by two virtual LEDs. Based on the projection equations of the two virtual LEDs, an image sensing algorithm can estimate the receiver’s position. Experimental results show that the proposed system can achieve a 90th percentile accuracy of < 22 cm for 3-D positioning. To the best of author’s knowledge, this is the first work to demonstrate 3-D NLOS VLP using just a single LED and an IS. Additionally, the proposed LDM is the first physically based model for the first reflected light to estimate the channel gain of an NLOS link.

We experimentally demonstrate a multicarrier interleave division multiple access (IDMA) scheme for bidirectional visible light communications using orthogonal frequency division multiplexing (OFDM), which has the advantages of good tolerance against multi‐path, high spectral efficiency and excellent transmission performance. The generated IDMA signals are modulated on OFDM subcarriers and the different users are separated by the interleavers. When compared with orthogonal frequency domain multiple access, IDMA‐OFDM offers increased transmission spans of 30 and 50 cm at a bit error rate (BER) of 10 −3 in the cases of two and four users, respectively.

In this study, the authors present efficient frequency‐domain channel estimation (CE) methods based on the adjacent subcarriers frequency‐domain averaging (ASFA) and minimum mean squared error (MMSE) schemes for the orthogonal frequency division multiplexing/offset quadrature amplitude modulation (OFDM/OQAM) passive optical network (PON) system. The complete channel transmission response for OFDM/OQAM‐PON with the chromatic dispersion induced intrinsic imaginary interference effect is systemically derived. Compared with the conventional interference approximation CE method, ASFA and MMSE offer improved receiver sensitivity.

The authors present efficient frequency‐domain channel estimation methods based on the intra‐symbol frequency‐domain averaging (ISFA), minimum mean squared error (MMSE) and weighted inter‐frame averaging (WIFA) schemes for the orthogonal frequency division multiplexing (OFDM) visible light communications (VLC) system. OFDM‐VLC with quadrature phase shift keying, 16‐ and 64‐quadrature amplitude modulation mapping is experimentally demonstrated. Compared with the conventional least square channel estimation method, ISFA, MMSE and WIFA offer improved performance with MMSE offering the best performance in terms of the error vector magnitude but at the cost of high complexity. The authors show that the WIFA can improve the estimation accuracy of time‐varying VLC optical channel.