Non-line-of-sight optical camera communication aided by a pilot

Chen, Shao-Qi; Chi, Xuefen; Li, Te-yu

doi:10.1364/ol.431932

Cited by 14 publications

(3 citation statements)

References 8 publications

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“…In further research on VLC in mobile scenarios, several promising directions can be pursued. Firstly, integrating advanced equalization and modulation techniques tailored specifically for mobile environments can significantly enhance the robustness and reliability of VLC systems [28,29]. This could involve the development of adaptive algorithms capable of dynamically adjusting parameters in response to changes in ambient lighting conditions and mobility patterns.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Laser-Based Mobile Visible Light Communication System

Hou,

Wang,

et al. 2024

Sensors

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Mobile visible light communication (VLC) is key for integrating lighting and communication applications in the 6G era, yet there exists a notable gap in experimental research on mobile VLC. In this study, we introduce a mobile VLC system and investigate the impact of mobility speed on communication performance. Leveraging a laser-based light transmitter with a wide coverage, we enable a light fidelity (LiFi) system with a mobile receiving end. The system is capable of supporting distances from 1 m to 4 m without a lens and could maintain a transmission rate of 500 Mbps. The transmission is stable at distances of 1 m and 2 m, but an increase in distance and speed introduces interference to the system, leading to a rise in the Bit Error Rate (BER). The mobile VLC experimental system provides a viable solution to the issue of mobile access in the integration of lighting and communication applications, establishing a solid practical foundation for future research.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Laser-Based Mobile Visible Light Communication System

Hou,

Wang,

et al. 2024

Sensors

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“…Innovations in receiver diversity and computational methods, such as neural networks, have markedly improved positioning accuracy within Light Positioning Technologies [16]. Recent research has introduced innovative tracking algorithms and explored the potential of artificial intelligence in optimizing VLP signal decoding processes, addressing challenges such as the need for dense LED distributions [17], line-of-sight constraints [18], and the impact of environmental factors.…”

Section: Related Workmentioning

confidence: 99%

Neural Network-Based Detection of OCC Signals in Lighting-Constrained Environments: A Museum Use Case

Rufo,

Aguiar-Castillo,

Rufo

et al. 2024

Electronics

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This research presents a novel approach by applying convolutional neural networks (CNNs) to enhance optical camera communication (OCC) signal detection under challenging indoor lighting conditions. The study utilizes a smartphone app to capture images of an LED lamp that emits 25 unique optical codes at distances of up to four meters. The developed CNN model demonstrates superior accuracy and outperforms traditional methodologies, which often struggle under variable illumination. This advancement provides a robust solution for reliable OCC detection where previous methods underperform, particularly in the tourism industry, where it can be used to create a virtual museum on the Unity platform. This innovation showcases the potential of integrating the application with a virtual environment to enhance tourist experiences. It also establishes a comprehensive visible light positioning (VLP) system, marking a significant advance in using CNN for OCC technology in various lighting conditions. The findings underscore the effectiveness of CNNs in overcoming ambient lighting challenges, paving the way for new applications in museums and similar environments and laying the foundation for future OCC system improvements.

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“…OCC is not bounded in LOS communication technique. Some authors already developed OCC for NLOS communication system [10] [11]. In NLOS, the performance of the system depends on many factors such as neighboring light's illumination, surrounding reflective surface, interference from other sources etc.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of Remote Controlling System Using GAN in Optical Camera Communication

et al. 2023

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This paper illustrates the controlling mechanism along with data transmission using optical camera communication in both line-of-sight and non-line-of sight (NLOS) environment. The transmitter of the system is mainly composite of microcontroller (Arduino Mega), DHT sensor, two LEDs, and four push button switches. Here, two LEDs are continuously transmitting the control and data signal. The control signal is operated through push button switches. We have used four different control signals that are transmitted from the LEDs and data transmission by collecting data from the surrounding through the temperature and humidity sensor. The entire transmitter operations are processed and controlled through arduino programming in a microcontroller. The COOK modulation technique is used for this system. For data reception, we have used laptop's camera that is controlled through five different exposure times and operated based on the rolling shutter effect of the camera. A logistic regression algorithm is applied to recognize the data transmitting LED from the normalized intensity of the stripe patterns. The receiver is capable to collect data under certain conditions, if the light source is obstructed by an object through deep neural network. Again, Generative Adversial Network (GAN) is used as a decoder to reduce the BER during moving scenario and NLOS conditions. Different activation functions are used in the GAN model to find the optimum solution for the system. However, we have archived the maximum 2.5 m communication distance with 10-4 BER. The receiver program is designed using Python 3.8.

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Non-line-of-sight optical camera communication aided by a pilot

Cited by 14 publications

References 8 publications

Laser-Based Mobile Visible Light Communication System

Laser-Based Mobile Visible Light Communication System

Neural Network-Based Detection of OCC Signals in Lighting-Constrained Environments: A Museum Use Case

Design and Implementation of Remote Controlling System Using GAN in Optical Camera Communication

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