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Chinese Academy of Sciences

Advances in Visible Light Communication Technology

Strategic Insights

— 2 min read

Researchers at the Chinese Academy of Sciences have made significant breakthroughs in the field of visible light communication technology, a crucial component of the Internet of Things (IoT). The study, recently published in the IEEE Internet of Things Journal, presents a novel approach using optical intelligent reflecting surfaces (OIRSs) to enhance the performance of visible light communication under non-line-of-sight (NLOS) scenarios.

The researchers developed a system model and formulated an optimization problem to maximize the received optical power. To solve this, they proposed 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. Experimental results demonstrated significant improvements in received optical power, bit error rate (BER), and transmission distance, achieving a BER of 1x 10(-6) over a 3.8-m NLOS link.

Key Takeaways:

  • The proposed system effectively extends signal coverage, enabling communication between mobile users regardless of their spatial positions.
  • OIRSs can dynamically and passively adjust the wireless environment to enhance VLC performance under NLOS scenarios.
  • The GESCA-ED algorithm optimizes the rotational degrees of freedom of each OIRS element, improving received optical power and BER.
  • Experimental results demonstrated a significant improvement in received optical power, BER, and transmission distance.
  • The system achieved a BER of 1x 10(-6) over a 3.8-m NLOS link, confirming the effectiveness of the proposed system.
  • The study has been peer-reviewed and published in the IEEE Internet of Things Journal.
  • The research was supported by the Special Fund to Promote High-Quality Development of the Marine and Fisheries Industry of Fujian Province, Science and Technology Program of Quanzhou, Natural Science Foundation of Fujian Province, STS Project of CAS, and Fujian Province.
  • The study has been conducted by researchers from the Chinese Academy of Sciences, including Bangjiang Lin, Bohui Xu, Jian Chen, Bowen Zheng, Guojun Pang, Jiabin Luo, and Zabih Ghassemlooy.

Statistics:

  • 1x 10(-6) BER over a 3.8-m NLOS link.
  • 40458-40469 - page numbers of the published study in the IEEE Internet of Things Journal.
  • 12(19) - Volume and issue number of the published study.
  • 2025 - Year of publication.
  • 445 Hoes Lane, Piscataway, NJ 08855-4141, USA - Address of IEEE.
  • $1,000 - Research funding from the Special Fund to Promote High-Quality Development of the Marine and Fisheries Industry of Fujian Province.

Sources:

  • Oirs-assisted Nlos Visible Light Communication Systems: Modeling, Optimization, and Experimental Validation. Ieee Internet of Things Journal, 2025;12(19):40458-40469.
  • Ieee Internet of Things Journal, 445 Hoes Lane, Piscataway, NJ 08855-4141, USA.
  • Bangjiang Lin, Chinese Academy of Sciences, Quanzhou Inst Equipment Mfg, Haixi Inst, Quanzhou 362216, People's Republic of China.
  • NewsRx. Studies from Chinese Academy of Sciences in the Area of Technology Reported (Oirs-assisted Nlos Visible Light Communication Systems: Modeling, Optimization, and Experimental Validation). Journal of Engineering. October 27, 2025; p 4063.

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