Performance Analysis of an Underwater Partitioned IRS-Assisted VLC Link With Energy Harvesting

• Published in: International Conference on Communication Systems and Networks (Online) pp. 998 - 1002
• Main Authors: Mehta, Himani, Kumar, Rohit, Prakriya, Shankar
• Format: Conference Proceeding
• Language: English
• Published: IEEE 06.01.2025
• Subjects: Energy harvesting; ergodicrate; Intelligent reflecting surface; Internet of Things; Monte Carlo methods; outage probability; Performance analysis; Power system reliability; Probability; Propagation losses; Reliability theory; System analysis and design; Visible light communication; Visible light communications
• ISSN: 2155-2509
• DOI: 10.1109/COMSNETS63942.2025.10885570

Underwater visible light communication (UVLC) offers high-speed data transmission but faces challenges like path loss, turbulence, pointing error and power constraints from internet of things (IoT) nodes. This paper introduces a partitioned intelligent reflecting surface (IRS) for energy harvesting (EH) and data transmission (DT) to tackle these challenges in an UVLC system. This dual-purpose IRS enhances system metrics like outage probability, ergodic rate and harvested energy. By using IRS for data transmission as well as EH to power the sensor node, this approach extends operational lifespan of the sensor node without frequent recharging. Closed-form mathematical expressions are derived for outage probability (OP) and ergodic rate (ER). This novel IRS-EH integration fills a research gap, improving coverage and signal reliability in underwater environments, and is validated through Monte Carlo simulations.