Reflections over the Sea: Reconfigurable Intelligent Surface for Maritime Self-Powered Communications

2026-01-20

AI Summary

This work addresses the challenges of insufficient coverage, low availability, and poor robustness in maritime Internet-of-Things (IoT) communications under harsh sea conditions. To overcome these limitations, the authors propose a self-sustaining communication framework that integrates reconfigurable intelligent surfaces (RIS) with wave energy harvesting, deployed on offshore infrastructure such as wind turbines to enable energy-autonomous sensor nodes. A near-sea-surface dynamic channel model is developed, and RIS reflection parameters are adaptively optimized based on real-time channel state information to enhance multi-user communication rates. Experimental results demonstrate that the proposed approach significantly improves system performance by over 20% under adverse maritime conditions.

Technology Category

• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

Maritime communication is becoming a vital component of 6G networks, driven by the rapid expansion of the maritime economy. However, existing technologies face critical challenges in signal coverage, availability, and robustness, especially under harsh sea conditions. This paper proposes a novel framework for the maritime Internet-of-Things (IoT) communications that leverages the reconfigurable intelligent surface (RIS) mounted on offshore infrastructures, such as wind turbines, to enhance coverage and reliability. To capture dynamic maritime environment, a near-ocean-surface channel model is developed considering the impact of sea waves. In addition, a wave energy harvesting (EH) system is designed to self-power IoT sensors for data acquisition, processing, and transmission. To support real-time adaptation, channel state information is continuously measured to optimize RIS reflection parameters and maximize multi-user communication rates. Simulation results show that the proposed system significantly improves IoT communication performance by over 20%, under harsh sea conditions.

Problem

• maritime communication
• signal coverage
• robustness
• harsh sea conditions
• Internet-of-Things

Innovation

• Reconfigurable Intelligent Surface
• Maritime IoT
• Wave Energy Harvesting
• Near-Ocean-Surface Channel Model
• Self-Powered Communications