Bajaj Parveen, Kataria Aman, Puri Vikram, Gupta Sachin, Min Hong
University Institute of Engineering, Chandigarh University, Gharuan, Mohali 140413, India.
University Centre for Research and Development, Chandigarh University, Gharuan, Mohali 140413, India.
Sensors (Basel). 2024 Dec 5;24(23):7797. doi: 10.3390/s24237797.
In the dynamic landscape of the tech industry, the escalating requirement for swift and secure data transmission has catalyzed innovation in integrated communication systems. Free-Space Optics (FSOs) has emerged as a promising contender in optical communications. While conventional optical fiber systems can achieve bit rates of up to 40 Gbps with proper design, they are limited primarily by electronics rather than semiconductor laser capabilities. This study presents an integrated framework that combines FSOs, blockchain technology, and sensor networks to address challenges in data transmission, security, and environmental adaptation. This study analyzes FSOs system performance through the Quality (Q) Factor and Bit Error Rate (BER), comparing systems with and without Erbium-Doped Fiber Amplifiers (EDFAs) across various bit rates (8, 12, 16, and 20 Gbps) and transmission distances (5-25 km). To enhance data security and reliability, a blockchain architecture is incorporated with smart contracts and an InterPlanetary File System (IPFS) for storing and validating results generated from FSOs simulation. Additionally, this study explores the design of sensor network models for FSOs technology by investigating how distributed sensor arrays can be theoretically integrated with FSOs systems, with testing focused on FSOs performance and blockchain implementation.
在科技行业不断变化的格局中，对快速安全的数据传输的需求不断升级，推动了集成通信系统的创新。自由空间光通信（FSO）已成为光通信领域一个有前景的竞争者。虽然传统光纤系统经过适当设计可实现高达40 Gbps的比特率，但它们主要受电子设备而非半导体激光能力的限制。本研究提出了一个集成框架，将FSO、区块链技术和传感器网络结合起来，以应对数据传输、安全和环境适应性方面的挑战。本研究通过质量（Q）因子和误码率（BER）分析FSO系统性能，比较了有无掺铒光纤放大器（EDFA）的系统在各种比特率（8、12、16和20 Gbps）和传输距离（5 - 25 km）下的情况。为了提高数据安全性和可靠性，将区块链架构与智能合约和星际文件系统（IPFS）结合，用于存储和验证FSO模拟产生的结果。此外，本研究通过研究分布式传感器阵列如何从理论上与FSO系统集成，探索了FSO技术的传感器网络模型设计，测试重点是FSO性能和区块链实现。
