An Optical Differential Method for Underwater Wireless Communication in Turbid Environments

Underwater optical communication has emerged as an essential tool for exploring oceanography and marine resources for underwater vehicles or robots in recent years. Current techniques mostly rely on the paradigm of intensity modulation and direct detection, resorting to more powerful light sources o...

Full description

Saved in:
Bibliographic Details
Main Authors: Xiaoqing Tian, Feng Jiang, Hongfei Yu, Hang Xu, Jiyong Wang
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Photonics
Subjects:
Online Access:https://www.mdpi.com/2304-6732/12/2/112
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Underwater optical communication has emerged as an essential tool for exploring oceanography and marine resources for underwater vehicles or robots in recent years. Current techniques mostly rely on the paradigm of intensity modulation and direct detection, resorting to more powerful light sources on the transmitting side and more sensitive detectors on the receiving side, thus causing excess energy consumption and system costs. Here, a novel approach, namely, the optical differential communications method (ODCM), is proposed to extend the distance of underwater wireless optical communications in turbid water. The underlying physical reason is explained in theory and demonstrated in experiments. It is found that the stable propagation distance of ODCM could be further extended without relying on intensive light sources, in contrast to conventional methods, showing potential for longer communication ranges. Tests of underwater optical communications are conducted, and the results show that ODCM can significantly reduce the bit error rate (BER) at the same propagation distance or extend the propagation distance for the same BER level of optical signals. As such, this study provides an avenue for long-distance and stable underwater wireless optical communications in turbid environments.
ISSN:2304-6732