Underwater communication is a complex and critical technology with significant value in the fields of marine resource development, marine scientific research, and military applications. The research on Underwater communication mainly focuses on improving the communication rate, enhancing the stability of signal transmission and anti-jamming ability, and combining it with artificial intelligence to meet the growing demand for Underwater communication. Machine learning is an important development direction for Underwater communication. Therefore, this paper firstly reviews the development of China and the rest of the world based on the time-tracing method to analyze Underwater communication technology in both regions, and then this paper analyzes the different machine learning algorithms based on the topic classification, and introduces the challenges of machine learning in the field of Underwater communication, and discusses the limitations of the traditional methods, including the signal fading, multipath propagation, and noise interference. noise interference. Next, the paper describes the potential role of machine learning in Underwater communications, including channel modelling, signal modulation, demodulation, and adaptive aspects. Finally, it summarizes the current research progress and looks forward to the future development trend of machine learning in Underwater communications.
Underwater communication; Machine learning; Analysis of Chinese and foreign underwater communication Technology
Yang. K., Xie Y., Si K, Zeng S., Yang K, Zhang D. Machine Learning based on Underwater Communication Technology. Eng. Solut. Mech. Mar. Struct. Infrastruct., 2024, 1(3), doi: 10.58531/esmmsi/1/3/4