## 1 Introduction  
Since the 20 th century--from cable to optical cable, wired to wireless, analog to digital, and 1G to 5G--land communication has undergone rapid development and change. However, in the vastness of the ocean, the development of marine communication obviously lags behind that of land communication due to the complex and changing marine environment and the difficulty of offshore construction [1]. However, humans have historically been in awe of the ocean, which lies in both the Southern and Northern Hemispheres and is larger than the land area in either hemisphere. Although there are many setbacks and challenges in the development of marine communication, the exploration of the ocean is of great significance and value. In addition to having a very low frequency, electromagnetic waves attenuate quickly in water, and strong ultra-long waves can penetrate only approximately 100 m past the surface of water. Light waves are affected by absorption and scattering in water and can be transmitted only for short distances. Even the most distant blue and green lasers can be transmitted only for a few hundred meters underwater. Because sound waves can travel a relatively long distance in water, underwater acoustic communication is the main means of underwater wireless information transmission [2]. In the past decade, underwater acoustic networks (UANs) [3; 4; 5; 6; 7; 8; 9; 10] have attracted significant interest from both academia and industry due to the wide range of applications of UANs, including underwater environment monitoring. Various coexisting applications in oceans have led to multiple underwater networks sharing channel resources with each other [11]. Underwater acoustic channels are the medium of sound wave propagation and the foundation of underwater acoustic networks. [PERSON] et al. [12] examined several key aspects of hydroacoustic communication, discussing various architectures for two- and three-dimensional underwater sensor networks and detailing the characteristics of underwater channels. [PERSON] et al. [13] firstly explored the unique propagation feature of underwater acoustic channels. Secondly, they analyzed how the channel variations affect cognitive communication and networks. Thirdly, they investigated the constraints for cognitive networks relayed by underwater acoustic channels. Lastly, they drew a modeling scheme with both physical-layer and upper-layer considerations for the cognitive network. Time-varying multi-path propagation and non-Gaussian noise are two of the major factors that limit acoustic communication performance in shallow water. The simple Rayleigh fading ray model yields good agreement with data collected at ranges of 50 m to 1020 m. The fading statistics of interfering rays could also be explained with the model [14]. [PERSON] et al. [11] proposed the concept of a cognitive acoustic network. By sensing the surrounding spectrum usage, cognitive acoustic (CA) users in underwater cognitive acoustic networks (UCANs) are able to intelligently detect whether any portion of the spectrum is occupied and change their frequency, power, or even other operation parameters to temporarily use the idle frequencies without interfering with other networks. Spectrum sensing is a fundamental part of such cognitive acoustic networks. [PERSON] [15] defined and developed a cognitive radio architecture that organizes the knowledge of the radio domain into data structures that can be processed in real time, incorporating machine learning and natural language processing techniques into software radio. [PERSON] [16] showed that it is possible to combine cognitive radio with underwater acoustic communication, which provides a new research direction for the development and progress of underwater communication technology in the future. [PERSON] et al.