Abstract
AbstractUnderwater is a harsh and dynamic environment. Its physical properties are unsteady in the space-time domain and that complicates the communication process inside the water. Moreover, underwater transmissions suffer from many attenuations and scattering sources due to several environmental noises such as shipping, turbulence, wave dynamics, and the background life of the marine organisms.In this chapter, we introduce the underwater communication basics and challenges compared with terrestrial networks, then illustrate the Internet of Underwater Things (IoUT) network structure and the underwater node architecture, and finally, overview the machine learning modeling in underwater communication.KeywordsUnderwaterInternet of Underwater Things (IoUT)Cooperative communicationMachine learning modelingUnderwater wireless sensor networksAmplify-and-forward (AF)Decode-and-forward (DF)Hybrid and cooperative transmissionTransmission power levelsRelayMoteMachine learning techniquesSupervised learningMachine learning algorithms
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