Resumen
Originating from the concept of cognitive networks (CNs), which are becoming popular in wireless terrestrial communication scenarios, underwater acoustic cognitive networks (UACNs) are drawing more and more attention in the field of the Internet of Underwater Things (IoUT). However, as the implementation of cognitive mechanisms in underwater acoustic networks is different from that of wireless scenarios, it is impossible or difficult for traditional simulation platforms to carry out simulations of UACNs. There is a lack of specialized simulation tools in terms of UACNs. To enable the quantitative evaluation of the effectiveness and performance enhancement of a UACNs in an adverse underwater environment, a simulation platform of acoustic cognitive networks (SPACNet) was designed and investigated in this article. First, based on a state machine-based protocol programming framework, the SPACNet is capable of supporting the implementation of different state-transform types associated with cognitive networking protocols. Moreover, to facilitate the realization of cognitive function at comprehensive levels of signal, information, and link, an underwater acoustic channel model with an environmental parameter input is integrated in SPACNet to generate underwater environment-driven multiple-aspect behaviors. Moreover, a simplified collision model consisting of an environment factor, channel response, and node location is used to reduce the complexity of the simulation of UACNs signal reception. A simulation was carried out to verify the effectiveness of SPACNet in evaluating the cognitive capabilities of UACNs. Finally, a field UACNs experiment was performed to validate the general consistency between the conclusion obtained with the SPACNet-based simulation and that from the field test.