2023
DOI: 10.3390/app132312950
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Joint Channel and Power Assignment for Underwater Cognitive Acoustic Networks on Marine Mammal-Friendly

Libin Xue,
Chunjie Cao

Abstract: When marine animals and underwater acoustic sensor networks (UASNs) share spectrum resources, problems such as serious harm caused to marine animals by underwater acoustic systems and scarcity of underwater spectrum resources are encountered. To address these issues, a mammal-friendly underwater acoustic sensor network channel power allocation algorithm is proposed. Firstly, marine animals are treated as authorized users and sensor nodes as unauthorized users. Considering the interference level of sensor nodes… Show more

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Cited by 2 publications
(2 citation statements)
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“…The environment and conditions of an underwater acoustic sensor network can change over time and with external changes, which can lead to communication disruptions between sensor nodes, data corruption, or node failures, which in turn affect the reliability and accuracy of the entire network [9]. The network must promptly detect and distinguish abnormal behaviors while also dynamically adapting its trust evaluation.…”
Section: Introductionmentioning
confidence: 99%
“…The environment and conditions of an underwater acoustic sensor network can change over time and with external changes, which can lead to communication disruptions between sensor nodes, data corruption, or node failures, which in turn affect the reliability and accuracy of the entire network [9]. The network must promptly detect and distinguish abnormal behaviors while also dynamically adapting its trust evaluation.…”
Section: Introductionmentioning
confidence: 99%
“…The application of collaborative communication in free-space optical (FSO) communication systems which utilizes statistical laws to achieve overlapping spectrum sharing through power control by means of statistical information about the animal's location. In [13], the researchers proposed a mammal-friendly channel power allocation algorithm for hydroacoustic sensor networks. The interference level of sensor nodes with marine animals was fully considered, and a game model with a unique Nash equilibrium point was established based on the network interference level and node residual energy.…”
Section: Introductionmentioning
confidence: 99%