{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T15:02:43Z","timestamp":1779202963457,"version":"3.51.4"},"reference-count":64,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,2,18]],"date-time":"2022-02-18T00:00:00Z","timestamp":1645142400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61371091"],"award-info":[{"award-number":["61371091"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61801074"],"award-info":[{"award-number":["61801074"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017683","name":"Dalian Science and Technology Innovation Fund","doi-asserted-by":"publisher","award":["2019J11CY015"],"award-info":[{"award-number":["2019J11CY015"]}],"id":[{"id":"10.13039\/501100017683","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science General Foundation of Chinese Postdoctoral","award":["223227"],"award-info":[{"award-number":["223227"]}]},{"name":"Liaoning Natural Science Foundation","award":["2019-BS-021"],"award-info":[{"award-number":["2019-BS-021"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, we investigate how to efficiently utilize channel bandwidth in heterogeneous hybrid optical and acoustic underwater sensor networks, where sensor nodes adopt different Media Access Control (MAC) protocols to transmit data packets to a common relay node on optical or acoustic channels. We propose a new MAC protocol based on deep reinforcement learning (DRL), referred to as optical and acoustic dual-channel deep-reinforcement learning multiple access (OA-DLMA), in which the sensor nodes utilizing the OA-DLMA protocol are called agents, and the remainder are non-agents. The agents can learn the transmission patterns of coexisting non-agents and find an optimal channel access strategy without any prior information. Moreover, in order to further enhance network performance, we develop a differentiated reward policy that rewards specific actions over optical and acoustic channels differently, with priority compensation being given to the optical channel to achieve greater data transmission. Furthermore, we have derived the optimal short-term sum throughput and channel utilization analytically and conducted extensive simulations to evaluate the OA-DLMA protocol. Simulation results show that our protocol performs with near-optimal performance and significantly outperforms other existing protocols in terms of short-term sum throughput and channel utilization.<\/jats:p>","DOI":"10.3390\/s22041628","type":"journal-article","created":{"date-parts":[[2022,2,21]],"date-time":"2022-02-21T08:34:47Z","timestamp":1645432487000},"page":"1628","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Deep Reinforcement Learning Based Optical and Acoustic Dual Channel Multiple Access in Heterogeneous Underwater Sensor Networks"],"prefix":"10.3390","volume":"22","author":[{"given":"Enhong","family":"Liu","sequence":"first","affiliation":[{"name":"College of Information Science and Technology, Dalian Maritime University, Dalian 116026, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0506-0021","authenticated-orcid":false,"given":"Rongxi","family":"He","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Dalian Maritime University, Dalian 116026, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaojing","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Dalian Maritime University, Dalian 116026, China"},{"name":"School of Electrical Engineering, Dalian University of Science and Technology, Dalian 116052, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cunqian","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Dalian Maritime University, Dalian 116026, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"998","DOI":"10.1121\/1.5119263","article-title":"Doppler scale estimation for varied speed mobile frequency-hopped binary frequency-shift keying underwater acoustic communication","volume":"146","author":"Qiao","year":"2019","journal-title":"J. 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