Deep Reinforcement Learning Based Time-Domain Interference Alignment Scheduling for Underwater Acoustic Networks
Message conflicts caused by large propagation delays severely affect the performance of Underwater Acoustic Networks (UWANs). It is necessary to design an efficient transmission scheduling algorithm to improve the network performance. Therefore, we propose a Deep Reinforcement Learning (DRL) based T...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI
2022
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| Subjects: | |
| Online Access: | View Fulltext in Publisher |