CN111787624A - D2d辅助的蜂窝网络中的一种基于深度学习的可变维度资源分配算法 - Google Patents
D2d辅助的蜂窝网络中的一种基于深度学习的可变维度资源分配算法 Download PDFInfo
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- CN111787624A CN111787624A CN202010598328.3A CN202010598328A CN111787624A CN 111787624 A CN111787624 A CN 111787624A CN 202010598328 A CN202010598328 A CN 202010598328A CN 111787624 A CN111787624 A CN 111787624A
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- 238000013468 resource allocation Methods 0.000 title claims abstract description 12
- 238000004891 communication Methods 0.000 claims abstract description 37
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- 238000013528 artificial neural network Methods 0.000 claims abstract description 19
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- H—ELECTRICITY
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Cited By (3)
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CN114142908A (zh) * | 2021-09-17 | 2022-03-04 | 北京航空航天大学 | 一种面向覆盖侦察任务的多无人机通信资源分配方法 |
CN115474276A (zh) * | 2021-06-10 | 2022-12-13 | 山东大学 | 基于深度学习的多小区蜂窝网络下行链路资源分配方法 |
CN115483964A (zh) * | 2022-09-30 | 2022-12-16 | 中国人民解放军陆军工程大学 | 一种空天地一体化物联网通信资源联合分配方法 |
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CN110808824A (zh) * | 2019-11-12 | 2020-02-18 | 哈尔滨工业大学 | 低轨卫星星地链路的高谱效稀疏码多址接入方法 |
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CN110808824A (zh) * | 2019-11-12 | 2020-02-18 | 哈尔滨工业大学 | 低轨卫星星地链路的高谱效稀疏码多址接入方法 |
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HAORAN SUN: "Learning to Optimize: Training Deep Neural Networks for Interference Management", 《 IEEE TRANSACTIONS ON SIGNAL PROCESSING》 * |
廖晓闽: "基于深度强化学习的蜂窝网资源分配算法", 《通信学报》 * |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115474276A (zh) * | 2021-06-10 | 2022-12-13 | 山东大学 | 基于深度学习的多小区蜂窝网络下行链路资源分配方法 |
CN115474276B (zh) * | 2021-06-10 | 2024-03-19 | 山东大学 | 基于深度学习的多小区蜂窝网络下行链路资源分配方法 |
CN114142908A (zh) * | 2021-09-17 | 2022-03-04 | 北京航空航天大学 | 一种面向覆盖侦察任务的多无人机通信资源分配方法 |
CN115483964A (zh) * | 2022-09-30 | 2022-12-16 | 中国人民解放军陆军工程大学 | 一种空天地一体化物联网通信资源联合分配方法 |
CN115483964B (zh) * | 2022-09-30 | 2024-03-08 | 中国人民解放军陆军工程大学 | 一种空天地一体化物联网通信资源联合分配方法 |
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