Deep Learning for Resource Allocation of a Marine Vehicular Ad-Hoc Network

被引：0
|
作者：
Liu, Xian [1 ]
机构：
[1] Univ Arkansas, Dept Syst Engn, Little Rock, AR 72204 USA
来源：
2020 IEEE LATIN-AMERICAN CONFERENCE ON COMMUNICATIONS (LATINCOM 2020) | 2020年
关键词：
Deep learning; machine learning; marine vehicular ad-hoc network; network optimization; neural networks; QoS-promotion; INTERNET;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The marine vehicular ad-hoc network (M-VANET) is one of prospective architectures to provide Internet services to various users in the oceanic environment. When multiple users share a single spectrum band, it highly desirable to design a optimal strategy to allocate the transmission power while mitigating the mutual interference. In this paper, we apply the deep learning (DL) methodology to solve such a problem.
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页数：6
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