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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Deep Learning-Based Solutions for 5G Network and 5G-Enabled Internet of Vehicles: Advances, Meta-Data Analysis, and Future Direction
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Deep Learning-Based Solutions for 5G Network and 5G-Enabled Internet of Vehicles: Advances, Meta-Data Analysis, and Future Direction

机译:基于深度学习的5G网络和5G车联网解决方案:进展、元数据分析与未来发展方向

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摘要

The advent of the 5G mobile network has brought a lot of benefits. However, it prompted new challenges on the 5G network cybersecurity defense system, resource management, energy, cache, and mobile network, therefore making the existing approaches obsolete to tackle the new challenges. As a result of that, research studies were conducted to investigate deep learning approaches in solving problems in 5G network and 5G powered Internet of Vehicles (IoVs). In this article, we present a survey on the applications of deep learning algorithms for solving problems in 5G mobile network and 5G powered IoV. The survey pointed out the recent advances on the adoption of deep learning variants in solving the challenges of 5G mobile network and 5G powered IoV. The deep learning algorithm solutions for security, energy, resource management, 5G-enabled IoV, and mobile network in 5G communication systems were presented including several other applications. New comprehensive taxonomies were created, and new comprehensive taxonomies were suggested, analysed, and presented. The challenges of the approaches are already discussed in the literature, and new perspective for solving the challenges was outlined and discussed. We believed that this article can stimulate new interest in practical applications of deep learning in 5G network and provide clear direction for novel approaches to expert researchers.
机译:5G移动网络的出现带来了很多好处。然而,它给5G网络网络安全防御系统、资源管理、能源、缓存和移动网络带来了新的挑战,因此,现有的方法已经过时,无法应对新的挑战。因此,我们进行了研究,以研究深度学习方法在解决 5G 网络和 5G 驱动的车联网 (IoV) 中的问题。在本文中,我们综述了深度学习算法在解决 5G 移动网络和 5G 车联网问题中的应用。该调查指出了采用深度学习变体解决5G移动网络和5G驱动的车联网挑战的最新进展。介绍了用于5G通信系统中安全、能源、资源管理、5G车联网和移动网络的深度学习算法解决方案,包括其他几个应用。创建了新的综合分类法,并提出、分析和提出了新的综合分类法。文献中已经讨论了这些方法的挑战,并概述和讨论了解决这些挑战的新视角。我们相信,本文可以激发人们对深度学习在5G网络中实际应用的新兴趣,并为专家研究人员提供明确的新方法方向。

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