An Optimal Resource Allocation in 5G Environment Using Novel Deep Learning Approach

Q3 Social Sciences
Raja Varma Pamba, Rahul Bhandari, A. Asha, A. Bist
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引用次数: 0

Abstract

In recent times, the advancement in network devices has focused entirely on the miniaturization of services that should ensure better connectivity between them via fifth generation (5G) technology. The 5G network communication aims to improve Quality of Service (QoS). However, the allocation of resources is a core problem that increases the complexity of packet scheduling. In this paper, a resource allocation model is developed using a novel deep learning algorithm for optimal resource allocation. The novel deep learning is formulated using the constraints associated with optimal radio resource allocation. The objective function design aims at reducing the system delay. The study predicts the traffic in a complex environment and allocates resources accordingly. The simulation was conducted to test the scheduling efficacy and the results showed an improved rate of allocation than the other methods.
基于新型深度学习方法的5G环境下资源优化分配
最近,网络设备的进步完全集中在服务的小型化上,通过第五代(5G)技术确保它们之间更好的连接。5G网络通信旨在提高服务质量(QoS)。然而,资源的分配是一个核心问题,增加了数据包调度的复杂性。本文利用一种新颖的深度学习算法建立了资源分配模型,以实现资源的最优分配。这种新颖的深度学习是使用与最佳无线电资源分配相关的约束来制定的。目标函数设计的目的是减少系统的延迟。该研究对复杂环境下的流量进行预测,并据此分配资源。通过仿真验证了该方法的调度效率,结果表明该方法的分配率比其他方法有所提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Mobile Multimedia
Journal of Mobile Multimedia Social Sciences-Communication
CiteScore
1.90
自引率
0.00%
发文量
80
期刊介绍: The scope of the journal will be to address innovation and entrepreneurship aspects in the ICT sector. Edge technologies and advances in ICT that can result in disruptive concepts of major impact will be the major focus of the journal issues. Furthermore, novel processes for continuous innovation that can maintain a disruptive concept at the top level in the highly competitive ICT environment will be published. New practices for lean startup innovation, pivoting methods, evaluation and assessment of concepts will be published. The aim of the journal is to focus on the scientific part of the ICT innovation and highlight the research excellence that can differentiate a startup initiative from the competition.
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