An Efficient approach Network Selection and Fast Delivery Handover Route 5G LTE Network

O. P. Mishra, Gaurav Morghare
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引用次数: 2

Abstract

To move from 4G to 5G technology spectrum deficiency is an important criteria which can be overcome by an efficient technology called Cognitive Radio (CR). This can be achieved by continuous sensing the spectrum band, and detecting the unused frequency bands which would be not used by licensed band and without any unwanted interference to the primary user or licensed user (PU). We Proposed NN-PSO method for network selection and Fast Delivery handover route mechanism in order to increase system efficiency by consider more number of SUs in network and providing to their preferences, and respect the criteria of primary network operators, at the same time. The goal is to provide SUs good network and fast delivery handover route with a high QoS based on the criteria of SU, subject to the interference boundation of each existing network with other channels. The proposed technique Neural Network and Particle swarm optimization would be use to solve the Network selection and optimization problem. Finally, experimental results and numerical parameters represent the effectiveness of the proposed NN-PSO methods to finding a near-optimal solution for network selection.
一种高效的5G LTE网络选择方法及快速交付切换路由
从4G技术过渡到5G技术频谱不足是一个重要的标准,这可以通过一种称为认知无线电(CR)的高效技术来克服。这可以通过连续感知频谱带来实现,并检测未使用的频段,这些频段不会被许可频段使用,并且不会对主用户或许可用户(PU)产生任何不必要的干扰。为了提高系统效率,我们提出了基于NN-PSO的网络选择方法和快速交付切换路由机制,该方法考虑了网络中更多的SUs数量并提供了它们的偏好,同时也尊重了主要网络运营商的标准。目标是在每个现有网络与其他信道的干扰边界限制下,根据SU的标准,为SU提供良好的网络和具有高QoS的快速交付切换路由。采用神经网络和粒子群优化技术来解决网络的选择和优化问题。最后,实验结果和数值参数表明了所提出的神经网络-粒子群算法在寻找网络选择的近最优解方面的有效性。
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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