基于支持向量机的高速铁路异构超密集网络切换方案

IF 1.5 4区 计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Siling Wang, Li Zhang
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引用次数: 0

摘要

为了满足高速铁路(HSR)系统日益增长的需求并扩大网络覆盖范围,5G 网络考虑密集部署大量小蜂窝(SC)。然而,密集 SC 的部署和列车的高速行驶导致了一些具有挑战性的问题,如干扰、频繁切换 (HO)、HO 故障率增加,进而导致整体服务质量 (QoS) 下降。为了应对切换中的挑战,提出了一种基于支持向量机(SVM)的改进型切换决策策略。考虑到高铁网络中可能存在的可用状态,HO 决策被视为一个分类问题。从仿真结果可以看出,所提出的方案能够减少 HO 的数量和 HO 的失败率,并显著提高网络性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Support vector machine-based handover scheme for heterogeneous ultra dense network of high-speed railway

Support vector machine-based handover scheme for heterogeneous ultra dense network of high-speed railway

In order to meet the growing demands and extend network coverage for high-speed railway (HSR) system, the dense deployment of a large number of small cells (SCs) is considered for 5G networks. However, the deployment of dense SCs and the high speed of trains result in challenging problems such as interference, frequent handovers (HOs), increased HO failure rate, and consequently the deteriorated overall quality of service (QoS). In order to address the challenges in handover, an improved handover decision strategy is proposed based on Support Vector Machine (SVM). The HO decision making is considered as a classification problem taking into account available states that they may have in the HSR network. From the simulation results, it is observed that the proposed scheme is capable of decreasing the number of HO, HO failure rate and enhancing the network performance remarkably.

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来源期刊
IET Communications
IET Communications 工程技术-工程:电子与电气
CiteScore
4.30
自引率
6.20%
发文量
220
审稿时长
5.9 months
期刊介绍: IET Communications covers the fundamental and generic research for a better understanding of communication technologies to harness the signals for better performing communication systems using various wired and/or wireless media. This Journal is particularly interested in research papers reporting novel solutions to the dominating problems of noise, interference, timing and errors for reduction systems deficiencies such as wasting scarce resources such as spectra, energy and bandwidth. Topics include, but are not limited to: Coding and Communication Theory; Modulation and Signal Design; Wired, Wireless and Optical Communication; Communication System Special Issues. Current Call for Papers: Cognitive and AI-enabled Wireless and Mobile - https://digital-library.theiet.org/files/IET_COM_CFP_CAWM.pdf UAV-Enabled Mobile Edge Computing - https://digital-library.theiet.org/files/IET_COM_CFP_UAV.pdf
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