基于5G-V2X的深度学习算法优化队列行驶车辆基站分配

2019 IEEE 8th Global Conference on Consumer Electronics (GCCE) Pub Date : 2019-10-01 DOI:10.1109/GCCE46687.2019.9014645

Chi-Chuan Ho, Bo-Hong Huang, Meng-Ting Wu, Tin Yu Wu

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引用次数: 5

摘要

本研究提出利用基于5G- v2x的深度学习算法，创建人工智能(AI)模型，以优化正在进行的队列车辆的5G基站分配。从仿真中提取实验数据，研究基站与车辆之间的通信、信号强度、服务和队列车辆的速度等参数，以达到最优的参数调整。

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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Optimized Base Station Allocation for Platooning Vehicles Underway by Using Deep Learning Algorithm Based on 5G-V2X

This study proposes to use deep learning algorithm based on 5G-V2X to create an artificial intelligence (AI) model for optimizing 5G base station allocation for platooning vehicles underway. Experimental data are retrieved from the simulation, and parameters, including communication between base stations and vehicles, signal strength, services and speed of platooning vehicles, are investigated to reach the optimal parameter adjustment.

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来源期刊

2019 IEEE 8th Global Conference on Consumer Electronics (GCCE)

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