基于SVM智能预测的车地多网融合无线通信系统方案的研究与设计

为提高城市轨道交通车地无线通信质量，提出了一种车地多网融合无线通信系统方案，方案利用线路中共存的多种车地无线网络提供多条通信链路，共同保障车地数据的稳定传输。针对如何选择最优网络进行数据传输这一关键技术点，采用支持向量机（SVM）分类方法实现智能选择。最后，通过搭建车地多网融合无线通信系统的仿真环境，进行实验仿真。仿真显示:列车在当前车地无线网络信号质量下降时，能够智能检测并切换至质量更优的无线网络完成车地数据通信。基于SVM智能预测的车地多网融合无线通信系统方案能够提高车地无线通信质量，该方案具备有效性和可行性。

Train-wayside multi-network integration wireless communication based on SVM intelligent prediction

In order to improve the stability of the train-wayside wireless communication of urban rail transit, a trainwayside wireless communication scheme based on multi-network integration was proposed in this paper which used a variety of wireless networks to ensure data transmission. Selecting the optimal network for data transmission was a key technical point in this scheme. The paper proposed an optimization network selection algorithm based on support vector machine(SVM) to solve network selection problems by classification method. Then experimental simulations were used to prove the availability and reliability of SVM on optimal network selection. In this paper, the simulation environment of multi-network integrated train-wayside communication was established. the simulation results show that the train can intelligently detect and switch to a better quality wireless network to complete train-wayside data communication when the signal quality of the current wireless network was degraded. The train-wayside multi-network integration wireless communication system scheme based on SVM can improve the wireless communication quality of train-wayside communication. The scheme has the effectiveness and feasibility.