高速移动环境下4G链路的测量与预测

MEASUREMENT AND PREDICTION OF 4G LINK IN HIGH-SPEED MOBILE ENVIRONMENT

高铁在高速移动的过程中,基于运营商的3G/4G无线通信技术无法满足向乘客提供高清直播视频服务的需求。主要是由于沿途运营商网络覆盖质量的不连续,多普勒效应及车体屏蔽等原因,导致实际运行中网络存在不稳定和不可预测问题,不能满足实时视频业务的需求。因此,基于大数据深度学习技术,结合主动和被动模式实时收集空口链路质量信息,提出一种MLQMP-BD检测方法,用于实时、准确地测量运营商的无线链路质量,从而优化高清直播视频的传输优化。

During the high-speed movement of high-speed railway,the 3G/4G wireless communication technology based on operators cannot meet the demand of providing high-definition live video services to passengers.Mainly due to the discontinuity of the network coverage quality of the operators along the way,the Doppler effect and the shielding of the vehicle body,etc.,the network is unstable and unpredictable in actual operation,which cannot meet the needs of real-time video services.Therefore,based on the big data deep learning technology,combined with active and passive modes to collect air interface link quality information in real time,an MLQMP-BD detection method is proposed to measure the operator s wireless link quality in real time and accurately,thereby optimizing optimized transmission of HD live video.