基于改进卷积神经网络的可见光通信系统信道估计方法
Channel estimation method of visible optical communication system based on improved convolutional neural network
赵小强1
作者信息
- 1. 郑州工业应用技术学院信息工程学院,河南新郑 451100
- 折叠
摘要
为了提升可见光通信系统的通信质量,开展了基于改进卷积神经网络的可见光通信系统信道估计方法研究.首先,建立可见光通信系统信道模型,获取信道增益、LED限制带宽、频域响应的模等参数.其次,从可见光通信系统导频分布与导频间隔两个维度,设计系统导频结构,准确得出系统发送端想要传输的信道信息.利用改进卷积神经网络,开展可见光通信系统信道估计,求解信道估计结果.实验结果表明,该方法的信道估计误码率不存在大幅度波动,最高不超过0.5％,信道传输效果较好.
Abstract
In order to improve the communication quality of visible optical communication sys-tem,reduce the number of error codes generated by signal damage,improve the accuracy of channel estimation,optimize the channel transmission effect of the system channel,the im-proved convolutional neural network is introduced,and the channel estimation method of visi-ble optical communication system based on improved convolutional neural network is studied.First,the channel model of visible optical communication system is established to obtain param-eters such as channel gain,LED limit bandwidth and mode of frequency domain response.Sec-ondly,the pilot structure of the pilot distribution and the pilot interval of the visible optical communication system is designed to accurately obtain the channel information of the transmit-ting end of the system.On this basis,the improved convolutional neural network is used to de-velop the channel estimation of the visible light communication system and solve the channel es-timation results.The experimental analysis results show that after the proposed channel estima-tion method,the channel estimation error rate does not fluctuate greatly,the highest does not exceed 0.5％,the channel transmission effect is good,the estimation accuracy and the commu-nication quality level of visible optical communication system are significantly improved.
关键词
改进卷积神经网络/可见光通信系统/方法/信道/误码率Key words
improving convolutional neural network/estimation/visible optical communica-tion system/method/channel/bit error rate引用本文复制引用
基金项目
河南省科学技术厅(省级)(172102210169)
出版年
2024
NETL
NSTL
万方数据