摘要
针对目前数字广播电视单频网不能自动进行覆盖结果优化调整的问题,该文在基于地理信息的单频网台站场强预测的基础上,实现了单频网覆盖时延自动优化。首先,利用台站基本信息,结合地理信息,利用台站场强预测模型,对单频网内各个台站进行覆盖场强预测,得到各个台站的覆盖结果矩阵。其次,结合各个台站的覆盖结果矩阵,利用遗传算法对各个台站的时延情况进行寻优。最后,得到每个台站的最优时延结果,以及得到时延优化后的单频网覆盖结果。实验结果表明,本文提出的基于遗传算法的单频网覆盖时延优化算法,能够很好地实现单频网内各个台站的自动时延优化,根据得到的时延结果,对单频网内各台站信号进行控制,从而自动地进行单频网覆盖结果的优化。
Aiming at the problem that the current digital broadcasting-TV SFN could not automatically adjust the coverage result,this paper proposed a SFN delay optimization algorithm based on geneticalgorithm,which was based on the field-strength prediction of SFN-stations and the geographic information.Firstly,using the basic information of the stations,combined with the geographic information,using the field-strength prediction model of the stations,do the prediction of field-strength for each station in the SFN,and the coverage result matrix of each station is obtained.Secondly,combined with the coverage-result-matrix of each station,the genetic algorithm was used to optimize the delay of each station.Finally,the optimal delay results of each station was obtained,and the SFN coverage-results after the optimization was obtained.The experimental results showed that the SFN coverage-delay optimization algorithm based on genetic algorithm could realize the automatic delay optimization of each station in the SFN.Based on the delay result did the signal control of each station in the SFN.Finally the automatic optimization on the coverage result of SFN was realized.
作者
贺鹏艳
HE Pengyan(ZCGK Surveying Engineering Technology Co.,Ltd.,Beijing 100041,China)
出处
《测绘科学》
CSCD
北大核心
2019年第6期341-346,共6页
Science of Surveying and Mapping
关键词
台站覆盖
单频网
遗传算法
时延优化
station coverage
SFN
genetic algorithm
delay optimization
