基于烟花算法的煤矿工作面VLC光源高度优化

发布时间：2018-03-31 21:52

  本文选题：可见光通信　切入点：烟花算法　出处：《中国矿业大学学报》2017年05期

【摘要】：针对煤矿工作面可见光通信系统中光源发光二极管(LED)导致接收平面光信号信噪比(SNR)分布不均匀的问题,提出了优化LED光源高度、提高工作面接收平面光信号SNR分布均匀性的新方法.可见光通信中接收点光功率与距离平方成反比,随着通信距离的改变,接收光功率变化明显,应用群体优化算法——烟花算法搜索每个LED光源高度,降低接收平面SNR波动,增加接收平面SNR均值,提高系统整体性能.结果表明:LED光源高度在0.85~3.00m范围内调节时,光接收平面SNR方差由2.16×104降低到1.08×10~4,SNR因子从32.703 4降低到16.678 4,SNR均值从44.967提高到62.390;LED光源高度限制在2.60~3.00m时,光接收平面SNR方差由2.16×104降低到1.61×10~4,SNR因子从32.703 4降低到22.693 1,SNR均值从44.967提高到55.850,有效改进了接收平面SNR均匀性和系统SNR性能.
[Abstract]:Aiming at the problem of uneven distribution of signal to noise ratio (SNR) of received plane light signal in the visible light communication system of coal face, an optimized LED light source height is proposed.A new method to improve the SNR distribution uniformity of the plane light signals received from the working face.The optical power of the receiving point is inversely proportional to the square of the distance in the visible light communication. With the change of the communication distance, the received optical power changes obviously. The group optimization algorithm-fireworks algorithm is applied to search the height of each LED light source to reduce the SNR fluctuation in the receiving plane.Increase the average value of SNR in the receiving plane and improve the overall performance of the system.The results show that when the light source height is adjusted within the range of 0.85 ~ 3.00 m, the variance of SNR in the light receiving plane decreases from 2.16 脳 10 ~ 4 to 1.08 脳 10 ~ (4) SNR from 32.703 4 to 16.678 4 ~ (4). The average value of SNR is increased from 44.967 to 62.390 m, and the height of the light source is limited to 2.60 脳 10 ~ 4 ~ 3.00 m.The SNR variance of the optical receiving plane is reduced from 2.16 脳 10 ~ 4 to 1.61 脳 10 ~ (4) SNR factor from 32.703 ~ (4) to 22.693 ~ (1) ~ 1 ~ (th) SNR from 44.967 to 55.850, which effectively improves the homogeneity of the receiving plane SNR and the SNR performance of the system.
【作者单位】： 中国矿业大学物联网(感知矿山)研究中心;江苏师范大学物理与电子工程学院;
【基金】：江苏省自然科学基金项目(BK20151148) 江苏省科技成果转化专项资金项目(BA2016016) 徐州市科技计划项目(KC14SM097)
【分类号】：TN929.1
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本文编号：1692599