University of East Sarajevo, Faculty of Electrical Engineering, East Sarajevo 71123, Bosnia and Herzegovina.
University of Belgrade, School of Electrical Engineering, Belgrade 11000, Serbia.
Radiat Prot Dosimetry. 2020 Aug 28;190(2):226-236. doi: 10.1093/rpd/ncaa091.
Since radio frequency (RF) signals from public mobile systems are stochastic and exhibit large temporal variations, the results of measurements, typically E field measurements, are time dependent and highly variable. Therefore, any 6-min measurements and 6-min averaged results to obtain the mean level strength at a given place may not be so reliable when it comes to determine long-term exposure levels. Specifically, the results of such short-term exposure assessments can be both under- or overestimated depending on whether the extreme value is caught during the measurement time. Because the RF range is active 24 h a day, the authors suggest that the monitoring process should cover the same time period. To evaluate the variability of measurement results, the analysis in this paper was conducted through descriptive statistics of the 24-h instantaneous, time-averaged and integral-based values. By applying the 24-h time-averaged and integral-based measure on a 24-h data set of measurements, the variability of daily exposure could be reduced to ±20% of the mean week value obtained either with the time-averaged or integral-based measure.
由于公共移动通信系统的射频（RF）信号是随机的，并表现出较大的时间变化，因此测量结果（通常是电场测量结果）是时间相关的且高度可变的。因此，在确定长期暴露水平时，任何 6 分钟的测量和 6 分钟的平均值结果都可能无法可靠地获得给定地点的平均水平强度。具体而言，根据测量时间是否捕捉到极值，这种短期暴露评估的结果可能会被低估或高估。由于 RF 范围每天 24 小时都处于活动状态，因此作者建议监测过程应涵盖相同的时间段。为了评估测量结果的可变性，本文通过对 24 小时瞬时值、时间平均值和基于积分的值的描述性统计进行了分析。通过将 24 小时时间平均值和基于积分的测量应用于 24 小时测量数据集，每日暴露的可变性可以降低到通过时间平均值或基于积分的测量获得的平均周值的±20%。
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