Electromagnetic exposure caused by mobile communication signals has always been a cause of concern. Due to the cost and inconvenience of professional measurement equipment, researchers have turned to smartphone APPs to study and assess the electric field strength caused by mobile communication signals. However, existing cell phone-based measurements have two weaknesses. First, no system architecture suitable for large-scale crowdsourced testing has been proposed. Second, since smartphone sensors cannot measure electric field strength directly, existing methods for converting the received signal power of the phone and electric field strength have errors of more than 5 dB. This paper proposes a measurement and calibration method for electric field strength of mobile communication signals based on a smartphone app and gradient boosting decision tree (GBDT). This method consists of a downlink signal acquisition system based on an APP and a calibration model based on GBDT to convert received signal power into electric field strength. The experimental results show that the proposed model achieves a R² score of 0.93 and a MAE of 0.97 dB. Compared with the existing methods, our method improves the calibration accuracy by 4 dB, enabling large-scale, low-cost, and high-precision direct measurement of the electric field strength of mobile communication signals.

中文翻译：

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EMF 的测量和校准：使用电话和 GBDT 进行移动通信信号的研究

移动通信信号引起的电磁暴露一直是人们关注的焦点。由于专业测量设备的成本和不便，研究人员转向智能手机APP来研究和评估移动通信信号引起的电场强度。然而，现有的基于手机的测量有两个弱点。首先，还没有提出适合大规模众包测试的系统架构。其次，由于智能手机传感器无法直接测量电场强度，现有的手机接收信号功率与电场强度的换算方法存在5dB以上的误差。本文提出了一种基于智能手机应用程序和梯度提升决策树（GBDT）的移动通信信号电场强度测量和校准方法。该方法由基于APP的下行信号采集系统和基于GBDT的校准模型组成，将接收信号功率转换为电场强度。实验结果表明，该模型的R ²得分为0.93，MAE为0.97 dB。与现有方法相比，我们的方法将校准精度提高了4 dB，从而能够大规模、低成本、高精度地直接测量移动通信信号的电场强度。