Abstract
Paving the path toward the fifth generation (5G) of wireless networks with a huge increase in the number of user equipment has strengthened public concerns on human exposure to radio-frequency electromagnetic fields (RF EMFs). This requires an assessment and monitoring of RF EMF exposure, in an almost continuous way. Particular interest goes to the uplink (UL) exposure, assessed through the transmission power of the mobile phone, due to its close proximity to the human body. However, the UL transmit (TX) power is not provided by the off-the-shelf modem and RF devices. In this context, we first conduct measurement campaigns in a multi-floor indoor environment using a drive test solution to record both downlink (DL) and UL connection parameters for Long Term Evolution (LTE) networks. Several usage services (including WhatsApp voice calls, WhatsApp video calls, and file uploading) are investigated in the measurement campaigns. Then, we propose an artificial neural network (ANN) model to estimate the UL TX power, by exploiting easily available parameters such as the DL connection indicators and the information related to an indoor environment. With those easy-accessed input features, the proposed ANN model is able to obtain an accurate estimation of UL TX power with a mean absolute error (MAE) of 1.487 dB.
Highlights
Human exposure to radiofrequency electromagnetic field (RF-EMF) has been addressed and monitored over the years, especially with the succession of generations of cellular networks, the massive deployment of base stations, and the exponential increase in the number of RF devices
This may be due to the fact that the main gain of the active antenna base station is directed toward floor 5
The reference signal received power (RSRP) values on floor 6 are higher than the others due to a glass window on the roof, which permits to pass more of electromagnetic waves
Summary
Human exposure to radiofrequency electromagnetic field (RF-EMF) has been addressed and monitored over the years, especially with the succession of generations of cellular networks, the massive deployment of base stations, and the exponential increase in the number of RF devices (including connected objects of the Internet of Things IoT). Uplink (UL) exposure induced by a user equipment (UE), together with the DL exposure, could be evaluated by using network-based tools that allow recording a huge amount of data related to, e.g., number of connected UEs, UE transmit (TX) power, UE received power, and throughput [7,8,9,10,11] These data are just accessible to the network operator. A specific equipment (i.e., OPTis-P8E, Innowireless Co., Ltd.) with a control software is used for the recording of both DL and UL EMF exposure, even in fifth generation (5G) new radio environment [17, 18]
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