Methodology Based on Vector and Scalar Measurement of Traffic Channel Power Levels to Assess Maximum Exposure to Electromagnetic Radiation Generated by 5G NR Systems

Maximum-Power Extrapolation (MPE) for mobile telecommunication sources follows an established paradigm based on the identification and measurement of a channel that acts as a power reference. Prior to the 5G era, the role of reference channel has been played by always-on broadcast signals since they had the great advantage of being always transmitted at the maximum power level allowed for a generic signal channel. However, the beamforming implemented by 5G sources obliges us to rethink this approach. In fact, with beamforming the 5G source can transmit data traffic streams through a beam characterized by a much higher gain than the broadcast one. This implies that the detected power for traffic beams could be much higher than the corresponding power of broadcast beams. In this paper, a novel approach for 5G MPE procedure is presented, where the direct measurement of the received power of a traffic beam is used to assess the maximum exposure generated by a 5G system. An innovative specific experimental setup is also proposed, with the use of a User Equipment (UE) with the aim of forcing the traffic beam toward the measurement positions. In this way, it is possible to directly measure the power of each Resource Element (RE) transmitted by the traffic beam. As opposed to other MPE proposals for 5G, the discussed technique does not require any correction of the measured data since it relies only on the traffic beam pointing toward the measurement position, simplifying the overall MPE procedure and thus reducing the uncertainty of the MPE estimated field strength

An integrated approach to monitoring the calibration stability of operational dual-polarization radars

The stability of weather radar calibration is a mandatory aspect for quantitative applications, such as rainfall estimation, short-term weather prediction and initialization of numerical atmospheric and hydrological models. Over the years, calibration monitoring techniques based on external sources have been developed, specifically calibration using the Sun and calibration based on ground clutter returns. In this paper, these two techniques are integrated and complemented with a self-consistency procedure and an intercalibration technique. The aim of the integrated approach is to implement a robust method for online monitoring, able to detect significant changes in the radar calibration. The physical consistency of polarimetric radar observables is exploited using the self-consistency approach, based on the expected correspondence between dual-polarization power and phase measurements in rain. This technique allows a reference absolute value to be provided for the radar calibration, from which eventual deviations may be detected using the other procedures. In particular, the ground clutter calibration is implemented on both polarization channels (horizontal and vertical) for each radar scan, allowing the polarimetric variables to be monitored and hardware failures to promptly be recognized. The Sun calibration allows monitoring the calibration and sensitivity of the radar receiver, in addition to the antenna pointing accuracy. It is applied using observations collected during the standard operational scans but requires long integration times (several days) in order to accumulate a sufficient amount of useful data. Finally, an intercalibration technique is developed and performed to compare colocated measurements collected in rain by two radars in overlapping regions. The integrated approach is performed on the C-band weather radar network in northwestern Italy, during July–October 2014. The set of methods considered appears suitable to establish an online tool to monitor the stability of the radar calibration with an accuracy of about 2 dB. This is considered adequate to automatically detect any unexpected change in the radar system requiring further data analysis or on-site measurements