Power Reduction Estimation of 5G Active Antenna Systems for Human Exposure Assessment in Realistic Scenarios

Abstract

Maximum power extrapolation techniques from measured data are usually employed to assess the compliance with standards of average fields radiated by base stations. However, such techniques provide an upper bound, which is not reached in real scenarios. This is particularly true in 5G Communications, where Active Antenna Systems allow a decrease of the average power density according to the adopted scheduling strategy. This paper is focused on the power reduction estimation in realistic scenarios. In particular a deterministic model of a communication system is used to obtain simple formulas only requiring the knowledge of the served area angular extension and of the Envelope Radiation Pattern of the antenna. The model, developed for beam steering and grid of beams antennas, is also extended to analyze the case of Multi User massive Multiple Input Multiple Output (MU-mMIMO) antennas with single layer per user, showing that under proper hypothesis on the beams of the antenna it is possible to estimate the reduction parameter without the explicit knowledge of the number of layers of MU-mMIMO systems. In spite of the simplicity of the approach, comparison with stochastic models and results reported in recent literature show that the formulas obtained using the model proposed in this paper allow to obtain a useful approximation of the power reduction factor, making the formulas suitable for a preliminary fast estimation of the Electromagnetic Field in 5G cells for human exposure assessment.