Performance modeling of camera-assisted proactive base station selection for human blockage problem in mmWave communications

In millimeter wave (mmWave) communications, when a pedestrian blocks the path of the line of sight (LOS) between a station (STA) and a base station (BS), the quality of communication sharply deteriorates. In order to cope with such human blockage, an RGB and depth (RGB-D) camera-assisted proactive handover scheme is proposed in this paper. The scheme uses images from an RGB-D camera to predict human blockage, and allows the selection of an appropriate BS based on this prediction. To clarify the impact of the accuracy of blockage prediction on throughput performance and assess the ideal performance of the proposed scheme, we propose the performance modeling of both proactive and reactive handover schemes based on the received power level. Numerical evaluation results revealed conditions under which the proactive handover scheme yields higher spectral efficiency than the reactive scheme. We conducted simulations to verify the performance gain of the proposed scheme in a realistic scenario where the LOS paths between a mobile STA and the BS were stochastically blocked. The results show that the proactive handover scheme can reduce the duration of outages due to human blockage, and increased system throughput by 12.1% over the reactive handover scheme.

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