Millimeter-wave transceivers will feature massive phased-array antennas whose pencilbeams can be steered toward the angle of arrival of the propagation path having the maximum power, exploiting their high gain to compensate for the greater path loss witnessed in the upper spectrum. For this reason, maximum-power path-loss models, in contrast to conventional ones based on the integrated power from an omnidirectional antenna, may be more relevant. Yet to our knowledge, they do not appear in the literature save for one reference. In this paper, we compare both model types at 83.5 GHz for four indoor environments typical of hotspot deployments in line-of-sight (LOS) and non-LOS conditions up to a range of 160 m. To fit the models, we conducted a measurement campaign with over 3000 different transmitter–receiver configurations using a custom-designed channel sounder capable of extracting the delay and 3-D angle of arrival of the received paths with super-resolution. The models are supported by a detailed analysis of the propagation mechanisms of direct transmission, reflection, and knife-edge diffraction to shed light on their interplay in the E-band regime.

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In wireless sensor networks, the positioning scheme using the received signal strength (RSS) has been widely considered due to its simplicity. Appropriate estimation of pathloss exponent (PLE) between a sensor node and an anchor node plays a key role in reducing position error in this RSS-based positioning. In the conventional researches, a sensor node directly uses the PLEs given by its neighboring anchor nodes, e.g., its nearest anchor node, to calculate its position. However, the PLE between a sensor node and an anchor node is usually different from those given by the anchor nodes, and accordingly results in the distance error in sensor node's positioning. In this paper, we propose the method how a sensor node estimates PLEs from the anchor nodes of interest by itself and calculates its position based on these self-estimated PLEs. In the proposed scheme, a sensor node recalculates PLEs depending on the estimated distances between itself and anchor nodes, and reproduces its position based on the recalculated PLEs. Through simulations, we show that our proposed positioning scheme outperforms the traditional scheme in terms of position error.