A Holistic Assessment of Directional Deafness in mmWave-Based Distributed 3D Networks

Abstract

The adoption of abundant millimeter-wave (mmWave) spectrum offers higher capacity for short-range connectivity in various Unmanned Aerial Vehicle (UAV)-centric communications scenarios. In contrast to the conventional cellular paradigm, where the coordination of connected nodes is highly centralized, the distributed deployments, such as those operating over unlicensed frequency bands, maintain robust interactions in the absence of central control. These agile decentralized systems are being naturally created by dynamic UAV swarms that form a temporary 3D structure without reliance on remote management or pre-established network infrastructures. While much effort has been invested in the performance assessment of distributed, directional, and 3D systems individually, a combination of these three angles allows capturing more realistic UAV swarm scenarios and produces a novel research perspective. This work addresses one of the fundamental challenges in mmWave-based 3D networks -directional deafness -which is known to adversely affect the overall system performance. Particularly, we develop a mathematical framework by taking into account the peculiarities of 3D directional and distributed deployments. We provide a holistic analytical assessment of directional deafness and propose several powerful approximations that capture realistic antenna patterns.

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“…We assume that devices transmit directionally with an antenna pattern akin to a conical shape, i.e., with a unique beam shape in both elevation and azimuth planes. To this end, for numerical tractability, we approximate the beamforming design as proposed in [9] with the transmit antenna gain:…”

“…where D 0 is the maximum directivity along the antenna boresight, α is the angular deviation of the transmit/receive direction from the antenna boresight for a receiver, ρ(α) ∈ [0; 1] is a linear function that scales the directivity D 0 [9] , which, in turn, depends on the number of antenna elements, N AE . We adopt the 3GPP urban microcell (UMi) Street Canyon path loss model in [10].…”