Beyond 5G with UAVs: Foundations of a 3D Wireless Cellular Network

TL;DR

This paper introduces a comprehensive 3D cellular network framework integrating drone base stations and users, proposing novel deployment, frequency planning, and latency-minimizing cell association methods to enhance coverage and efficiency.

Contribution

It presents new deployment strategies, frequency reuse analysis, and a latency-minimal cell association scheme for 3D drone-based cellular networks, advancing beyond traditional 2D architectures.

Findings

Up to 46% latency reduction with the proposed cell association.

Efficient drone-BS deployment using truncated octahedron shapes.

Improved spectral efficiency in 3D drone networks.

Abstract

In this paper, a novel concept of three-dimensional (3D) cellular networks, that integrate drone base stations (drone-BS) and cellular-connected drone users (drone-UEs), is introduced. For this new 3D cellular architecture, a novel framework for network planning for drone-BSs as well as latency-minimal cell association for drone-UEs is proposed. For network planning, a tractable method for drone-BSs' deployment based on the notion of truncated octahedron shapes is proposed that ensures full coverage for a given space with minimum number of drone-BSs. In addition, to characterize frequency planning in such 3D wireless networks, an analytical expression for the feasible integer frequency reuse factors is derived. Subsequently, an optimal 3D cell association scheme is developed for which the drone-UEs' latency, considering transmission, computation, and backhaul delays, is minimized. To this end, first, the spatial distribution of the drone-UEs is estimated using a kernel density estimation method, and the parameters of the estimator are obtained using a cross-validation method. Then, according to the spatial distribution of drone-UEs and the locations of drone-BSs, the latency-minimal 3D cell association for drone-UEs is derived by exploiting tools from optimal transport theory. Simulation results show that the proposed approach reduces the latency of drone-UEs compared to the classical cell association approach that uses a signal-to-interference-plus-noise ratio (SINR) criterion. In particular, the proposed approach yields a reduction of up to 46% in the average latency compared to the SINR-based association. The results also show that the proposed latency-optimal cell association improves the spectral efficiency of a 3D wireless cellular network of drones.