University of Oulu

M. Mozaffari, A. Taleb Zadeh Kasgari, W. Saad, M. Bennis and M. Debbah, "Beyond 5G With UAVs: Foundations of a 3D Wireless Cellular Network," in IEEE Transactions on Wireless Communications, vol. 18, no. 1, pp. 357-372, Jan. 2019. doi: 10.1109/TWC.2018.2879940

Beyond 5G with UAVs : foundations of a 3D wireless cellular network

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Author: Mozaffari, Mohammad1,2; Kasgari, Ali Taleb Zadeh3; Saad, Walid3;
Organizations: 1Wireless@VT Research Group, Electrical and Computer Engineering Department, Virginia Tech, Blacksburg, VA 24061 USA
2Ericsson Research, Santa Clara, CA 95054 USA
3ireless@VT Research Group, Electrical and Computer Engineering Department, Virginia Tech, Blacksburg, VA 24061 USA
4Centre for Wireless Communications, University of Oulu, 90014 Oulu, Finland
5Mathematical and Algorithmic Sciences Laboratory, Huawei France R&D, 92100 Paris, France
6CentraleSupèlec, Universitè Paris-Saclay, 91190 Gif-sur-Yvette, France
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.4 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2019
Publish Date: 2019-05-24


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 and 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, which ensures full coverage for a given space with a 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 an optimal transport theory. The simulation results show that the proposed approach reduces the latency of drone-UEs compared with 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 with 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.

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Series: IEEE transactions on wireless communications
ISSN: 1536-1276
ISSN-E: 1558-2248
ISSN-L: 1536-1276
Volume: 18
Issue: 1
Pages: 357 - 372
DOI: 10.1109/TWC.2018.2879940
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This work was supported in part by the Army Research Office (ARO) under Grant W911NF-17-1-0593 and in part by the US NSF under Grants AST-1506297 and CNS-1739642. The work of M. Bennis was supported in part by the Academy of Finland project CARMA, in part by the INFOTECH project NOOR, and in part by the Academy of Finland project SMARTER.
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