Self-Organizing Flying Drones with Massive MIMO Networking
This article studies distributed algorithms to con-trol self-organizing swarm drone hotspots with massive MIMO networking capabilities- A network scenario referred to as OrgSwarm. We attempt to answer the following fundamental question: What is the optimal way to provide spectrally-efficient wireless access to a multitude of ground nodes with mobile base stations/aerial relays mounted on a swarm of drones and endowed with a large number of antennas; when we can control the position of many-antenna-enabled drones, access association of ground nodes to drones, and the transmit power of ground nodes? The article first derives a mathematical formulation of the problem of spectral efficiency maximization through joint control of the movement of many-antenna-enabled aerial drones, access association of single-antenna ground nodes to many-antenna drones, and transmit power of ground nodes. It is shown that the resulting network control problem is a mixed integer nonlinear nonconvex programming problem (MINLP). We then first design a distributed solution algorithm with polynomial computational complexity. Then, a centralized but globally optimal solution algorithm is designed based on a combination of the branch and bound framework and convex relaxation techniques to provide a performance benchmark for the distributed algorithm. Results indicate that the distributed algorithm achieves a network spectral efficiency very close (over 95% on average) to the global optimum.
Z. Guan et al., "Self-Organizing Flying Drones with Massive MIMO Networking," Proceedings of the 17th Annual Mediterranean Ad Hoc Networking Workshop (2018, Capri, Italy ), pp. 1-8, Institute of Electrical and Electronics Engineers (IEEE), Jun 2018.
The definitive version is available at https://doi.org/10.23919/MedHocNet.2018.8407088
17th Annual Mediterranean Ad Hoc Networking Workshop, Med-Hoc-Net 2018 (2018: Jun. 20-22, Capri, Italy )
Keywords and Phrases
Ad Hoc Networks; Aircraft Control; Antennas; Benchmarking; Efficiency; Integer Programming; Polynomials; Relaxation Processes, Convex Relaxation; Distributed Solutions; Mathematical Formulation; Mobile Base Station; Non-Convex Programming; Optimal Solutions; Spectral Efficiencies; Spectral Efficiency Maximizations, Drones
International Standard Book Number (ISBN)
Article - Conference proceedings
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01 Jun 2018