%0 Conference Proceedings
%T Self-Organizing Flying Drones with Massive MIMO Networking
%+ Dept. of Electrical and Computer Engineering [Northeastern]
%+ Air Force Research Laboratory (AFRL)
%A Guan, Zhangyu
%A Cen, Nan
%A Melodia, Tommaso
%A Pudlewski, Scott
%< avec comité de lecture
%B 17th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net 2018)
%C Capri Island, Italy
%Y Luigi Paura
%Y Sergio Palazzo
%3 Annual Mediterranean Ad Hoc Networking Workshop
%V IFIP eCollection-2
%P 15-22
%8 2018-06-20
%D 2018
%Z Computer Science [cs]Conference papers
%X This article studies distributed algorithms to control self-organizing swarm drone hotspots with massive MIMOnetworking capabilities - a network scenario referred to asOrgSwarm. We attempt to answer the following fundamentalquestion: what is the optimal way to provide spectrally-efficientwireless access to a multitude of ground nodes with mobile basestations/aerial relays mounted on a swarm of drones and endowedwith a large number of antennas; when we can control the positionof many-antenna-enabled drones, access association of groundnodes to drones, and the transmit power of ground nodes?The article first derives a mathematical formulation of theproblem of spectral efficiency maximization through joint controlof the movement of many-antenna-enabled aerial drones, accessassociation of single-antenna ground nodes to many-antennadrones, and transmit power of ground nodes. It is shown that theresulting network control problem is a mixed integer nonlinearnonconvex programming problem (MINLP). We then first designa distributed solution algorithm with polynomial computationalcomplexity. Then, a centralized but globally optimal solutionalgorithm is designed based on a combination of the branchand bound framework and convex relaxation techniques toprovide a performance benchmark for the distributed algorithm.Results indicate that the distributed algorithm achieves a networkspectral efficiency very close (over 95% on average) to the globaloptimum.
%G English
%Z TC6
%Z WG 6.8
%2 https://inria.hal.science/hal-01832485/document
%2 https://inria.hal.science/hal-01832485/file/paper03.pdf
%L hal-01832485
%U https://inria.hal.science/hal-01832485
%~ IFIP
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC6
%~ IFIP-WG6-8
%~ IFIP-MED-HOC-NET-2018
%~ IFIP-MED-HOC-NET