Analysis of millimeter wave ad hoc networks

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dc.contributor.advisorHeath, Robert W., Jr, 1973-
dc.contributor.committeeMemberAndrews, Jeffrey
dc.contributor.committeeMemberBaccelli, Francois
dc.contributor.committeeMemberHasenbein, John
dc.contributor.committeeMemberde Veciana, Gustavo
dc.creatorThornburg, Andrew Scott
dc.date.accessioned2018-01-31T20:25:45Z
dc.date.available2018-01-31T20:25:45Z
dc.date.created2017-12
dc.date.issued2018-01-23
dc.date.submittedDecember 2017
dc.date.updated2018-01-31T20:25:45Z
dc.description.abstractOver the coming few years, the next-generation of wireless networks will be standardized and defined. Ad hoc networks, which operate without expensive infrastructure, are desirable for use cases such as military networks or disaster relief. Millimeter wave (mmWave) technology may enable high speed ad hoc networks. Directional antennas and building blockage limit the received interference power while the huge bandwidth enables high data rates. For this reason, understanding the interference and network performance of mmWave ad hoc networks is crucial for next-generation network design. In my first contribution, I derive the SINR complementary cumulative distribution function (CCDF) for a random single-hop mmWave ad hoc network. These base results are used to further give insights in mmWave ad hoc networks. The SINR distribution is used to compute the transmission capacity of a mmWave ad hoc network using a Taylor bound. The CDF of the interference to noise ratio (INR) is also derived which shows that mmWave ad hoc networks are line-of-sight interference limited. I extend my work in the second contribution to include general clustered Poisson point processes to derive insights in the effect of different spatial interference patterns. Using the developed framework, I derive the ergodic rate of both spatially uniform and cluster mmWave ad hoc networks. I develop scaling trends for the antenna array size to keep the ergodic rate constant. The impact of beam alignment is computed in the final part of the contribution. Finally, I account for the overhead of beam alignment in mmWave ad hoc networks. The final contribution leverages the first two contributions to derive the expected training time a mmWave ad hoc network must perform before data transmission occurs. The results show that the optimal conditions for minimizing the training time are different than the optimal conditions for maximizing rate.
dc.description.departmentElectrical and Computer Engineering
dc.format.mimetypeapplication/pdf
dc.identifierdoi:10.15781/T20000G9P
dc.identifier.urihttp://hdl.handle.net/2152/63369
dc.language.isoen
dc.subjectWireless communication
dc.subject5G networks
dc.subjectStochastic geometry
dc.titleAnalysis of millimeter wave ad hoc networks
dc.typeThesis
dc.type.materialtext
thesis.degree.departmentElectrical and Computer Engineering
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorThe University of Texas at Austin
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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