Designing MIMO interference alignment networks

dc.contributor.advisorHeath, Robert W., Ph. D.en
dc.contributor.advisorAndrews, Jeffrey G.en
dc.contributor.committeeMemberEvans, Brian L.en
dc.contributor.committeeMemberHasenbein, Johnen
dc.contributor.committeeMemberNettles, Scotten
dc.contributor.committeeMemberVishwanath, Sriramen
dc.creatorNosrat Makouei, Behrangen
dc.date.accessioned2012-10-25T20:49:13Zen
dc.date.accessioned2017-05-11T22:29:05Z
dc.date.available2012-10-25T20:49:13Zen
dc.date.available2017-05-11T22:29:05Z
dc.date.issued2012-08en
dc.date.submittedAugust 2012en
dc.date.updated2012-10-25T20:50:33Zen
dc.descriptiontexten
dc.description.abstractWireless networks are increasingly interference-limited, which motivates the development of sophisticated interference management techniques. One recently discovered approach is interference alignment, which attains the maximum sum rate scaling (with signal-to-noise ratio) in many network configurations. Interference alignment is not yet well understood from an engineering perspective. Such design considerations include (i) partial rather than complete knowledge of channel state information, (ii) correlated channels, (iii) bursty packet-based network traffic that requires the frequent setup and tear down of sessions, and (iv) the spatial distribution and interaction of transmit/receive pairs. This dissertation aims to establish the benefits and limitations of interference alignment under these four considerations. The first contribution of this dissertation considers an isolated group of transmit/receiver pairs (a cluster) cooperating through interference alignment and derives the signal-to-interference-plus-noise ratio distribution at each receiver for each stream. This distribution is used to compare interference alignment to beamforming and spatial multiplexing (as examples of common transmission techniques) in terms of sum rate to identify potential switching points between them. This dissertation identifies such switching points and provides design recommendations based on severity of the correlation or the channel state information uncertainty. The second contribution considers transmitters that are not associated with any interference alignment cooperating group but want to use the channel. The goal is to retain the benefits of interference alignment amid interference from the out-of-cluster transmitters. This dissertation shows that when the out-of-cluster transmitters have enough antennas, they can access the channel without changing the performance of the interference alignment receivers. Furthermore, optimum transmit filters maximizing the sum rate of the out-of-cluster transmit/receive pairs are derived. When insufficient antennas exist at the out-of-cluster transmitters, several transmit filters that trade off complexity and sum rate performance are presented. The last contribution, in contrast to the first two, takes into account the impact of large scale fading and the spatial distribution of the transmit/receive pairs on interference alignment by deriving the transmission capacity in a decentralized clustered interference alignment network. Channel state information uncertainty and feedback overhead are considered and the optimum training period is derived. Transmission capacity of interference alignment is compared to spatial multiplexing to highlight the tradeoff between channel estimation accuracy and the inter-cluster interference; the closer the nodes to each other, the higher the channel estimation accuracy and the inter-cluster interference.en
dc.description.departmentElectrical and Computer Engineeringen
dc.format.mimetypeapplication/pdfen
dc.identifier.slug2152/ETD-UT-2012-08-6083en
dc.identifier.urihttp://hdl.handle.net/2152/ETD-UT-2012-08-6083en
dc.language.isoengen
dc.subjectMIMOen
dc.subjectInterference alignmenten
dc.subjectInterference channelen
dc.subjectEqualizeren
dc.subjectBeamformingen
dc.subjectPrecodingen
dc.subjectWireless networksen
dc.subjectCluster point processen
dc.subjectPoisson point processen
dc.subjectCognitive radioen
dc.subjectGrassmann manifolden
dc.subjectWishart distributionen
dc.subjectTransmission capacityen
dc.subjectOutageen
dc.titleDesigning MIMO interference alignment networksen
dc.type.genrethesisen

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