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dc.contributor.advisorHeath, Robert W., Jr, 1973-
dc.creatorEl Ayach, Omaren
dc.date.accessioned2013-10-24T17:31:53Zen
dc.date.issued2013-05en
dc.date.submittedMay 2013en
dc.identifier.urihttp://hdl.handle.net/2152/21720en
dc.descriptiontexten
dc.description.abstractWireless systems in which multiple users simultaneously access the propagation medium suffer from co-channel interference. Untreated interference limits the total amount of data that can be communicated reliably across the wireless links. If interfering users allocate a portion of the system's resources for information exchange and coordination, the effect of interference can be mitigated. Interference alignment (IA) is an example of a cooperative signaling strategy that alleviates the problem of co-channel interference and promises large gains in spectral efficiency. To enable alignment in practical wireless systems, channel state information (CSI) must be shared both efficiently and accurately. In this dissertation, I develop low-overhead CSI feedback strategies that help networks realize the information-theoretic performance of IA and facilitate its adoption in practical systems. The developed strategies leverage the concepts of analog, digital, and differential feedback to provide IA networks with significantly more accurate and affordable CSI when compared to existing solutions. In my first contribution, I develop an analog feedback strategy to enable IA in multiple antenna systems; multiple antennas are one of IA's key enabling technologies and perhaps the most promising IA use case. In my second contribution, I leverage temporal correlation to improve CSI quantization in limited feedback single-antenna systems. The Grassmannian differential strategy developed provides several orders of magnitude in CSI compression and ensures almost-perfect IA performance in various fading scenarios. In my final contribution, I complete my practical treatment of IA by revisiting its performance when CSI acquisition overhead is explicitly accounted for. This last contribution settles the viability of IA, from a CSI acquisition perspective, and demonstrates the utility of the proposed feedback strategies in transitioning interference alignment from theory to practice.en
dc.format.mimetypeapplication/pdfen
dc.language.isoen_USen
dc.subjectWirelessen
dc.subjectCommunicationsen
dc.subjectMultiple antennasen
dc.subjectMIMOen
dc.subjectInterferenceen
dc.subjectInterference managementen
dc.subjectCoordinationen
dc.subjectFeedbacken
dc.subjectChannel state informationen
dc.titleInterference alignment from theory to practiceen
dc.date.updated2013-10-24T17:31:54Zen
dc.description.departmentElectrical and Computer Engineeringen
thesis.degree.departmentElectrical and Computer Engineeringen
thesis.degree.disciplineElectrical and Computer Engineeringen
thesis.degree.grantorThe University of Texas at Austinen
thesis.degree.levelDoctoralen
thesis.degree.nameDoctor of Philosophyen


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