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" Transmit Precoding and Bayesian Detection for Cognitive Radio Networks with Limited Channel State Information "
Mohannad Hamed Al-Ali
Ho, Dominic K. C.
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Latin Dissertation
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| Language of Document
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English
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| Record Number
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805140
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| Doc. No
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TL49989
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| Call number
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2153769939; 11012689
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| Main Entry
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Alkhanbooli, Badreyya
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| Title & Author
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Transmit Precoding and Bayesian Detection for Cognitive Radio Networks with Limited Channel State Information\ Mohannad Hamed Al-AliHo, Dominic K. C.
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| College
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University of Missouri - Columbia
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| Date
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2017
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| Degree
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Ph.D.
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| field of study
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Electrical Engineering and Computer Science Department
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| student score
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2017
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| Page No
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160
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| Note
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Committee members: Ho, Dominic K. C.; Islam, Naz; Legarsky, Justin; Micheas, Athanasios C.
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| Note
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Place of publication: United States, Ann Arbor; ISBN=978-0-438-66319-0
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| Abstract
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Cognitive radio (CR) represents a recent direction for enabling coexistence among heterogeneous networks. It can be a potential solution for the problem of scarce spectrum available for wireless communication systems. The study here investigates the underlay and interweave paradigms for the coexistence of CR network of secondary users (SUs) with a primary network of primary users (PUs). Under underlay mode, both networks communicates concurrently using the same resources. With interweave, SU is able to communicate as long as (some) PUs are not active. Usually, underlay or interweave employs multiple antennas at SU to use the spectral resources better and manage the interference towards the primary network. Performance of the CR network under either paradigm depends largely on the amount and quality of channel state information (CSI) available about the different communication links. In practical systems, often CSI at SU has uncertainty since it is deviated from the true one or is not known at all. This uncertainty should be accounted when designing the precoding schemes for SU or otherwise the interference impact on primary networks would violate the quality of service (QoS) requirements for PUs. This dissertation considers two cases regarding to the availability of CSI, the first one is when CSI is imperfect and the second is when CSI is completely not known.
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| Subject
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Electrical engineering
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| Descriptor
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Applied sciences;Bayesian detection;Cognitive radio;Convex optimization;Lagrange duality;Maximin;Multiple-input multiple-output
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| Added Entry
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Ho, Dominic K. C.
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Electrical Engineering and Computer Science DepartmentUniversity of Missouri - Columbia
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