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UID:518@lincs.fr
DTSTART;TZID=Europe/Paris:20200312T140000
DTEND;TZID=Europe/Paris:20200312T160000
DTSTAMP:20200312T165614Z
URL:https://www.lincs.fr/events/thesis-defense-resource-allocation-and-opt
 imization-for-the-non-orthogonal-multiple-access/
SUMMARY:Thesis Defense : Resource allocation and optimization for the
 non-orthogonal multiple access
DESCRIPTION:Non-orthogonal multiple access (NOMA) is a promising technology
 to increase the spectral efficiency and enable massive connectivity in
 future wireless networks. In contrast to orthogonal schemes\, such as
 OFDMA\, NOMA can serve multiple users on the same frequency and time
 resource by superposing their signal in the power domain. One of the key
 challenges for radio resource management (RRM) in NOMA systems is to solve
 the joint subcarrier and power allocation (JSPA) problem.\nIn this thesis\,
 we present a novel optimization framework to study a general class of JSPA
 problems. This framework employs a generic objective function which can be
 used to represent the popular weighted sum-rate (WSR)\, proportional
 fairness\, harmonic mean and max-min fairness utilities. Our work also
 integrates various realistic constraints. We prove under this framework
 that JSPA is NP-hard to solve in general. In addition\, we study its
 computational complexity and approximability in various special cases\, for
 different objective functions and constraints.\nIn this framework\, we
 first consider the WSR maximization problem subject to cellular power
 constraint. We propose three new algorithms: Opt-JSPA computes an optimal
 solution with lower complexity than current optimal schemes in the
 literature. It can be used as an optimal benchmark in simulations.
 However\, its pseudo-polynomial time complexity remains impractical for
 real-world systems with low latency requirements. To further reduce the
 complexity\, we propose a fully polynomial-time approximation scheme called
 &#400\;-JSPA\, which allows tight trade-offs between performance guarantee
 and complexity. To the best of our knowledge\, &#400\;-JSPA is the first
 polynomial-time approximation scheme proposed for this problem. Finally\,
 Grad-JSPA is a heuristic based on gradient descent. Numerical results show
 that it achieves near-optimal WSR with much lower complexity than existing
 optimal methods.\nAs a second application of our framework\, we study
 individual power constraints. Power control is solved optimally by gradient
 descent methods. Then\, we develop three heuristics: DGA\, DPGA and DIWA\,
 which solve the JSPA problem for centralized and distributed settings.
 Their performance and computational complexity are compared through
 simulations.\n\nKeywords : NOMA\, SIC\, resource allocation\, convex and
 combinatorial optimization\n\nTitre : Allocation des ressources et
 optimisation pour l’accès multiple non-orthogonal
CATEGORIES:PhD Defense,Youtube
LOCATION:Paris-Rennes Room (EIT Digital)\, 23 avenue d'Italie\, 75013
 Paris\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=23 avenue d'Italie\, 75013
 Paris\, France;X-APPLE-RADIUS=100;X-TITLE=Paris-Rennes Room (EIT
 Digital):geo:0,0
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TZID:Europe/Paris
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DTSTART:20191027T020000
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