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AuthorBen Ghorbel, Mahdi
AuthorKhalfi, Bassem
AuthorHamdaoui, Bechir
AuthorGuizani, Mohsen
Available date2016-03-20T11:42:14Z
Publication Date2014
Publication Name2014 IEEE Globecom Workshops, GC Wkshps 2014
CitationBen Ghorbel, M., Khalfi, B., Hamdaoui, B., Guizani, M. "Resources allocation for large-scale dynamic spectrum access system using particle filtering" (2014) 2014 IEEE Globecom Workshops, GC Wkshps 2014, art. no. 7063434, pp. 219-224.
ISBN9.78E+12
URIhttp://dx.doi.org/10.1109/GLOCOMW.2014.7063434
URIhttp://hdl.handle.net/10576/4254
AbstractThis paper proposes an efficient spectrum and power allocation solution for a large scale dynamic spectrum access (DSA) systems. Unlike conventional methods relying on optimization techniques which need huge computational capabilities and full information exchange, in this paper we rely on particle filtering to allocate the available bands among users in a distributed manner. Particle filter is based on the representation of the searched state, bands allocation per user in our case, by a set of particles. The Particle filter has the advantage, with comparison to Kalman-based filters, of its adaptivity to general scenarios (non-linear models, non-Gaussian noise, multi-modal distributions). Like Kalman-based filters, two model equations are needed for particle filter, (i) A state evolution equation to characterize the time evolution of the state. For our case, we derive a prediction equation of the channel allocation from the previous allocation from the channel fading temporal correlation, (ii) An observation equation which relates the observation, the Quality of Service in our case, to the channel allocation (state). This equation will be useful in the weighting and re-sampling phases of the filtering algorithm. The performances are analyzed in terms of the per user achieved throughput. In addition, comparison with performance when Q-learning is employed to show the efficiency of our approach.
SponsorNPRP grant #NPRP 5- 319-2-121 from the Qatar National Research Fund (a member of Qatar Foundation).
Languageen
PublisherIEEE
SubjectDistributed algorithms
SubjectDynamic spectrum access
SubjectEfficient spectrum allocation
SubjectLarge-scale systems
SubjectParticle filtering
TitleResources allocation for large-scale dynamic spectrum access system using particle filtering
TypeConference Paper
Pagination219-224


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