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  •   University of Thessaly Institutional Repository
  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
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  •   University of Thessaly Institutional Repository
  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ.
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Multi-RAT spectrum reallocation including carrier aggregation for 5G networks

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Author
Galanopoulos A., Foukalas F., Xenakis A.
Date
2018
Language
en
DOI
10.1145/3291533.3291539
Keyword
Global system for mobile communications
Informatics
Queueing networks
Rats
Resource allocation
Application scenario
Carrier aggregations
Enabling technologies
Joint coordination
Performance requirements
Radio access technologies
Re-farming
Spectrum reallocation
5G mobile communication systems
Association for Computing Machinery
Metadata display
Abstract
Towards the 5G vision of massive access exploding the growth in data traffic, spectrum refarming and reallocation are considered key enabling technologies. Using spectrum reallocation (SR) with the spectrum originally assigned to a Radio Access Technology (RAT) and the the remaining to use spectrum reallocation in the context of multi-RATs (m-RAT). For example, GSM, HSPA and UMTS technologies to be underutilized due to the migration of subscribers to 4G networks are considered in the m-RAT application scenario. To this end, efforts are made in order to deploy m-RAT systems, where the spectrum assigned to m-RATs can be efficiently redistributed and utilized by the involved RATs. In this work, we assume a HSPA/LTE-A m-RAT that provide Carrier Aggregation (CA) too, and propose specific functionality in order to coordinate the operation of both RATs regarding the spectrum assignment and resource allocation. Results show that by assigning spectrum to cover a minimum performance requirement for HSPA, there is a significant performance improvement for LTE-A. Moreover, when spectrum assignment is performed jointly with resource allocation between the involved RATs, the throughput results are higher for both HSPA and LTE-A users. © 2018 Association for Computing Machinery.
URI
http://hdl.handle.net/11615/71920
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