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Fairness and User Assignment in Cloud-RAN
KTH, School of Electrical Engineering (EES), Information Science and Engineering. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Information Science and Engineering. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Information Science and Engineering. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
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2017 (English)In: 2017 IEEE 86TH VEHICULAR TECHNOLOGY CONFERENCE (VTC-FALL), 2017Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we extend our previous work on user assignment in Cloud-RAN, where we proposed an algorithm for user assignment (UA). We motivate the inherent fairness issue that is present in the latter UA scheme, since some users in the system will never get served. To improve the fairness, we propose that the UA scheme is preceded by a user scheduling step which aims at selecting at any time the users that should be considered by the UA algorithm for scheduling (in the next time slot). Two user scheduling approaches have been studied. The first scheme improves the minimum throughput (MT), by selecting at any time the users with the lowest throughput. The second scheme is based on round-robin (RR) scheduling, where the set of potentially scheduled users for the next slot, is done by excluding all the previously served users, in that round. Moreover, the subset of actual users to be served, is determined using the UA algorithm. We evaluate their fairness and sumrate performance, via extensive simulations. While one might have expected a tradeoff between the sum-rate performance and fairness, our results show that MT improves both metrics, when compared to the original UA algorithm (without fairness), for some choice of parameter values. This implies that both fairness and aggregate system performance can be improved, by a careful choice of the number of assigned and served users.

Place, publisher, year, edition, pages
2017.
National Category
Engineering and Technology
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-223415ISI: 000428141600171Scopus ID: 2-s2.0-85045234015OAI: oai:DiVA.org:kth-223415DiVA, id: diva2:1184295
Conference
IEEE Vehicular Technology Conference (VTC Fall 2017)
Note

QC 20180327

Available from: 2018-02-21 Created: 2018-02-21 Last updated: 2018-05-08Bibliographically approved

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fulltext(186 kB)5 downloads
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