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. For that purpose, we propose two schemes to be used in conjunction with aforementioned UA scheme, to improve its fairness. The first scheme aims at improving the minimum throughput (MT), by selecting users with lowest throughput, as input to the UA algorithm, and to be (potentially) scheduled in the next time slot. 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 sum-rate performance, via extensive simulations. While one might have expected a tradeoff between the sum-rate performance and fairness, our results showed that MT improves both metric, when compared to the original UA algorithm (without fairness), for some choice of parameter values.
Fairness and User Assignment in Cloud-RAN
2017-09-01
181139 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Taylor & Francis Verlag | 2023
|Kraftfahrwesen | 1994
|Kraftfahrwesen | 1994