A QoE-aware joint resource allocation and dynamic pricing algorithm for Heterogeneous Networks
| Main Authors: | Trakas, Panagiotis, Adelantado, Ferran, Zorba, Nizar, Verikoukis, Christos |
|---|---|
| Format: | Proceeding eJournal |
| Bahasa: | eng |
| Terbitan: |
, 2017
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/1161185 |
Daftar Isi:
- The rise of third-party content providers and the introduction of numerous applications has been driving the growth of mobile data traffic in the past few years. The applications' various Quality of Service (QoS) requirements as well as the use of multiple devices per user have increased the traffic heterogeneity, pressing the telecommunications industry to the deployment of dense Heterogeneous Networks (HetNets). At the same time, the content providers' rise has also led to the decrease of the Mobile Network Operators' (MNOs) revenues. Under these circumstances, the MNOs need to guarantee the users' Quality of Experience (QoE) requirements, while ensuring the sustainability of HetNet investments. To this end, we consider a HetNet deployment where MNOs offer a multitude of services with diverse pricing. We propose a heuristic, joint QoE-aware resource allocation and dynamic pricing algorithm with overall user satisfaction constraints to maximize the MNO profit, while providing high QoE. Simulation results show that the proposed algorithm can handle traffic heterogeneity by achieving substantial profit and QoE gains, compared to a state of the art algorithm. Moreover, we demonstrate the benefits of our dynamic pricing scheme and its applicability on other resource allocation algorithms.
- Grant numbers : This work has been funded by the Project CellFive (TEC2014- 60130- P), anb by the Catalan Government (2014-SGR-1551).© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.