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QoE-Aware Beamforming Design for Massive MIMO Heterogeneous Networks
IUST, Iran; MTNi Co, Iran.
IUST, Iran.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-5954-434X
2018 (English)In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 67, no 9, p. 8315-8323Article in journal (Refereed) Published
Abstract [en]

One of the main goals of the future wireless networks is improving the users quality of experience (QoE). In this paper, we consider the problem of the QoE-based resource allocation in the downlink of a massive multiple-input multiple-output heterogeneous network. The network consists of a macrocell with a number of small cells embedded in it. The small cells base stations (BSs) are equipped with a few antennas, while the macro BS is equipped with a massive number of antennas. We consider the two services Video and Web Browsing and design the beamforming vectors at the BSs. The objective is to maximize the aggregated mean opinion score (MOS) of the users under constraints on the BSs powers and the required quality of service of the users. We also consider extra constraints on the QoE of users to more strongly enforce the QoE in the beamforming design. To reduce the complexity of the optimization problem, we suggest suboptimal and computationally efficient solutions. Our results illustrate that increasing the number of antennas at the BSs and also increasing the number of small cells antennas in the network leads to a higher user satisfaction.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2018. Vol. 67, no 9, p. 8315-8323
Keywords [en]
Quality of experience (QoE); Web browsing; massive multiple-input multiple-output (MaMIMO); heterogeneous networks (HetNets); power allocation; mean opinion score; quality of service (QoS); video service; 5G
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:liu:diva-151953DOI: 10.1109/TVT.2018.2843355ISI: 000445397600035OAI: oai:DiVA.org:liu-151953DiVA, id: diva2:1256328
Available from: 2018-10-16 Created: 2018-10-16 Last updated: 2019-06-28

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