The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
A Data-Driven Architecture for Personalized QoE Management in 5G Wireless Networks
Abstract
With the emergence of a variety of new wireless network types, business types, and QoS in a more autonomic, diverse, and interactive manner, it is envisioned that a new era of personalized services has arrived, which emphasizes users' requirements and service experiences. As a result, users' QoE will become one of the key features in 5G/future networks. In this article, we first review the state of the art of QoE research from several perspectives, including definition, influencing factors, assessment methods, QoE models, and control methods. Then a data-driven architecture for enhancing personalized QoE is proposed for 5G networks. Under this architecture, we specifically propose a two-step QoE modeling approach to capture the strength of the relationship between users and services. Thereafter, the preferences of a user is introduced to model the user's subjectivity toward a specific service. With the comprehension of users' preferences, radio resources can be distributed more precisely. Simulation results show that overall QoE can be enhanced by 20 percent, while 96 percent of users have an improved QoE, which validates the efficiency of the proposed architecture.
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“As stated in [8], the main challenges that arise with regards to QoE optimization and control may be summarized in the answers to the following four questions: (1) What key quality parameters to optimize and control? (2) Where to control (e.g., at the client, server and the network side)? (3) When to perform QoE optimization and control (e.g., during the service, that is, on-line control or in an”
From QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey (2020) · cites this paper as [19]
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“Although recent efforts explore the QoE management aspects using SDN and/or NFV, we note that these works are limited in at least one of the following: 1) limited review and discussion of the standardization activities related to SDN and/or NFV;”
From QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey (2020) · cites this paper as [19]
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Scenarios for 5G mobile and wireless communications: the vision of the METIS project
Osseiran, A., Boccardi, F., Braun, V., Kusume, K., Marsch, P., Maternia, M., Queseth, O., Schellmann, M., Schotten, H. D., Taoka, H., et al. (2014) · IEEE Communications Magazine · doi:10.1109/mcom.2014.6815890 · Cited by 2,004
A Survey on Quality of Experience of HTTP Adaptive Streaming
Seufert, M., Egger, S., Slanina, M., Zinner, T., Hoßfeld, T., & Tran-Gia, P. (2015) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2014.2360940 · Cited by 844
Qualinet White Paper on Definitions of Quality of Experience
Callet, P. L., Möller, S., Perkis, A., Brunnstrom, K. E., Beker, S., Moor, K. D., Dooms, A., Egger, S., Garcia, M.-N., Hoßfeld, T., et al. (2013) · HAL · Cited by 693
Networks and devices for the 5G era
Bangerter, B., Talwar, S., Arefi, R., & Stewart, K. (2014) · IEEE Communications Magazine · doi:10.1109/mcom.2014.6736748 · Cited by 471
Quantification of YouTube QoE via Crowdsourcing
Hoßfeld, T., Seufert, M., Hirth, M., Zinner, T., Tran‐Gia, P., & Schatz, R. (2011) · IEEE International Symposium on Multimedia (ISM) · doi:10.1109/ism.2011.87 · Cited by 338
5G: Personal mobile internet beyond what cellular did to telephony
Fettweis, G. P., & Alamouti, S. M. (2014) · IEEE Communications Magazine · doi:10.1109/mcom.2014.6736754 · Cited by 309
The Logarithmic Nature of QoE and the Role of the Weber-Fechner Law in QoE Assessment
Reichl, P., Egger, S., Schatz, R., & D'Alconzo, A. (2010) · 2010 IEEE International Conference on Communications · doi:10.1109/icc.2010.5501894 · Cited by 284
Toward total quality of experience: A QoE model in a communication ecosystem
Laghari, K. U. R., & Connelly, K. H. (2012) · IEEE Communications Magazine · doi:10.1109/mcom.2012.6178834 · Cited by 223
The memory effect and its implications on Web QoE modeling
Hosfeld, T., Biedermann, S., Schatz, R., Platzer, A., Egger, S., & Fiedler, M. (2011) · International Teletraffic Congress · doi:10.5555/2043468.2043485 · Cited by 104
MOS-Based Multiuser Multiapplication Cross-Layer Optimization for Mobile Multimedia Communication
Khan, S., Duhovnikov, S., Steinbach, E. G., & Kellerer, W. (2007) · Advances in Multimedia · doi:10.1155/2007/94918 · Cited by 102
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Deep Learning in Mobile and Wireless Networking: A Survey
Zhang, C., Patras, P., & Haddadi, H. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2904897 · Cited by 1,913
5G network slicing using SDN and NFV: A survey of taxonomy, architectures and future challenges
Barakabitze, A. A., Ahmad, A., Mijumbi, R., & Hines, A. (2019) · Computer Networks · doi:10.1016/j.comnet.2019.106984 · Cited by 842
QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey
Barakabitze, A. A., Barman, N., Ahmad, A., Zadtootaghaj, S., Sun, L., Martini, M. G., & Atzori, L. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2958784 · Cited by 239
Blockchain-enabled resource management and sharing for 6G communications
Xu, H., Klaine, P. V., Onireti, O., Cao, B., Imran, M. A., & Zhang, L. (2020) · Digital Communications and Networks · doi:10.1016/j.dcan.2020.06.002 · Cited by 232
Green Resource Allocation Based on Deep Reinforcement Learning in Content-Centric IoT
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Metadata
- Authors
- Wang, Y., Li, P., Jiao, L., Su, Z., Cheng, N., Shen, X. S., & Zhang, P.
- Affiliations
- Beijing University of Posts and Telecommunications (CN)
- University of Agder (NO)
- Shanghai University (CN)
- University of Waterloo (CA)
- Venue
- IEEE Wireless Communications
- Published
- 2017-02
- Volume
- 24
- Issue
- 1
- Pages
- 102-110
- ISSN
- 1536-1284 (ISSN-L)
- OpenAlex
- W2556076181
- Cited by
- 125
- References
- 16
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 5 · 2023: 10 · 2022: 21 · 2021: 16 · 2020: 18 · 2019: 17 · 2018: 17 · 2017: 6
- FWCI
- 10.19
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Wireless Communications (publishedVersion)
- Funders
- National Science Foundation
- National Natural Science Foundation of China
- Beijing University of Posts and Telecommunications
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Video Quality Assessment
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Network Optimization
- Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
- Keywords
- quality of experience, 5G, data-driven architecture, user preferences, QoE modeling, radio resource allocation
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