Towards user-centric operation in 5G networks

Monserrat, José F.; Alepuz, Irene; Cabrejas, Jorge; Osa, Vicente; López, Javier; Garcı́a, Roberto; Domenech, María José; Soler, Vicent

doi:10.1186/s13638-015-0506-z

Cited by 9 publications

(10 citation statements)

References 9 publications

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“…Traditional network-centric KPIs have been used in advanced mathematical optimization problems, such as in [17], for example, where the aim is to obtain a multi-criteria based on KPIs to recover the coverage map of a cellular network. However, industry and academy have both been discussing the need for shifting from network-centric KPIs to user-centric KPIs [18], as a bridge that could help in linking KPIs with the end user Quality of Experience (QoE) [16,[19][20][21][22][23]. Reference [16] explores how to obtain an index outperforming the Hotspot score, by introducing data driven tools that could automate the current empirically-based process.…”

Section: Introducing Composite Indicatorsmentioning

confidence: 99%

“…Reference [16] explores how to obtain an index outperforming the Hotspot score, by introducing data driven tools that could automate the current empirically-based process. In [19,20], data are gathered from the users in order to establish the correlation between the users' perception and the actual performance of the network. Note that references [16,19,20] do actually have access to massive MNO data.…”

Section: Introducing Composite Indicatorsmentioning

confidence: 99%

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On the Use of Composite Indicators for Mobile Communications Network Management in Smart Sustainable Cities

et al. 2020

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Beyond 5G networks will be fundamental towards enabling sustainable mobile communication networks. One of the most challenging scenarios will be met in ultra-dense networks that are deployed in densely populated areas. In this particular case, mobile network operators should benefit from new assessment metrics and data science tools to ensure an effective management of their networks. In fact, incorporating architectures allowing a cognitive network management framework could simplify processes and enhance the network’s performance. In this paper, we propose the use of composite indicators based on key performance indicators both as a tool for a cognitive management of mobile communications networks, as well as a metric which could successfully integrate more advanced user-centric measurements. Composite indicators can successfully synthesize and integrate large amounts of data, incorporating in a single index different metrics selected as triggers for autonomous decisions. The paper motivates and describes the use of this methodology, which is applied successfully in other areas with the aim of ranking metrics to simplify complex realities. A use case that is based on a universal mobile telecommunications system network is analyzed, due to technology simplicity and scalability, as well as the availability of key performance indicators. The use case focuses on analyzing the fairness of a network over different coverage areas as a fundamental metric in the operation and management of the networks. To this end, several ranking and visualization strategies are presented, providing examples of how to extract insights from the proposed composite indicator.

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Section: Introducing Composite Indicatorsmentioning

confidence: 99%

Section: Introducing Composite Indicatorsmentioning

confidence: 99%

On the Use of Composite Indicators for Mobile Communications Network Management in Smart Sustainable Cities

et al. 2020

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“…A survey conducted by Pew research clearly shows that 86% of the internet users have tried to use the internet in ways that would minimize the visibility of their digital footprints [5]. However, fifth generation (5G) technology is user centric and data centric [6]. It is very importation that the users of the technology to trust services provided by the network and share accurate information with the services.…”

Section: Introductionmentioning

confidence: 99%

Introduction to the Minitrack on Privacy, 5G and Economics

Skouby

Sørensen

Khajuria

2018

Proceedings of the 51st Hawaii International Conference on System Sciences

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The mini-track on Privacy, 5G and Economics focus on discussion of different aspects of security and privacy in the data rich environment including user right to privacy with regards to collection, retention, analysis and transfer of personal data. Differences between the regulation in the EU and the USA are debated in different examples. The mini-track also insists on the economic value of end users' data to innovatively redefine the relationships between end users' concerns on their personal data handling and the legal businesses on data analytics, in order to make that relationship ethically correct, compliant with regulation and also profitable for all.

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“…The rising demands for network resources and quality of service are forcing operators of wireless cellular networks to continuously add capacities to their networks. One of the means to do so is densification: deploying heterogeneous networks with a multitude of smaller base stations, such as picobase stations and femtobase stations [1][2][3][4]. Such a heterogeneous network will be significantly more complex than today's system and hence will require more effective state control strategies to achieve energy efficient coverage.…”

Section: Introductionmentioning

confidence: 99%

Sliding Window Based Feature Extraction and Traffic Clustering for Green Mobile Cyberphysical Systems

Zhang

Zhou

Xiao

et al. 2017

Mobile Information Systems

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Both the densification of small base stations and the diversity of user activities bring huge challenges for today’s heterogeneous networks, either heavy burdens on base stations or serious energy waste. In order to ensure coverage of the network while reducing the total energy consumption, we adopt a green mobile cyberphysical system (MCPS) to handle this problem. In this paper, we propose a feature extraction method using sliding window to extract the distribution feature of mobile user equipment (UE), and a case study is presented to demonstrate that the method is efficacious in reserving the clustering distribution feature. Furthermore, we present traffic clustering analysis to categorize collected traffic distribution samples into a limited set of traffic patterns, where the patterns and corresponding optimized control strategies are used to similar traffic distributions for the rapid control of base station state. Experimental results show that the sliding window is more superior in enabling higher UE coverage over the grid method. Besides, the optimized control strategy obtained from the traffic pattern is capable of achieving a high coverage that can well serve over 98% of all mobile UE for similar traffic distributions.

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Towards user-centric operation in 5G networks

Cited by 9 publications

References 9 publications

On the Use of Composite Indicators for Mobile Communications Network Management in Smart Sustainable Cities

On the Use of Composite Indicators for Mobile Communications Network Management in Smart Sustainable Cities

Introduction to the Minitrack on Privacy, 5G and Economics

Sliding Window Based Feature Extraction and Traffic Clustering for Green Mobile Cyberphysical Systems

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