Management architecture for location-aware self-organizing LTE/LTE-a small cell networks

Fortes, Sergio; Aguilar-Garcı́a, Alejandro; Barco, Raquel; Barba, Félix Barba; Fernández-Luque, Jose Antonio; Fernandez-Duran, A.

doi:10.1109/mcom.2015.7010548

Cited by 45 publications

(38 citation statements)

References 7 publications

(5 reference statements)

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“…In this respect, the work in [9] proposed the interfaces and architecture required to integrate app-level information into the 3GPP management plane. Meanwhile, the work in [17] developed a real testbed prototype of such UE-level app based network troubleshooting.…”

Section: Ue Radio Measurementsmentioning

confidence: 99%

“…The required architectural coordination of different localization sources with SON mechanisms has been presented in [9]. In this way, UEs positioning information can be obtained indistinctively from the UEs or external sources, such as surveillance camera localization.…”

Section: Ue Radio Measurementsmentioning

confidence: 99%

“…An element in charge of that task is named as NETACC checking entity. This element or elements can perform the checking periodically or following an event/demand [9]. This check can be performed for a specific small cell element or for the complete deployment backhaul, e.g., by IP-PING style messages.…”

Section: Diagnosis Of Sleeping Cell Causesmentioning

confidence: 99%

“…Localization mechanisms based on the small cell deployments [8] open the door to using location to support the OAM tasks. Even if its use for self-healing in indoor scenarios has been just recently proposed [9], its usefulness has been previously demonstrated for macrocell scenarios and other OAM tasks (e.g., for coverage optimization [10]). Also, another important limitation of classical approaches is the high signaling costs of transmitting the monitoring data to the centralized OAM/SON systems, which might overload the operator's network.…”

Section: Introductionmentioning

confidence: 99%

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Location-based distributed sleeping cell detection and root cause analysis for 5G ultra-dense networks

Fortes

Barco

Aguilar-Garcı́a

2016

J Wireless Com Network

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The sleeping cell problem is one of the most critical issues for cellular deployments, consisting in the outage of a cellular station, which, conversely, works properly from the point of view of the monitoring system. This problem is often not detectable by the operators, and it could lead to severe degradations in the service provision in the long term. This issue has been commonly managed by the centralized analysis of network performance indicators. However, those solutions are unsuitable for the new ultra-dense small cell scenarios that will characterize 5G deployments. New approaches are required to cope with the high level of cell overlapping as well as the huge number of sites to be managed. In this context, a novel mechanism to detect sleeping cell issues is proposed, which takes advantage of the recent advances in indoor localization as well as monitoring data obtained by user equipments. In addition, a root cause analysis of the cell failure is presented. The capabilities of the proposed approach are evaluated in a realistic key scenario, showing the feasibility and usefulness of the proposed location-based approach.

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Section: Ue Radio Measurementsmentioning

confidence: 99%

Section: Ue Radio Measurementsmentioning

confidence: 99%

Section: Diagnosis Of Sleeping Cell Causesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Location-based distributed sleeping cell detection and root cause analysis for 5G ultra-dense networks

Fortes

Barco

Aguilar-Garcı́a

2016

J Wireless Com Network

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“…A lot of work were devoted to the femtocells usage [2,3,4] for dead zones coverage, mobile monitoring [5], some network delays caused by different factors [6], network optimization near wireless dead zones [7], architecture and its management in mobile networks [8,9,10].…”

Section: Introductionmentioning

confidence: 99%

The Simulation-Based Smart Management Approach for Cellular Network Operation and Planning

Suleykin¹,

Panfilov²

2017

DAAAM Proceedings

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The number of mobile users in the world has been steadily increasing for last decades and is anticipated to continue its growth by the end to 2019 up to more than 5 billion users. This process brings new challenges to the telecom companies over the globe and to the cellular network infrastructures. The problem (dead) zones and dropped calls are now among the most critical issues that mobile providers tend to solve, while trying to increase the quality of service at the same time. The paper discusses modeling approaches to the cellular network's problem zones detection and analysis, on the basis of complaints, subscribers and base stations data aggregation and analysis. We describe algorithms to be used in building Heat Map geo-spatial visualizations of cellular network data, which show the distribution of problem zones within the network with their corresponding weights assigned according to the amount of complaints and population density in the area. This information is used in prioritization of distributed problem zones for the cellular network development and decision support on new base station deployment. It means that simulation-based approaches to problem zone detection and fixation in cellular network can help to increase the customer satisfaction of connection level and quality of mobile service. In addition, the paper presents the evaluation of economic effect of solving the problem zone issue that follows the subscriber traffic increase.

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Location‐Aware Network Management

Fortes,

Baena,

Barco

et al. 2023

Positioning and Location‐based Analytics in 5G and Beyond

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Management architecture for location-aware self-organizing LTE/LTE-a small cell networks

Abstract: nández-Durán are with Alcatel-Lucent.

Cited by 45 publications

References 7 publications

Location-based distributed sleeping cell detection and root cause analysis for 5G ultra-dense networks

Location-based distributed sleeping cell detection and root cause analysis for 5G ultra-dense networks

The Simulation-Based Smart Management Approach for Cellular Network Operation and Planning

Location‐Aware Network Management

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