Design of Distributed and Autonomic Load Balancing for Self-Organization LTE

Zhang, Heng; Qiu, Xuesong; Li, Meng; Zhang, Xidong

doi:10.1109/vetecf.2010.5594567

Cited by 30 publications

(19 citation statements)

References 1 publication

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“…Other mechanisms [17,21] based on FLCs, where efficient rules are defined by experts, present adaptive solutions to reach the best system configuration. Some others propose complex equations or techniques [19], even based on FLCs [18], which lead to high computational cost not really feasible to be implemented in real deployments. In consequence, the main reasons for choosing FLCs are related to the ease for the integration and translation of expert human knowledge into a set of fuzzy rules, its simplicity in implementing and managing rules based on experience, and the low computational cost required to obtain highly improved performance in femtocell networks.…”

Section: Fuzzy Logic Controllersmentioning

confidence: 99%

“…A similar fuzzy logic approach is presented in [17], where cell transmission power and handover margins are tuned to solve persistent congestion problems in enterprise LTE environments, based on call blocking rate. A more computationally complex method [18] obtained better performance than previous studies through a fuzzy rule-based reinforcement learning system, while reference [19] proposed a distributed method to achieve automatic load balancing based on a flowing water method. However, none of these previous works focused on femtocell environments have taken into account the femtocell limitation in the number of simultaneous users which is an important restriction in this kind of base stations (macrocells or other type of small cells do not have such restriction).…”

Section: Introductionmentioning

confidence: 97%

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Load balancing mechanisms for indoor temporarily overloaded heterogeneous femtocell networks

Aguilar-Garcı́a

Barco

Fortes

et al. 2015

J Wireless Com Network

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Macrocell and small cell deployments and self-organizing network (SON) techniques work together to increase indoor cellular network capacity and ensure better quality of service (QoS). As a consequence of uneven local user densities and temporal or spatial fluctuations of traffic, the network may suffer overload situations, which partially degrades network performance. Load balancing self-optimization introduces automatic and intelligent mechanisms to tune network parameters in order to improve the overall cellular network performance. This paper proposes novel load balancing methods based on fuzzy logic controllers (FLC) that evaluate temporarily overloaded situations and resize cell coverage areas by an adaptive process of adjusting cell transmission power. To accomplish this goal, classical network indicators are analyzed (e.g., call blocking ratio, available radio resources) while a novel and simple, although powerful, indicator (not mentioned in the literature yet) is additionally proposed as the system input. This indicator is related to the maximum allowed number of users in a femtocell. The proposed methods have been evaluated and compared with the literature in a realistic scenario.

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Section: Fuzzy Logic Controllersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

Load balancing mechanisms for indoor temporarily overloaded heterogeneous femtocell networks

Aguilar-Garcı́a

Barco

Fortes

et al. 2015

J Wireless Com Network

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“…Load balancing consists in the redistribution of load between cells in such way that all cells are equally loaded. Namely, the articles as [12], [6], [17] and [19] present different algorithms for spectrum and energy efficient load balancing. The performance of heterogeneous networks gained a lot of research interest recently, for example see [4] and [8], since their deployment is already commercial and will probably continue to grow.…”

Section: Related Workmentioning

confidence: 99%

Qos and network performance estimation in heterogeneous cellular networks validated by real-field measurements

Jovanović

Karray

Błaszczyszyn

2014

Proceedings of the 11th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, &Amp; Ubiquitous Networks

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Mobile network operators observe a significant disparity of quality of service (QoS) and network performance metrics, such as the mean user throughput, the mean number of users and the cell load, over different network base stations. The principal reason being the fact that real networks are never perfectly hexagonal, base stations are subject to different radio conditions, and may have different engineering parameters. We propose a model that takes into account these network irregularities in a probabilistic manner, in particular assuming Poisson spatial location of base stations, lognormal shadowing and random transmission powers. Performance of base stations is modeled by spatial processor sharing queues, which are made dependent of each other via a system of load equations. In order to validate our approach, we estimate all the model parameters from the data collected in a commercial network, solve it and compare the spatial variability of the QoS and performance metrics in the model to the real network performance metrics. Considering two scenarios: downtown of a big city and a mid-size city, we show that our model predicts well the network performance.

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“…This difference along with the current Qoffset values are used as inputs to a fuzzy logic algorithm in order to make Qoffset adjustments. The authors in [24] propose a Qoffset-adjusting scheme based on an Autonomic Flowing Water Balancing Method (AFWBM) inspired by the connected vessels theory in physics.…”

Section: Overview Of Schemesmentioning

confidence: 99%

Understanding the interactions of handover-related self-organization schemes

Suleiman

Taha

Hassanein

2014

Proceedings of the 17th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

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A Self Organizing Network (SON) scheme monitors certain Key Performance Indicators (KPIs) and responds by adjusting system control parameters.Multiple SON schemes may have related KPIs or use the same control parameters. This leads these schemes and their use cases to interact either constructively or destructively. In this paper, we study these interactions between three SON use cases all aiming at improving the overall handover procedure in LTE femtocell networks. These use cases are namely: handover self optimization, call admission control self optimization and load balancing self optimization. This work is motivated by the lack of interaction studies conducted so far between these three self optimization use cases. First, we have surveyed related individual scheme proposals in order to identify schemes which represent these three use cases in our interaction study. Then, several interaction experiments are conducted in realistic scenarios using our in-house built and LTE-compliant simulation environment.We conclude by drawing guidelines that we believe can help designers realize better coordination policies between these three handover-related SON use cases.

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Design of Distributed and Autonomic Load Balancing for Self-Organization LTE

Cited by 30 publications

References 1 publication

Load balancing mechanisms for indoor temporarily overloaded heterogeneous femtocell networks

Load balancing mechanisms for indoor temporarily overloaded heterogeneous femtocell networks

Qos and network performance estimation in heterogeneous cellular networks validated by real-field measurements

Understanding the interactions of handover-related self-organization schemes

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