Impact of the HSPDA-Based Mobile Broadband Access on the Investment of the 3G Access Network

Sánchez-García, Juan; Ahmadzadeh, Amir; Jiménez-Fernández, Silvia; Salcedo‐Sanz, Sancho; Portilla-Figueras, Antonio

doi:10.1007/978-3-642-29479-2_24

Cited by 2 publications

(4 citation statements)

References 3 publications

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“…As stated before, the coral encoding determines the services’ distribution over the different mobile technologies available. To obtain the health function associated to each coral, the software tool SMNPT has been used in this work. The SMNPT, developed by the University of Alcalá, the University of Cantabria and the German company WIK‐Consult GmbH, has been successfully applied before to several regulatory projects .…”

Section: Algorithm For Solving the Osdpmentioning

confidence: 99%

“…Each terminal category presents its own features in terms of modulation and coding schemes (MCS), signal to interference noise ratio, SINR , used in the Cost231‐Hata model propagation analysis, and maximum offered throughput applied to the capacity study. The model estimates the cell range and the number of HSPA BS to be deployed based on , .…”

Section: Algorithm For Solving the Osdpmentioning

confidence: 99%

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A coral‐reef optimization algorithm for the optimal service distribution problem in mobile radio access networks

Salcedo‐Sanz

Sánchez-García

Portilla-Figueras

et al. 2013

Trans. Emerging Tel. Tech.

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Mobile technology is currently one of the main pillars of worldwide economy. The constant evolution that mobile communications have undergone in the last decades, due to the appearance of new services and new technologies such as Universal Mobile Telecommunication Systems/High Speed Data Access and Long Term Evolution, has contributed to achieve this position in global economy. However, because of the crisis of the sector in the last 5 years, mobile operator's revenues and investments have been reduced. Thus, mobile network operators tend to exploit the existing infrastructure at maximum possible, trying to use the existing network in the most efficient way. In this paper, a novel bio-inspired algorithm, the coral reef optimization algorithm (CRO) is introduced to minimise a network deployment investment cost problem. This is carried out by means of optimising the user demand of different services offered by mobile operators over the available technologies in the market, namely the optimal service distribution problem. The CRO is a recently proposed meta-heuristic based on the computer simulation of corals reproduction and reefs' formation. In this paper, this algorithm has been tested on several optimal service distribution problem scenarios in Spain, observing a significant reduction (up to 400 Me) on the total investment costs associated to the radio access network deployment. We compare the performance of the CRO approach with that of a classical (experience-based) services distribution, and with alternative meta-heuristics techniques, obtaining good results in all cases.

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Section: Algorithm For Solving the Osdpmentioning

confidence: 99%

Section: Algorithm For Solving the Osdpmentioning

confidence: 99%

A coral‐reef optimization algorithm for the optimal service distribution problem in mobile radio access networks

Salcedo‐Sanz

Sánchez-García

Portilla-Figueras

et al. 2013

Trans. Emerging Tel. Tech.

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“…On the other hand, the other group of actors who might be interested in this type of proposal are National Regulatory Authorities, which want to check whether or not (and to what extent) mobile termination costs and/or the interconnection tariffs of a given service of a specific operator are appropriate or, conversely, are causing anomalies in the market. Regarding this, the short‐term objective is to integrate the proposed algorithm into a Strategic Mobile Network Planning Tool whose specific details have been published somewhere . This kind of tools are commonly applied to telecommunication regulatory projects, in which the objective is to estimate the provision cost of the different services under the so‐called bottom‐up long‐run incremental cost model, which is recommended by the European Commission .…”

Section: Introductionmentioning

confidence: 99%

“…Regarding this, the short-term objective is to integrate the proposed algorithm into a Strategic Mobile Network Planning Tool whose specific details have been published somewhere. [42][43][44] This kind of tools are commonly applied to telecommunication regulatory projects, in which the objective is to estimate the provision cost of the different services under the so-called bottom-up long-run incremental cost model, 45,46 which is recommended by the European Commission. 47 The goal of the long-run incremental cost model is to estimate the costs incurred by a hypothetical operator that aims to implement a cost-optimized network with the best suitable technology (LTE, in this case).…”

Section: Introductionmentioning

confidence: 99%

Near‐optimal user assignment in LTE mobile networks with evolutionary computing

Arco-Vega

Cuadra

Portilla-Figueras

et al. 2016

Trans. Emerging Tel. Tech.

Self Cite

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This paper tackles the problem of users assignment to evolved NodeBs in long‐term evolution mobile networks. We propose a model that aims at assigning users by minimizing a function called download time of the complete system, defined as the minimum time required for all the users in the system to complete their downloads. This strategy helps the network use its resources in a more balanced way, by assigning users from cells (which otherwise would be overloaded when using a simple signal‐to‐interference‐plus‐noise ratio‐based approach) to others with less load. The user‐cell association problem is, in general, a combinatorial NP hard problem. Although other approaches indirectly tackle this complexity by transforming the problem into another whose optimal solution is less difficult (but still with very high computational cost), we tackle directly our download time of the complete system minimization problem by finding an approximate solution provided by a specific implementation of an evolutionary algorithm, which is based on a long‐term evolution domain‐specific initial population along with fully tailored operators adapted to this assignment problem. A variety of experiments in different realistic scenarios point out that the proposed method outperforms the conventional signal‐to‐interference‐plus‐noise ratio‐based and load balancing approaches, specially in urban and dense urban environments (where the assignment is more critical in terms of capacity). We have also tested our approach in simple scenarios that mimic heterogeneous networks and ultra‐dense networks in which the number of users is similar to that of nodes, proving its beneficial properties. Our method is aimed at the design/dimensioning stage and not to the operation stage, and in this sense, it is an off‐line algorithm that could be useful to make better decisions on cost‐effective network dimensioning and upgrading.

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Impact of the HSPDA-Based Mobile Broadband Access on the Investment of the 3G Access Network

Cited by 2 publications

References 3 publications

A coral‐reef optimization algorithm for the optimal service distribution problem in mobile radio access networks

A coral‐reef optimization algorithm for the optimal service distribution problem in mobile radio access networks

Near‐optimal user assignment in LTE mobile networks with evolutionary computing

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