On GSM mobile measurement based interference matrix generation

Kuurne, A.

doi:10.1109/vtc.2002.1002966

Cited by 31 publications

(19 citation statements)

References 1 publication

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“…The more accurate the measure of the interference in a given GSM network, the higher the quality of the frequency plan that can be computed for this network. Several ways of quantifying this interference exist, ranging from theoretical methods to extensive measurements (Kuurne 2002). They all result in a so-called interference matrix, denoted by M .…”

Section: Frequency Planning In Gsm Networkmentioning

confidence: 99%

Solving large-scale real-world telecommunication problems using a grid-based genetic algorithm

Luna¹,

Nebro²,

Alba³

et al. 2008

Engineering Optimization

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. Solving large-scale real-world telecommunication problems using a grid-based genetic algorithm. Engineering Optimization, Taylor Francis, 2008, 40 (11) AbstractThis paper analyzes the use of a grid-based genetic algorithm (GrEA) to solve a real-world instance of a problem from the telecommunication domain. The problem, known as automatic frequency planning (AFP), is used in GSM networks (Global System for Mobile communications) to assign a number of fixed frequencies to a set of GSM transceivers located in the antennae of a cellular phone network. Real data instances of the AFP are very difficult to solve due to the NP-hard nature of the problem, so combining grid computing and metaheuristics comes out as a way to provide satisfactory solutions in a reasonable amount of time. GrEA has been deployed on a grid with up to 300 processors to solve an AFP instance of 2,612 transceivers. The results not only show that significant running times reductions are achieved, but that the search capability of GrEA outperforms clearly that of the equivalent non-grid algorithm.

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Section: Frequency Planning In Gsm Networkmentioning

confidence: 99%

Solving large-scale real-world telecommunication problems using a grid-based genetic algorithm

Luna¹,

Nebro²,

Alba³

et al. 2008

Engineering Optimization

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“…There are several ways of quantifying this interference. These methods range from theoretical methods to extensive measurements (Kuurne 2002), however the most extended way of quantifying the interferences produced in a GSM network is using the called interference matrix. Each element of this matrix contains a pair (i, j) which holds two types of interferences: the co-channel interference, which represents the degradation of the network quality if the cells i and j operate on the same frequency; and the adjacentchannel interference, which occurs when two TRXs operate on adjacent channels (e.g.…”

Section: The Frequency Assignment Problem and The Gsm Communication Smentioning

confidence: 99%

Optimizing a realistic large-scale frequency assignment problem using a new parallel evolutionary approach

Chaves-González

Vega‐Rodríguez

Gómez–Pulido

et al. 2011

Engineering Optimization

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International audienceThis paper analyzes the use of a novel parallel evolutionary strategy to solve complex optimization problems. The work developed here has been focused on a relevant real-world problem from the telecommunication domain to verify the effectiveness of our approach. The problem, known as frequency assignment problem (FAP), basically consists of assigning a very small number of frequencies to a very large set of transceivers used in a cellular phone network. Real FAP instances are very difficult to solve due to the NP-hard nature of the problem, therefore using an efficient parallel approach which takes the most of different evolutionary strategies can be considered as a good way to obtain high-quality solutions in short periods of time. Specifically, a parallel hyper-heuristic based on several meta-heuristics has been developed. After a complete experimental evaluation, results prove that our approach obtains very high-quality solutions for the FAP (it beats any other result published)

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“…The more accurate the measure of the interference in a given GSM network, the higher the quality of the frequency plan that can be computed for this network. Several ways of quantifying this interference exist, ranging from theoretical methods to extensive measurements [51]. They all result in a so-called interference matrix, denoted by M .…”

Section: Frequency Planning In Gsmmentioning

confidence: 99%

Optimization algorithms for large-scale real-world instances of the frequency assignment problem

et al. 2010

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Nowadays, mobile communications are experiencing a strong growth, being more and more indispensable. One of the key issues in the design of mobile networks is the Frequency Assignment Problem (FAP). This problem is crucial at present and will remain important in the foreseeable future. Real world instances of FAP typically involve very large networks, which can only be handled by heuristic methods. In the present work, we are interested in optimizing frequency assignments for problems described in a mathematical formalism that incorporates actual interference information, measured directly on the field, as is done in current GSM networks. To achieve this goal, a range of metaheuristics have been designed, adapted, and rigourously compared on two actual GSM networks modeled according to the latter formalism. In order to generate quickly and reliably high quality solutions, all metaheuristics combine their global search capabilities with a local-search method specially tailored for this domain. The experiments and statistical tests show that in general, all metaheuristics are able to improve upon results published in previous studies, but two of the metaheuristics emerge as the best performers: a populationFrancisco Luna, Antonio J. Nebro, and Enrique Alba Universidad de Málaga, Spain E-mail: {flv, antonio, eat}@lcc.uma.es César Estébanez, Ricardo Aler, and José M. Valls Universidad Carlos III de Madrid, Spain E-mail: {cesteban, aler, jvalls}@inf.uc3m.es Coromoto León, Carlos Segura, and Gara Miranda Universidad de La Laguna, Spain E-mail: {cleon, csegura, gmiranda}@ull.es José M. Chaves-González, Miguel A. Vega-Rodríguez, and Juan A. Gómez-Pulido Universidad de Extremadura, Spain E-mail: {jm, mavega, jangomez}@unex.es based algorithm (Scatter Search) and a trajectory based (1+1) Evolutionary Algorithm. Finally, the analysis of the frequency plans obtained offers insight about how the interference cost is reduced in the optimal plans.

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On GSM mobile measurement based interference matrix generation

Cited by 31 publications

References 1 publication

Solving large-scale real-world telecommunication problems using a grid-based genetic algorithm

Solving large-scale real-world telecommunication problems using a grid-based genetic algorithm

Optimizing a realistic large-scale frequency assignment problem using a new parallel evolutionary approach

Optimization algorithms for large-scale real-world instances of the frequency assignment problem

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