Parallelizing PBIL for Solving a Real-World Frequency Assignment Problem in GSM Networks

Frequency planning (also known as frequency assignment problem -FAP-) is a very important task for current GSM operators. The problem consists in trying to minimize the number of interferences caused when a limited number of frequencies has to be assigned to a quite high number of transceivers. In t...

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Bibliographic Details
Main Authors: Chaves-Gonzalez, J.M., Dominguez-Gonzalez, D., Vega-Rodriguez, M.A., Gomez-Pulido, J.A., Sanchez-Perez, J.M.
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Cities and towns
Clustering algorithms
Concurrent computing
Financial advantage program
Frequency
GSM
Interference
Technology planning
Transceivers
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Summary:Frequency planning (also known as frequency assignment problem -FAP-) is a very important task for current GSM operators. The problem consists in trying to minimize the number of interferences caused when a limited number of frequencies has to be assigned to a quite high number of transceivers. In this work we focus on solving this problem for a realistic-sized, real-world GSM network using a parallelized version of the PBIL (population-based incremental learning) algorithm. Therefore, we have parallelized the PBIL algorithm fixed to the FAP problem using cluster computing. The analysis of the results proves that we have reached a double goal: on the one hand, with the parallelized version of the algorithm, its execution time is reduced down to the optimum values; and on the other hand, we prove that using a distributed island model applied to PBIL, the results for the network-planning are better than the ones obtained with the sequential version.
ISSN:1066-6192
2377-5750
DOI:10.1109/PDP.2008.23