FREQUENCY ASSIGNMENT OPTIMIZATION USING THE SWARM INTELLIGENCE MULTI-AGENT BASED ALGORITHM (SIMBA)

Grant Blaise O'Reilly

Abstract

The swarm intelligence multi-agent based algorithm (SIMBA) is presented in this paper. The SIMBA utilizes swarm intelligence and a multi-agent system (MAS) to optimize the frequency assignment problem (FAP). The SIMBA optimises by considering both local and global i.e. collective solutions in the optimization process. Stigmergy single cell optimization (SSCO) is also used by the individual agents in SIMBA. SSCO enables the agents to recognize interference patterns in the frequency assignment structure that is being optimized and to augment it with frequency selections that minimized the interference. The changing configurations of the frequency assignment structure acts as a source of information that aids the agents when making further decisions. Due to the increasing demand of cellular communication services and the available frequency spectrum optimal frequency assignment is necessary. The SIMBA was used to optimize the fixed-spectrum frequency assignment problem (FS-FAP) in cellular radio networks. The results produced by the SIMBA were benchmarked against the COST 259 Siemens scenarios. The frequency assignment solutions produced by the SIMBA were also implemented in a commercial cellular radio network and the results are presented.

References

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Paper Citation


in Harvard Style

Blaise O'Reilly G. (2009). FREQUENCY ASSIGNMENT OPTIMIZATION USING THE SWARM INTELLIGENCE MULTI-AGENT BASED ALGORITHM (SIMBA) . In Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8111-85-2, pages 25-32. DOI: 10.5220/0001857600250032


in Bibtex Style

@conference{iceis09,
author={Grant Blaise O'Reilly},
title={FREQUENCY ASSIGNMENT OPTIMIZATION USING THE SWARM INTELLIGENCE MULTI-AGENT BASED ALGORITHM (SIMBA)},
booktitle={Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2009},
pages={25-32},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001857600250032},
isbn={978-989-8111-85-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - FREQUENCY ASSIGNMENT OPTIMIZATION USING THE SWARM INTELLIGENCE MULTI-AGENT BASED ALGORITHM (SIMBA)
SN - 978-989-8111-85-2
AU - Blaise O'Reilly G.
PY - 2009
SP - 25
EP - 32
DO - 10.5220/0001857600250032