Cost-effective Base Station Deployment Approach Based on Artificial Immune Systems

Djalma de Melo Carvalho  Filho; Marcelo Sampaio de Alencar

3d International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems

Research Article

Cost-effective Base Station Deployment Approach Based on Artificial Immune Systems

Download473 downloads

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.4108/ICST.BIONETICS2008.4696,
    author={Djalma de Melo Carvalho  Filho and Marcelo Sampaio de Alencar},
    title={Cost-effective Base Station Deployment Approach Based on Artificial Immune Systems},
    proceedings={3d International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems},
    publisher={ICST},
    proceedings_a={BIONETICS},
    year={2010},
    month={5},
    keywords={Base station deployment; optimisation; artificial immune systems.},
    doi={10.4108/ICST.BIONETICS2008.4696}
}

Djalma de Melo Carvalho Filho
Marcelo Sampaio de Alencar
Year: 2010
Cost-effective Base Station Deployment Approach Based on Artificial Immune Systems
BIONETICS
ICST
DOI: 10.4108/ICST.BIONETICS2008.4696

Djalma de Melo Carvalho Filho¹^,*, Marcelo Sampaio de Alencar¹^,*

1: Federal University of Campina Grande, Av. Aprígio Veloso, 882, CEP 58109-970 Campina Grande, Brazil Tel: 558333101578

*Contact email: djalmacarvalho@uol.com.br, malencar@iecom.org.br

Abstract

This work presents a cost-effective base station deployment model based on artificial immune systems. It uses a multi-objective algorithm based on artificial immune systems (MO-AIS) as an optimiser. MO-AIS algorithms are a new class of evolutionary algorithms. The Binary-coded Multi-objective Optimisation Algorithm (BRMOA) is inspired by the clonal selection theory and the immune network theory. In this innovative approach, the network is optimised for high service coverage and low cost. The cost function takes into account user-defined geographical costs and environmental legislation. The optimisation strategy is applied to two realistic scenarios and results are compared.

Keywords: Base station deployment; optimisation; artificial immune systems.

Published: 2010-05-16
Publisher: ICST
Modified: 2010-05-16

: http://dx.doi.org/10.4108/ICST.BIONETICS2008.4696