ACO Algorithm Applied to Multi-Objectives Optimization of Capacity Expansion in Next Generation Wireless Network

Автор: Dac-Nhuong Le, Son HongNgo, Vinh Trong Le

Журнал: International Journal of Wireless and Microwave Technologies(IJWMT) @ijwmt

Статья в выпуске: 1 Vol.3, 2013 года.

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The optimal capacity expansion of base station subsystems in Next Generation Wireless Network (NGWN) problem with respect to multi-demand type and system capacity constraints is known to be NP-complete. In this paper, we propose a novel ant colony optimization algorithm to solve a network topology has two levels in which mobile users are sources and both base stations and base station controllers are concentrators. There are two important aspects of upgrading to NGWN. The first importance of backward compatibility with pre-existing networks, and the second is the cost and operational benefit of gradually enhancing networks, by replacing, upgrading and installing new wireless network infrastructure elements that can accommodate both voice and data demand. Our objective function is the sources to concentrators connectivity costas well as the cost of the installation, connection, replacement, and capacity upgrade of infrastructure equipment. We evaluate the performance of our algorithm with a set of real world and data randomly generated. Numerical results show that our algorithms is a promising approach to solve this problem.

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Next Generation Wireless Network, Multi-Objectives, Capacity Expansion, Base Station Subsystems, Ant Colony Optimization

Короткий адрес: https://sciup.org/15012850

IDR: 15012850

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