OCNEApr 15, 2017

On Improving the Capacity of Solving Large-scale Wireless Network Design Problems by Genetic Algorithms

arXiv:1704.05367v124 citations
Originality Synthesis-oriented
AI Analysis

This addresses the need for efficient resource assignment in congested wireless networks, but it is incremental as it applies a known method to a specific problem.

The authors tackled the Power, Frequency and Modulation Assignment Problem in large-scale wireless network design by proposing a Genetic Algorithm, which allowed for broader exploration of power solutions and eliminated numerical issues, as tested on realistic Fixed WiMAX Network instances.

Over the last decade, wireless networks have experienced an impressive growth and now play a main role in many telecommunications systems. As a consequence, scarce radio resources, such as frequencies, became congested and the need for effective and efficient assignment methods arose. In this work, we present a Genetic Algorithm for solving large instances of the Power, Frequency and Modulation Assignment Problem, arising in the design of wireless networks. To our best knowledge, this is the first Genetic Algorithm that is proposed for such problem. Compared to previous works, our approach allows a wider exploration of the set of power solutions, while eliminating sources of numerical problems. The performance of the algorithm is assessed by tests over a set of large realistic instances of a Fixed WiMAX Network.

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