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

## TL;DR

This paper introduces a novel genetic algorithm designed to efficiently solve large-scale wireless network design problems, specifically focusing on power, frequency, and modulation assignment, demonstrating improved exploration and numerical stability.

## Contribution

First genetic algorithm tailored for large-scale wireless network design problems, enhancing solution exploration and numerical stability over previous methods.

## Key findings

- Effective in solving large realistic WiMAX network instances
- Outperforms previous approaches in solution quality and stability
- Enables wider exploration of power solutions

## Abstract

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.