Using Omnidirectional BTS and Different Evolutionary Approaches to Solve the RND Problem

RND (Radio Network Design) is an important problem in mobile telecommunications (for example in mobile/cellular telephony), being also relevant in the rising area of sensor networks. This problem consists in covering a certain geographical area by using the smallest number of radio antennas achieving the biggest cover rate. To date, several radio antenna models have been used: square coverage antennas, omnidirectional antennas that cover a circular area, etc. In this work we use omnidirectional antennas. On the other hand, RND is an NP-hard problem; therefore its solution by means of evolutionary algorithms is appropriate. In this work we study different evolutionary approaches to tackle this problem. PBIL (Population-Based Incremental Learning) is based on genetic algorithms and competitive learning (typical in neural networks). DE (Differential Evolution) is a very simple population-based stochastic function minimizer used in a wide range of optimization problems, including multi-obj...

• Type: Conference
• Year: 2007
• Where: EUROCAST
• Authors: Miguel A. Vega-Rodríguez, Juan Antonio Gómez Pulido, Enrique Alba, David Vega-Pérez, Silvio Priem-Mendes, Guillermo Molina
• Keywords: EUROCAST 2007, Evolutionary Algorithm, Hardware, Omnidirectional Antennas, Radio Antenna