Design of cognitive radio engine using artificial bee colony algorithm

Author

Pradhan, Pyari Mohan

Author_Institution

Sch. of Electr. Sci., Indian Inst. of Technol. Bhubaneswar, Bhubaneswar, India

fYear

2011

fDate

28-30 Dec. 2011

Firstpage

1

Lastpage

4

Abstract

A cognitive radio engine adapts its radio parameters using metaheauristic learning algorithms in order to satisfy certain objectives in a radio environment. In this study, three evolutionary algorithms are used for optimizing the predefined fitness functions in the time varying wireless environment. The performances of genetic algorithm, particle swarm optimization and artificial bee colony algorithm are analysed in different modes of operation and in presence of spectral interference. The simulation results are compared using convergence characteristics and two statistical metrics.

Keywords

cognitive radio; genetic algorithms; particle swarm optimisation; radiofrequency interference; statistical analysis; artificial bee colony algorithm; cognitive radio engine; evolutionary algorithm; fitness function; genetic algorithm; metaheauristic learning; particle swarm optimization; radio environment; radio parameter; spectral interference; statistical metrics; time varying wireless environment; Algorithm design and analysis; Cognitive radio; Convergence; Engines; Genetic algorithms; Interference; OFDM; Cognitive radio engine; artificial bee colony algorithm; evolutionary algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Energy, Automation, and Signal (ICEAS), 2011 International Conference on

Conference_Location

Bhubaneswar, Odisha

Print_ISBN

978-1-4673-0137-4

Type

conf

DOI

10.1109/ICEAS.2011.6147139

Filename

6147139