Paper Info
Title
Implementation of a genetic algorithm-based decision making framework for opportunistic radio
Abstract
The cognitive radio (CR) is known as a radio that can reconfigure its transceiver parameters based on the environmental awareness. The opportunistic radio (OR) is considered in this work, with a narrower definition where the awareness is limited to the spectrum knowledge. The decision making framework is employed as a crucial entity to control the behaviour of the OR. The main purpose is to enable an efficient spectrum usage while avoiding the interference to other users. This study describes the proposed OR decision making framework including the flow of context information as an input process to the decision making engine, the context filtering and the reasoning mechanisms in which the decision optimisation is achieved using a genetic algorithm (GA)-based approach. The system stability of the GA-based reasoning engine is tested through simulations. Then, the experimental study is performed on a test platform for a practical proof of the concept. The test platform is based on the Ettus USRP (Universal Software Radio Peripheral) hardware and the GNU Radio open source software. Several tests were carried out to observe the OR capabilities of the proposed decision making framework. Test environment settings together with the observation results are provided in this study, covering the spectrum sensing and opportunistic channel allocation in the industrial, scientific and medical (ISM) band of 2.4 GHz.
Year
DOI
Venue
2010
10.1049/iet-com.2009.0479
IET Communications
Keywords
Field
DocType
cognitive radio,decision making,genetic algorithms,inference mechanisms,transceivers,Ettus universal software radio peripheral hardware,GNU radio open source software,cognitive radio,context filtering,context information,decision making engine,environmental awareness,genetic algorithm,opportunistic radio,reasoning mechanisms,spectrum knowledge,transceiver parameters
Semantic reasoner,Transceiver,Software-defined radio,Computer science,Decision support system,Universal Software Radio Peripheral,Computer network,Real-time computing,Channel allocation schemes,Genetic algorithm,Cognitive radio
Journal
Volume
Issue
ISSN
4
5
1751-8628
Citations 
PageRank 
References 
7
0.46
4
Authors
2
Name
Order
Citations
PageRank
S. Chantaraskul1193.23
K. Moessner214423.09