Design of cognitive engine for cognitive radio based on the rough sets and radial basis function neural network

Yanchao Yang; Hong Jiang; Congbin Liu; Zhongli Lan

doi:10.1117/12.2010549

14 March 2013 Design of cognitive engine for cognitive radio based on the rough sets and radial basis function neural network

Yanchao Yang, Hong Jiang, Congbin Liu, Zhongli Lan

Author Affiliations +

Proceedings Volume 8768, International Conference on Graphic and Image Processing (ICGIP 2012); 876809 (2013) https://doi.org/10.1117/12.2010549
Event: 2012 International Conference on Graphic and Image Processing, 2012, Singapore, Singapore

Abstract

Cognitive radio (CR) is an intelligent wireless communication system which can dynamically adjust the parameters to improve system performance depending on the environmental change and quality of service. The core technology for CR is the design of cognitive engine, which introduces reasoning and learning methods in the field of artificial intelligence, to achieve the perception, adaptation and learning capability. Considering the dynamical wireless environment and demands, this paper proposes a design of cognitive engine based on the rough sets (RS) and radial basis function neural network (RBF_NN). The method uses experienced knowledge and environment information processed by RS module to train the RBF_NN, and then the learning model is used to reconfigure communication parameters to allocate resources rationally and improve system performance. After training learning model, the performance is evaluated according to two benchmark functions. The simulation results demonstrate the effectiveness of the model and the proposed cognitive engine can effectively achieve the goal of learning and reconfiguration in cognitive radio.

Citation Download Citation

Yanchao Yang, Hong Jiang, Congbin Liu, and Zhongli Lan "Design of cognitive engine for cognitive radio based on the rough sets and radial basis function neural network", Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 876809 (14 March 2013); https://doi.org/10.1117/12.2010549

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available