用RBF神经网络算法设计CR认知引擎

doi:10.3969/j.issn.1001-2400.2011.01.026

Abstract

Abstract:

Cognitive radio (CR) is an intelligent wireless communication system, and the design of a cognitive engine is one of the key issues. The cognitive engine can utilize the reasoning and learning methods to achieve the perception, adaptation and learning ability. This paper presents a design scheme for the cognitive engine based on the RBF neural network (RBF-NN) to adapt varied wireless environment according to experiential knowledge. A CR simulation cognitive engine is realized using the 802.11a simulation platform by collecting data and training the NN to learn channel characteristics. Under the premise of studying the sensation information, CR reconfiguration is realized according to the user's needs. Simulation results show that the proposed cognitive engine can effectively realize the study and reconfiguration function, and that the prediction accuracy is higher than that of the BP NN model by 10%～30%.

Key words: cognitive radio, cognitive engine, modulation, neural networks

JIANG Hong;MA Jinghui;HUANG Yuqing;WU Chun. Design of cognitive engine for CR using the RBF neural network[J].J4, 2011, 38(1): 159-164+170.

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Design of cognitive engine for CR using the RBF neural network

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