Research Article
Intelligent Decision Modeling for Communication Parameter Selection via Back Propagation Neural Network
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@INPROCEEDINGS{10.1007/978-3-319-73317-3_53, author={Zheng Dou and Yaning Dong and Chao Li}, title={Intelligent Decision Modeling for Communication Parameter Selection via Back Propagation Neural Network}, proceedings={Advanced Hybrid Information Processing. First International Conference, ADHIP 2017, Harbin, China, July 17--18, 2017, Proceedings}, proceedings_a={ADHIP}, year={2018}, month={2}, keywords={Neural Network Decision making Cognitive radio Intelligent radio}, doi={10.1007/978-3-319-73317-3_53} }- Zheng Dou
Yaning Dong
Chao Li
Year: 2018
Intelligent Decision Modeling for Communication Parameter Selection via Back Propagation Neural Network
ADHIP
Springer
DOI: 10.1007/978-3-319-73317-3_53
Abstract
Decision-making ability plays a key role in the cognitive radio system. The decision-making engine is expected to decide a suitable radio configuration (modulation mode, coding mode, coding rate, etc.) according to the complex and varying radio environment. In this paper, we propose a decision-making method for the Orthogonal Frequency Division Multiplexing (OFDM) communication system. Through this method, we can select waveform parameters for any channel condition to achieve optimal communication performance via the Back Propagation (BP) Neural Network (NN) regression. The simulation results illustrate the proposed method can provide a reasonable decision surface with various wireless channel condition.
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