Wireless Channel Identification Algorithm Based on Feature Extraction and BP Neural Network | Zendy

Dengao Li | Zendy; Gang Wu | Zendy; Jumin Zhao | Zendy; Wenhui Niu | Zendy; Qi Liu | Zendy

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Wireless Channel Identification Algorithm Based on Feature Extraction and BP Neural Network

Author(s) -

Dengao Li,

Gang Wu,

Jumin Zhao,

Wenhui Niu,

Qi Liu

Publication year - 2017

Publication title -

journal of information processing systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.288

H-Index - 23

eISSN - 2092-805X

pISSN - 1976-913X

DOI - 10.3745/jips.03.0063

Subject(s) - computer science , identification (biology) , artificial neural network , channel (broadcasting) , feature extraction , pattern recognition (psychology) , artificial intelligence , wireless , algorithm , data mining , computer network , telecommunications , botany , biology

Effective identification of wireless channel in different scenarios or regions can solve the problems of multipath interference in process of wireless communication. In this paper, different characteristics of wireless channel are extracted based on the arrival time and received signal strength, such as the number of multipath, time delay and delay spread, to establish the feature vector set of wireless channel which is used to train backpropagation (BP) neural network to identify different wireless channels. Experimental results show that the proposed algorithm can accurately identify different wireless channels, and the accuracy can reach 97.59%.

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