1 research outputs found
Deep Neural Network Aided Scenario Identification in Wireless Multi-path Fading Channels
This letter illustrates our preliminary works in deep nerual network (DNN)
for wireless communication scenario identification in wireless multi-path
fading channels. In this letter, six kinds of channel scenarios referring to
COST 207 channel model have been performed. 100% identification accuracy has
been observed given signal-to-noise (SNR) over 20dB whereas a 88.4% average
accuracy has been obtained where SNR ranged from 0dB to 40dB. The proposed
method has tested under fast time-varying conditions, which were similar with
real world wireless multi-path fading channels, enabling it to work feasibly in
practical scenario identification.Comment: Draft of a four-page letter with 8 figure