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About Deepchannel: Wireless Channel Quality Prediction Using Deep Learning
This paper proposes DeepChannel, a deep learning model that uses an encoder-decoder architecture to predict wireless channel quality and signal strength variations based on past data. DeepChannel contains two variants, one using LSTM and one using GRU for the encoder and decoder. The model is evaluated on data from 4G LTE, WiFi, WiMAX, industrial and Zigbee networks across different sampling rates and mobility scenarios. Results show DeepChannel outperforms linear regression and ARIMA baselines in predicting future signal strength.
Detailed Information
Author: | ['chandru'] |
---|---|
Publication Year: | 2020 |
Pages: | 14 |
Language: | English |
Format: | |
Price: | FREE |
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