Lora channel propagation modelling using artificial neural network
In Long Range (LoRa) wireless communication, the transmitted signals may experience loss due to many obstacles as well as interferences. The existing path loss propagation models which used for applications as the one used for LoRa networks are designed...
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| Main Authors: | , , , |
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| Format: | Proceeding Paper |
| Language: | en en |
| Published: |
IEEE
2021
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/90600/1/09467234.pdf http://irep.iium.edu.my/90600/7/90600_LoRa%20Channel%20Propagation%20Modelling_schedule.pdf http://irep.iium.edu.my/90600/ https://ieeexplore-ieee-org.ezlib.iium.edu.my/document/9467234 |
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| Summary: | In Long Range (LoRa) wireless communication,
the transmitted signals may experience loss due to many obstacles as well as
interferences. The existing path loss propagation models which used for applications as
the one used for LoRa networks are designed to make it simple for calculation
and thus making it less accurate. Enabling technology such as artificial
intelligence is capable to process complex variables in a very short duration with almost
accurate prediction. By having enough data or collecting more data over certain period, this
technology can be implemented to learn all the data rules and behavior to predict the output. In
this paper, the Artificial Neural network model is proposed to predict the propagation loss of
LoRa communication link. Results are compared against path loss propagation models and
RMSE values are also determined. The proposed model shows improvement compared with
other models in terms of Received Signal Strength Indicator (RSSI) performance and RMSE
values. |
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