DaRe

Data Recovery Through Application Layer Coding for LoRaWAN

Journal Article (2022)
Author(s)

Paul Marcelis (Student TU Delft)

Nikolaos Kouvelas (TU Delft - Embedded Systems)

Vijay Rao (TU Delft - Embedded Systems, Cognizant Technology Solutions)

RR Venkatesha Prasad (TU Delft - Embedded Systems)

Research Group
Embedded Systems
Copyright
© 2022 Paul J. Marcelis, N. KOUVELAS, V.S. Rao, Ranga Rao Venkatesha Prasad
DOI related publication
https://doi.org/10.1109/TMC.2020.3016654
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Paul J. Marcelis, N. KOUVELAS, V.S. Rao, Ranga Rao Venkatesha Prasad
Research Group
Embedded Systems
Issue number
3
Volume number
21
Pages (from-to)
895-910
Reuse Rights

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Abstract

Long-range wide-area network (LoRaWAN) is an energy-efficient and inexpensive networking technology that is rapidly being adopted for many Internet-of-Things applications. In this study, we perform extensive measurements on a new LoRaWAN deployment to characterise the spatio-temporal properties of the LoRaWAN channel. Our experiments reveal that LoRaWAN frames are mostly lost due to the channel effects, which are adverse when the end-devices are mobile. The frame losses are up to 70 percent, which can be bursty for both mobile and stationary scenarios. Frame losses result in data losses since the frames are transmitted only once in the basic configuration. To reduce data losses in LoRaWAN, we design a novel coding scheme for data recovery called DaRe that works on the application layer. DaRe combines techniques from convolutional and fountain codes. By implementing DaRe, we show that 99 percent of the data can be recovered with a code rate of 1/2 when the frame loss is up to 40 percent. Compared to the repetition coding scheme, DaRe provides 21 percent higher data recovery and can save up to 42 percent of the energy consumed on a transmission for 10-byte data units. We also show that DaRe provides better resilience to bursty frame losses.

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