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.
|Number of pages||16|
|Journal||IEEE Transactions on Mobile Computing|
|Publication status||Published - 2022|
Bibliographical noteGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
- application layer coding
- convolutional codes
- data recovery
- erasure coding
- forward error correction
- fountain codes
- network measurements