Exploiting chirp spread spectrum and error detection in LoRa collision recovery
Abstract/Contents
- Abstract
- LoRa is a prominent radio technology for wide-area IoT applications. LoRa allows a gateway to receive packets from low-power transmitters over a range of miles. But when two transmissions collide, the gateway loses one or both of them. Collisions waste airtime and energy. This dissertation proposes two novel cross-layer techniques that enable LoRa receivers to successfully receive colliding packets with high probability. The first, called symbol querying, changes the interface between the LoRa demodulator and decoder. Symbol querying greatly improves the ability of a LoRa receiver to successfully receive the stronger frame in a collision. It does so by elevating the error detection capabilities of channel coding into error correction. For instance, a receiver using (8, 4)-extended Hamming codes can correct two, instead of only one, bit errors per codeword. The second technique, called symbol SIC, uses the unique discrete properties of LoRa symbols to enable the efficient reception of the weaker frame in a collision, by subtracting the stronger frame's peaks in the frequency domain. This dissertation presents a prototype LoRa receiver that includes symbol querying and symbol SIC using an inexpensive, off-the-shelf software-defined radio (SDR). When receiving colliding frames, this implementation receives up to 17x more frames than traditional LoRa receivers and symbol querying cuts the energy costs of communication by up to 4.6x compared to an SIC-only design.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2021; ©2021 |
| Publication date | 2021; 2021 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Jung, Raejoon |
|---|---|
| Degree supervisor | Levis, Philip |
| Thesis advisor | Levis, Philip |
| Thesis advisor | Bambos, Nicholas |
| Thesis advisor | Jamieson, Kyle |
| Degree committee member | Bambos, Nicholas |
| Degree committee member | Jamieson, Kyle |
| Associated with | Stanford University, Department of Electrical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Raejoon Jung. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2021. |
| Location | https://purl.stanford.edu/dp797rg4331 |
Access conditions
- Copyright
- © 2021 by Raejoon Jung
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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