Conference Papers Year : 2021

Recovering Colliding LoRa Frames from Uncertainties Using LoRa Coding

Abstract

LoRa is one of the leading technologies for Low-Power Wide Area Networks and the Internet of Things. Collisions in LoRa might cause retransmissions, which negatively impact the network performance and scalability. Several algorithms have been proposed to decode colliding frames under specific conditions. However, there remain indistinguishable frames due to uncertainties in some or all symbols. In this paper, we propose a general algorithm that significantly improves the recovery capabilities of existing algorithms by leveraging the LoRa coding techniques. Simulation results show that our algorithm can significantly reduce the number of the failed decoding of LoRa frames and improve the performance of the network.
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Dates and versions

hal-03412369 , version 1 (08-12-2021)

Identifiers

Cite

Weixuan Xiao, Nancy El Rachkidy, Alexandre Guitton. Recovering Colliding LoRa Frames from Uncertainties Using LoRa Coding. IEEE Conference on Local Computer Networks, Oct 2021, Edmonton, Canada. pp.327-330, ⟨10.1109/LCN52139.2021.9524949⟩. ⟨hal-03412369⟩
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