LoRa performance analysis with superposed signal decoding

de Souza Sant’Ana, Jean Michel; Hoeller, Arliones; Souza, Richard Demo; Alves, Hirley; Montejo-Sánchez, Samuel (2020-07-02)
 
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https://doi.org/10.1109/LWC.2020.3006588

de Souza Sant’Ana, Jean Michel
Hoeller, Arliones
Souza, Richard Demo
Alves, Hirley
Montejo-Sánchez, Samuel
Institute of Electrical and Electronics Engineers
02.07.2020

J. M. de Souza Sant’Ana, A. Hoeller, R. D. Souza, H. Alves and S. Montejo-Sánchez, "LoRa Performance Analysis with Superposed Signal Decoding," in IEEE Wireless Communications Letters, vol. 9, no. 11, pp. 1865-1868, Nov. 2020, doi: 10.1109/LWC.2020.3006588

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doi:https://doi.org/10.1109/LWC.2020.3006588
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Abstract

This letter considers the use of successive interference cancellation (SIC) to decode superposed signals in Long Range (LoRa) networks. We build over a known stochastic geometry model for LoRa networks and include the effect of recovering colliding packets through SIC. We derive closed-form expressions for the successful decoding of packets using SIC taking path loss, fading, noise, and interference into account, while we validate the model by means of Monte Carlo simulations. Results show that SIC-enabled LoRa networks improve worst-case reliability by up to 34%. We show that, for at least one test scenario, SIC increases by 159% the number of served users with the same worst-case reliability level.

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