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
LoRa performance analysis with superposed signal decoding
|Author:||de Souza Sant’Ana, Jean Michel1; Hoeller, Arliones1,2,3; Souza, Richard Demo2;|
1Centre for Wireless Communications, University of Oulu, Finland
2Dept. of Electrical and Electronics Engineering, Federal University of Santa Catarina, Florianóplis, Brazil
3Dept. of Telecommunications, Federal Institute for Education, Science, and Technology of Santa Catarina, São José, Brazil
4Programa Institucional de Fomento a la I+D+i (PIDi), Universidad Tecnológica Metropolitana, Santiago, Chile
|Online Access:||PDF Full Text (PDF, 0.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2020120399287
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2020-12-03
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.
IEEE wireless communications letters
|Pages:||1865 - 1868|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was partially supported in Brazil by CNPq, PrInt CAPES-UFSC “Automation 4.0”, INESC P&D Brasil (F-LOCO, Energisa, ANEEL PD-00405-1804/2018); in Finland by Academy of Finland, 6Genesis Flagship (Grant 318927), EE-IoT (Grant 319008), and FIREMAN (Grant 326301); in Chile by FONDECYT Postdoctoral (Grant 3170021) and FONDECYT Regular No. 1201893.
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
319008 (Academy of Finland Funding decision)
326301 (Academy of Finland Funding decision)
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