|
|
LoRa performance analysis with superposed signal decoding |
|---|---|
| Author: | de Souza Sant’Ana, Jean Michel1; Hoeller, Arliones1,2,3; Souza, Richard Demo2; |
| Organizations: |
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
|
| Format: | article |
| Version: | accepted version |
| Access: | open |
| Online Access: | PDF Full Text (PDF, 0.3 MB) |
| Persistent link: | http://urn.fi/urn:nbn:fi-fe2020120399287 |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers,
2020
|
| Publish Date: | 2020-12-03 |
| Description: |
AbstractThis 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. see all
|
| Series: |
IEEE wireless communications letters |
| ISSN: | 2162-2337 |
| ISSN-E: | 2162-2345 |
| ISSN-L: | 2162-2337 |
| Volume: | 9 |
| Issue: | 1 |
| Pages: | 1865 - 1868 |
| DOI: | 10.1109/LWC.2020.3006588 |
| OADOI: | https://oadoi.org/10.1109/LWC.2020.3006588 |
| Type of Publication: |
A1 Journal article – refereed |
| Field of Science: |
213 Electronic, automation and communications engineering, electronics |
| Subjects: | |
| Funding: |
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 319008 326301 |
| Detailed Information: |
318927 (Academy of Finland Funding decision) 319008 (Academy of Finland Funding decision) 326301 (Academy of Finland Funding decision) |
| Copyright information: |
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |