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  4. A Maximum-Likelihood-based Multi-User LoRa Receiver Implemented in GNU Radio
 
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conference paper

A Maximum-Likelihood-based Multi-User LoRa Receiver Implemented in GNU Radio

Xhonneux, Mathieu
•
Tapparel, Joachim  
•
Afisiadis, Orion  
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January 1, 2020
2020 54Th Asilomar Conference On Signals, Systems, And Computers
54th Asilomar Conference on Signals, Systems, and Computers

LoRa is a popular low-power wide-area network (LPWAN) technology that uses spread-spectrum to achieve long-range connectivity and resilience to noise and interference. For energy efficiency reasons, LoRa adopts a pure ALOHA access scheme, which leads to reduced network throughput due to packet collisions at the gateways. To alleviate this issue, in this paper we analyze and implement a LoRa receiver that is able to decode LoRa packets from two interfering users. Our main contribution is a two-user detector derived in a maximum-likelihood fashion using a detailed interference model. As the complexity of the maximum-likelihood sequence estimation is prohibitive, a complexity-reduction technique is introduced to enable a practical implementation of the proposed two-user detector. This detector has been implemented along with an interference-robust synchronization algorithm on the GNU Radio software-defined radio (SDR) platform. The SDR implementation shows the effectiveness of the proposed method and also allows its experimental evaluation. Measurements indicate that our detector inherently leverages the time offset between the two colliding users to separate and demodulate their signals.

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Type
conference paper
DOI
10.1109/IEEECONF51394.2020.9443502
Web of Science ID

WOS:000681731800213

Author(s)
Xhonneux, Mathieu
•
Tapparel, Joachim  
•
Afisiadis, Orion  
•
Balatsoukas-Stimming, Alexios  
•
Burg, Andreas  
Date Issued

2020-01-01

Publisher

IEEE

Publisher place

New York

Journal
2020 54Th Asilomar Conference On Signals, Systems, And Computers
ISBN of the book

978-0-7381-3126-9

Series title/Series vol.

Conference Record of the Asilomar Conference on Signals Systems and Computers

Start page

1106

End page

1111

Subjects

Computer Science, Information Systems

•

Computer Science, Software Engineering

•

Engineering, Electrical & Electronic

•

Imaging Science & Photographic Technology

•

Telecommunications

•

Computer Science

•

Engineering

Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
TCL  
Event nameEvent placeEvent date
54th Asilomar Conference on Signals, Systems, and Computers

ELECTR NETWORK

Nov 01-05, 2020

Available on Infoscience
September 11, 2021
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/181295
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