LoRaWAN (Long Range Wide Area Network) is an attractive network infrastructure and protocol suite for ultra low power Internet of Things devices. Even if the technology itself is quite mature and specified, the currently deployed wireless resource allocation strategies are still coarse and based on rough heuristics. This paper proposes an innovative “sequential waterfilling” strategy for assigning spreading factors to End Devices. Our design relies on three complementary approaches: i) equalize the Time-on-Air of packets transmitted by the system’s End Devices in each spreading factor’s group; ii) balance the spreading factors across multiple gateways and iii) keep into account the channel capture, which our experimental results show to be very substantial in LoRa. While retaining an extremely simple and scalable implementation, this strategy yields a significant improvement (up to 38%) in the network capacity over the Adaptive Data Rate used by many network operators on the basis of the design suggested by Semtech, and appears to be extremely robust to different operating/load conditions and network topology configurations.

Garlisi D., Tinnirello I., Bianchi G., Cuomo F. (2020). Capture Aware Sequential Waterfilling for LoRaWAN Adaptive Data Rate. IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 20(3), 2019-2033 [10.1109/TWC.2020.3038638].

Capture Aware Sequential Waterfilling for LoRaWAN Adaptive Data Rate

Garlisi D.;Tinnirello I.;Bianchi G.;
2020-01-01

Abstract

LoRaWAN (Long Range Wide Area Network) is an attractive network infrastructure and protocol suite for ultra low power Internet of Things devices. Even if the technology itself is quite mature and specified, the currently deployed wireless resource allocation strategies are still coarse and based on rough heuristics. This paper proposes an innovative “sequential waterfilling” strategy for assigning spreading factors to End Devices. Our design relies on three complementary approaches: i) equalize the Time-on-Air of packets transmitted by the system’s End Devices in each spreading factor’s group; ii) balance the spreading factors across multiple gateways and iii) keep into account the channel capture, which our experimental results show to be very substantial in LoRa. While retaining an extremely simple and scalable implementation, this strategy yields a significant improvement (up to 38%) in the network capacity over the Adaptive Data Rate used by many network operators on the basis of the design suggested by Semtech, and appears to be extremely robust to different operating/load conditions and network topology configurations.
2020
Garlisi D., Tinnirello I., Bianchi G., Cuomo F. (2020). Capture Aware Sequential Waterfilling for LoRaWAN Adaptive Data Rate. IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 20(3), 2019-2033 [10.1109/TWC.2020.3038638].
File in questo prodotto:
File Dimensione Formato  
1907.12360.pdf

accesso aperto

Tipologia: Pre-print
Dimensione 1.38 MB
Formato Adobe PDF
1.38 MB Adobe PDF Visualizza/Apri
Capture_Aware_Sequential_Waterfilling_for_LoRaWAN_Adaptive_Data_Rate.pdf

Solo gestori archvio

Tipologia: Versione Editoriale
Dimensione 3.83 MB
Formato Adobe PDF
3.83 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/494826
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 24
  • ???jsp.display-item.citation.isi??? 20
social impact