<abstract xmlns="http://www.w3.org/1999/xhtml"><p>LoRa technology is derived from chirp spread spectrum (CSS) having embedded forward error correction (FEC). A wide band is used for transmissions to counter interference and to handle frequency offsets. The paper investigates low power wide area networks (LPWAN) transmissions in the uplink, where the end nodes are powered by using energy harvested from the surroundings. Long-range (LoRa) networks demonstrate their capability to support Internet of Things (IoT) applications, where the end nodes utilize the harvested energy for transmission to gateways using different spreading factor (<italic>SF</italic>) codes. The work fairly improves the throughput of the LoRa nodes while keeping the other parameters, like time duration of the energy harvesting (<italic>EH</italic>), <italic>SF</italic>, and transmit power, optimally. Initially, a mathematical expression is derived for collisions between packets of the end nodes; keeping this as an important factor, an algorithm is proposed that fairly assigns <italic>SFs</italic> to the nodes. Simulation results confirm the improvement in packet error rate and time on air when fewer LoRa nodes are used for lower <italic>SFs</italic>, as compared to higher <italic>SFs</italic>. The number of LoRa nodes that can communicate using <italic>SF</italic> = 7 is almost four times as compared to using <italic>SF</italic> = 11, while maintaining a low packet error rate. Also, for <italic>SF</italic> = 7, changing the coding rate from 1 to 4 increases time on air by around 20 ms, while time on air increases by 1,200 ms for <italic>SF</italic> = 12. The energy efficiency is also compared for different <italic>SFs</italic> and different transmission powers. A lower <italic>SF</italic> and lower transmission powers are more suitable for smaller distance and provides better energy efficiency.</p></abstract>

LoRa technology is derived from chirp spread spectrum (CSS) having embedded forward error correction (FEC). A wide band is used for transmissions to counter interference and to handle frequency offsets. The paper investigates low power wide area networks (LPWAN) transmissions in the uplink, where the end nodes are powered by using energy harvested from the surroundings. Long-range (LoRa) networks demonstrate their capability to support Internet of Things (IoT) applications, where the end nodes utilize the harvested energy for transmission to gateways using different spreading factor (SF) codes. The work fairly improves the throughput of the LoRa nodes while keeping the other parameters, like time duration of the energy harvesting (EH), SF, and transmit power, optimally. Initially, a mathematical expression is derived for collisions between packets of the end nodes; keeping this as an important factor, an algorithm is proposed that fairly assigns SFs to the nodes. Simulation results confirm the improvement in packet error rate and time on air when fewer LoRa nodes are used for lower SFs, as compared to higher SFs. The number of LoRa nodes that can communicate using SF = 7 is almost four times as compared to using SF = 11, while maintaining a low packet error rate. Also, for SF = 7, changing the coding rate from 1 to 4 increases time on air by around 20 ms, while time on air increases by 1,200 ms for SF = 12. The energy efficiency is also compared for different SFs and different transmission powers. A lower SF and lower transmission powers are more suitable for smaller distance and provides better energy efficiency.

Energy harvested end nodes and performance improvement of LoRa networks

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

running-head

LoRa technology is derived from chirp spread spectrum (CSS) having embedded forward error correction (FEC). A wide band is used for transmissions to counter...

Notation	Definition
R_c	Chip rate
T_c	Chip duration
R_s	Symbol rate
T_s	Symbol duration
R_b	Data rate
SF	Spreading factor
CR	Coding rate
t_ai	Time on air of ith node

Energy harvested end nodes and performance improvement of LoRa networks

Data publikacji: 01 mar 2021

Zakres stron: 1 - 15

Otrzymano: 15 lis 2020

DOI: https://doi.org/10.21307/ijssis-2021-002

Słowa kluczowe
LoRa, IoT, Energy harvesting, LoRaWAN, ToA, Gateway, Smart sensors

© 2021 Gunjan Gupta et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Energy harvested end nodes and performance improvement of LoRa networks

Data publikacji: 01 mar 2021

Zakres stron: 1 - 15

Otrzymano: 15 lis 2020

DOI: https://doi.org/10.21307/ijssis-2021-002

Słowa kluczoweLoRa, IoT, Energy harvesting, LoRaWAN, ToA, Gateway, Smart sensors

© 2021 Gunjan Gupta et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Figure 2:

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Figure 13:

Notations.

Słowa kluczowe
LoRa, IoT, Energy harvesting, LoRaWAN, ToA, Gateway, Smart sensors