Effects on Age of Information From Forward Error Correction in LoRa Transmissions

• Published in: IEEE sensors journal Vol. 24; no. 19; pp. 30853 - 30862
• Main Authors: Chache, Frederick M., Maxon, Sean, Narayanan, Ram M., Bharadwaj, Ramesh
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Age of information (AoI); Algorithms; channel coding; Communication; Error correction; Error correction & detection; Forward error correction; forward error correction (FEC); Hamming codes; Information age; long range (LoRa); LoRa; Modelling; Packet transmission; Parity check codes; Sensors; Signal to noise ratio; Symbols; Wireless sensor networks
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2024.3442917

This article focuses on modeling the effects of coding rates (CR) on the age of information (AoI) of data from low-powered sensors communicating over long-range (LoRa) radio frequency (RF) modulation and comparing them to experimental data we collected. AoI is an increasingly popular metric for measuring the performance of wireless sensor networks (WSNs) and little literature exists to study the effects that the CR has on the AoI. We advanced current closed-form expressions to estimate the average AoI for a node transmitting over LoRa as a function of the average CR of packets transmitted and the signal-to-noise ratio (SNR). Traditionally, LoRaWAN uses Hamming codes; in this work, we used Reed-Solomon encoding to allow for the correction of multiple errors in a packet, which is in line with more modern forward error correction (FEC) algorithms. To verify the modeling, data were collected with off-the-shelf LoRa transceivers. This modeling and testing showed that, due to FEC overhead, for a given SNR, there exists a CR that minimizes the AoI of the data. With this information, algorithms were developed to automatically adapt the CR during transmission as the nodes move relative to one another. This allows them to adjust to changes in the channel SNR and minimize the AoI of sensor data.