Adaptive Data Rate Techniques for Energy Constrained Ad Hoc LoRa Networks

Long Range (LoRa) is an emerging low-power wide-area network technology. LoRa messages can be transmitted with a variety of parameters including transmit power, spreading factor, bandwidth, and error coding rates. While adaptive data rate (ADR) capabilities exist in the LoRa wide-area network (LoRaWAN) specification, this work is motivated by a cattle monitoring application where LoRaWAN is not feasible. In this scenario, the mobility of the animal changes the optimal parameter selections, which are the settings that transmit the data with the lowest energy consumption. This work analyzes ADR techniques to most efficiently find the optimal data rate for a firmware update, although the techniques are still valid for any large data exchange. It extends the ADR to use frequency shift keying (FSK) when there is enough signal strength since Semtech LoRa integrated circuits support FSK mode. The work uses dynamic acknowledgements and timeout values to improve the convergence time. The paper experimentally validates an analytical transmit time model and then describes three different methods for accomplishing the adaptive data rate. The methods are modeled analytically for the different convergence settings and two are demonstrated using the Microchip SAMR34 Explained boards.

[1]  Younghwan Yoo,et al.  Contention-Aware Adaptive Data Rate for Throughput Optimization in LoRaWAN , 2018, Sensors.

[2]  Sergio F. Ochoa,et al.  A LoRa-Based Communication System for Coordinated Response in an Earthquake Aftermath , 2019, UCAmI.

[3]  Utz Roedig,et al.  Do LoRa Low-Power Wide-Area Networks Scale? , 2016, MSWiM.

[4]  Fernand Meyer,et al.  A comparative study of LPWAN technologies for large-scale IoT deployment , 2019, ICT Express.

[5]  Filip Lemic,et al.  Empirical Analysis of LoRaWAN Adaptive Data Rate for Mobile Internet of Things Applications , 2019, S3@MobiCom.

[6]  Luca Rugini,et al.  An IoT Architecture for Continuous Livestock Monitoring Using LoRa LPWAN , 2019, Electronics.

[7]  Vojtech Hauser,et al.  Proposal of Adaptive Data Rate Algorithm for LoRaWAN-Based Infrastructure , 2017, 2017 IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud).

[8]  Jean-Jacques Chaillout,et al.  Energy Consumption Model for Sensor Nodes Based on LoRa and LoRaWAN , 2018, Sensors.

[9]  Dirk Pesch,et al.  Fair Adaptive Data Rate Allocation and Power Control in LoRaWAN , 2018, 2018 IEEE 19th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM).

[10]  Usman Raza,et al.  How Agile is the Adaptive Data Rate Mechanism of LoRaWAN? , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[11]  Mario Di Francesco,et al.  Adaptive configuration of lora networks for dense IoT deployments , 2018, NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium.

[12]  Vishal Sharma,et al.  LoRaWAN-Based Energy-Efficient Surveillance by Drones for Intelligent Transportation Systems , 2018 .

[13]  Utz Roedig,et al.  LoRa Transmission Parameter Selection , 2017, 2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS).

[14]  Carles Gomez,et al.  Modeling the Energy Performance of LoRaWAN , 2017, Sensors.