LAUSR

LoRaWAN is a remarkable network protocol to support the deployment of low-power wide-area network applications for the Internet of Things. Its modulation scheme, LoRa, uses different transmission parameters to allow long-range bidirectional communication by trading-off range for Time on Air (ToA). The LoRaWAN specification suggests using an adaptive data rate (ADR) algorithm to assign transmission parameters to nodes dynamically. The ADR algorithm used by The Things Network, a global open network, selects transmission parameters for communication without disconnection while lowering ToA and energy consumption. However, its often optimistic link quality estimate drives the assignment of inadequate parameters, especially in lossy channels. More precise channel quality estimates would improve resource allocation at the cost of increased complexity at the network server (NS). Through simulations, we observe that we can use the ADR link margin parameter to compensate for inaccurate link quality estimates, providing better service to nodes and maintaining low levels of energy consumption. In this work, we propose a modification to ADR that allows the selection of the link margin at runtime, increasing the network performance without the need of any prior knowledge and with no increase in the NS computational complexity.