Channel Activity Detection with the Modified Backoff Algorithm for LoRaWAN

Long Range Wide Area Network (LoRaWAN) is one of the leading technologies to support Internet of Things (IoT). To enhance the scalability of LoRaWAN, the Channel Activity Detection (CAD) or Listen Before Talk (LBT) mode can help decreasing collisions among packets. In this paper, the modified backoff algorithm so called CAD-MB is proposed to enhance the CAD performance. The main concept of this algorithm is to implement the CAD with two main backoff delays. The first backoff delay is activated before the first CAD, while the second backoff delay is activated after the channel is found occupied. The results show that our algorithm can outperform the Exponential-AT and CSMA-10 by reducing the average queuing delay up to 51% and 95%, respectively. It also slightly improves the amount of packet received rate without jeopardizing the energy consumption.