A LoRaWAN Access Technology Based on Channel Adaptive Adjustment

Abstract

: Low-power wide area network (LPWAN) has developed rapidly in recent years and is widely used in various Internet of Things (IoT) services. In order to reduce cost and power consumption, wide coverage, LPWAN tends to use simple channel access control protocols, such as the Aloha protocol. This protocol is simple with poor extension capability. In high-density environment, Aloha protocol will lead to low channel utilization, prolonged access and high conflict probability. Therefore, in order to solve the above problems, we propose an enhanced channel access control mechanism based on the existing LoRaWAN protocol, that is, a dynamic listening backoff mechanism. We combine the improved “listen first and then talk” (LBT) mechanism with the current state of the channel to adaptively adjust the size of the backoff window. The theoretical analysis and simulation results show that the proposed mechanism have a better performance than the existing mechanism, it can reduce conflicts in dense environments. By comparison, the packet transmission success rate is increased by 17%.