A reinforcement learning based collision avoidance mechanism to superposed LoRa signals in distributed massive IoT systems

抄録

For Massive IoT systems, various Low Power Wide Area (LPWA) systems have been developed and deployed, i.e., LoRa, SigFox, etc. In this paper, to avoid destructive collisions when multiple IoT LoRa signals simultaneously received in the same channel, we propose a Successive Interference Cancellation (SIC) based collision avoidance mechanism by accessing channel using reinforcement learning for distributed massive IoT systems. Simulation results show the effectiveness of our proposed mechanism in terms of Frame Success Rate (FSR).