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

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 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 systems. Simulation results show effectiveness of our proposed terms Frame Success Rate (FSR).