Abstract:So far, most researches on LoRa technology are about single-application oriented IoT, low utilization of configurable parameters leaves room for further optimization of network performance. In order to adapt to the growing transmission requirements of heterogeneous multi-type services, it is increasing essential to optimize the performance of the LoRa network. To address the above issue, a dynamic parameters adaptive configuration strategy based on simulated annealing genetic algorithm is proposed, which can improve the number of end devices and data throughput supported by single gateway LoRa network while limiting energy consumption. The simulation results based on LoRaSim reveal that the proposed method outperforms ADR by 25.6%. By simulating the single gateway LoRa network of nearly over 1000 devices, the experimental results show that when packet generation rate 1/100 s, dynamic parameters adaptive configuration strategy proposed in this study can guarantee PDR above 90%. This method can adapt to the data transmission needs of multi-heterogeneous applications and effectively improve the data throughput while ensuring the PDR of each applications.