Modeling and Throughput Optimization of Multi-Gateway LoRaWAN

Abstract

Low power wide area network (LPWAN) technologies have become an integral part of Internet-of-Things (IoT) applications due to their ability to meet key requirements such as long range, low cost, massive device numbers, and low energy consumption. Among all available LPWAN technologies, LoRaWAN has garnered significant interest from both industry and academia. Due to wide communication range of LoRaWAN, the coverage of gateway (GW) may overlap and the packet transmissions from nodes in the overlapping area would collide, which deteriorates the network performance. How to tune the backoff parameter settings to reduce collision and maximize the network throughput in multi-GW LoRaWAN is still an open issue. To solve this issue, in this paper, we first propose a low-complexity model for multi-GW LoRaWAN, which divides nodes into different groups based on GWs they can communicate with. Key performance metrics, i.e., the network throughput, access delay and the probability of successful transmission, are derived as functions of backoff parameter and input rate. As the throughput performance crucially depends on whether each group is saturated or not, we propose an iterative algorithm to analyze the stability of the multi-GW LoRaWAN, based on which we further develop an iterative algorithm to tune the backoff parameter of each group iteratively for the network throughput optimization. The simulation results validate the effectiveness of the proposed algorithms and reveal the trade-off between fairness and efficiency.

Keywords

• LoRaWAN
• multi-gateway network
• throughput optimization
• modeling
• joint packet decoding
• random access