Comparative Analysis of Resource Allocation Strategies in LoRa Networks: Optimizing Performance and Power Efficiency

Internet-of-things (IoT) systems are expected to be integral to every aspect of human life. The number of IoT applications is exponentially growing, especially the low-power wide-area network (LPWAN). LPWAN is an emerging IoT networking paradigm with three main characteristics: low-cost, large-scale deployment, and high energy efficiency. IoT systems are becoming more and more important in a variety of areas, and LPWAN are essential because of their affordability, scalability, and energy efficiency (EE). One of the most popular LPWAN technologies, LoRaWAN, has performance issues with resource allocation (RA). This article investigates the architecture of the LoRaWAN network, emphasizing its primary resources and their characteristics. We classify current RA approaches, talk about important obstacles, and investigate future perspectives for LoRaWAN RA research. We also report a case study that improves resource distribution in LoRa networks by applying Spreading Factor Optimization (SFO) and the Hungarian algorithm. Our results demonstrate that, in comparison to conventional methods, the suggested SFO and Hungarian-based RA algorithms efficiently lower power consumption and enhance EE.