An Optimization Model for Resource Allocation in Multitenant LoRaWAN Scenarios

Abstract

Long Range Wide Area Network (LoRaWAN) has emerged as a leading Low Power Wide Area Network (LPWAN) solution for enabling connectivity in Internet of Things (IoT) wireless networks. The network slicing paradigm facilitates multitenancy and allows heterogeneous applications with diverse Quality of Service (QoS) requirements to coexist in various IoT use cases. This article addresses the radio resource allocation problem in a multitenant LoRaWAN network, where each tenant may serve multiple applications supported by Network Slicing (NS). To this end, we propose an optimization model to determine the optimal channel and Spreading Factor (SF) allocation for each end device in a multioperator environment with heterogeneous applications. The model maximizes aggregated normalized throughput while ensuring fairness among Network Operators (NOs), employing linearization strategies to solve the problem efficiently. Our evaluation demonstrates the maximum achievable LoRaWAN network capacity to accommodate diverse IoT smart city applications from different tenants. The results confirm that optimal resource allocations can be achieved within reasonable time frames while meeting all requirements, including fair resource distribution among slices, compliance with regulatory constraints, such as duty cycle limitations, assurance of QoS metrics (throughput, delay, and packet delivery ratio) for each NO, and full isolation of resources allocated to different NOs.