Achieving Low Queueing Latency in Time-Slotted LoRa Networks

LoRa, as a Low-Power Wide Area Networks (LP-WAN) technology, is extensively employed for connecting Internet of Things (IoT) applications. LoRa time-slotted networks have gained popularity due to their high channel utilization and robust anti-interference capability. However, the queueing latency of end-devices (EDs) in these networks is often overlooked in the time-slot-scheduled LoRa network, leading to data obsolescence and insufficient notification time. Existing research mainly focuses on reducing transmission delay and avoiding collisions in LoRa networks, while neglecting the importance of ensuring low queueing latency for EDs. In this paper, we propose a semidefinite relaxation (SDR)-based channel scheduler called Q-MAC to achieve low queueing latency in time-slotted LoRa networks. The core idea is to allocate time slots and channels effectively for packets while avoiding collisions. To accomplish this, we formulate an optimization model to minimize latency and packet collisions. This model is a multivariable-coupled non-convex integer problem, we transform the model into a Quadratically Constrained Quadratic Programming (QCQP) problem. Subsequently, we employ the SDR and heuristic algorithms to obtain feasible solutions. Simulation results demonstrate that Q-MAC can significantly reduce queueing latency, achieving an average improvement of 8.57 × compared to existing approaches.