An Enhanced Energy-Saving Algorithm for Narrowband Internet of Thing’s Indoor Localization Based on Convex Optimization

The narrowband Internet of Things’ (NB-IoT) algorithm must be streamlined to manage service quality and maximize network performance as the number of devices continuous to grow. In this paper, we proposed a convex optimization model for distributing multiple sources using the Karun-Kush-Tucker (KKT) conditions in networks with a single energy-harvesting (EH) relay. As NB-IoT devices proliferate, co-channel interference increases, challenging the performance enhancements that non-orthogonal multiple access (NMA) aims to deliver. To address this, we rigorously tested our proposed approach, demonstrating its effectiveness. The results show a 31.93% increase in energy efficiency, a 7.23% improvement in data rate proportional fairness, and a 36.76% boost in spectrum efficiency. Our approach significantly improves network metrics by strategically organizing resources.