Dynamic transmission adaptation algorithms for battery-free LoRaWAN networks

Abstract

Demand for sustainable IoT solutions has increased over the years, with energy-harvesting technologies coming to the fore, and environmental-powered sensors gaining much importance. Indeed, the benefits can be outstanding for batteryless sensors in terms of increased durability, reduced maintenance (no need for battery replacement), and higher resistance to environmental factors. However, such batteryless devices must be accurately designed to cope with time-varying energy sources, such as solar or wind power. In particular, this work investigates adaptive transmission algorithms to optimize the performance and lifetime of LoRa-based batteryless IoT sensors. First, a thorough characterization is carried out concerning the device’s power consumption, focusing on both sensor measurement and data transmission operations. The performed analysis takes into account also different network scenarios, considering possible changes of the device parameters. Second, a transmission adaptation scheme for the optimizing data transmission intervals, named Uniform Transmission Adaptation (UTA), is proposed. Finally, tailored energy storage solutions are developed, depending on the available energy capacity and considering direct coupling and the use of renewable sources, like photovoltaic cells. Through large-scale simulations in a massive IoT scenario, we quantitatively assess network performance, energy consumption and network efficiency. Simulations show that in massive network conditions, the Packet Delivery Ratio (PDR) reaches 87% with UTA, compared to about 70% achieved with fixed interval transmission strategies. Furthermore, the loss of energy productivity (LoEP) in the fixed transmission scenario is around 3.75% during winter, whereas with UTA it is reduced to near 0%, demonstrating a reduction in energy losses. The findings provide a basis for the design of sensor devices with optimal energy management, in order to meet given reliability requirements, and tackling important challenges of batteryless IoT networks.