Light First, RF Assist: Spatial Optimization for Minimum Energy Guarantees in Battery-Less IoT Network

Abstract

The rapid expansion of battery-less Internet of Things (IoT) deployments demands energy delivery strategies that minimise maintenance while ensuring reliable operation. This paper studies the placement optimisation of photovoltaic (PV)-equipped donor IoT nodes that harvest dedicated/ambient light power and redistribute surplus energy via radiofrequency (RF) transmissions, together with targeted ceiling-mounted RF transmitters. We formulate an illuminance-informed donor placement problem across heterogeneous light zones and extend it to a co-design framework that integrates dedicated RF support with donor placement. To address these problems, we develop a greedy illuminance-aware algorithm and a joint greedy–genetic algorithm for co-design, supported by a complexity analysis. Numerical results in a 5×5 m2 indoor simulation testbed demonstrate that the co-design approach reduces donor counts by up to 33% while maintaining the required energy thresholds. These results indicate that deployment-aware optimisation can effectively sustain dense IoT networks under practical illumination and RF constraints.