Age of Information in Non-Terrestrial Networks with Energy Harvesting
2026-08-03 • Networking and Internet Architecture
Networking and Internet Architecture
AI summaryⓘ
The authors study how fresh information is kept when a device on the ground sends updates through moving satellites while using harvested energy. Because satellites come in and out of connection unpredictably, the device first spends energy to check if a satellite is available before sending updates. They mathematically model both the satellite connections and the device's energy level to find the average freshness of updates. Their results show that checking for satellite availability before transmitting helps save energy and keeps information fresher, especially when satellites are few or energy is limited.
Age of InformationLow Earth Orbit (LEO) satellitesEnergy harvestingInternet of Things (IoT)Stochastic geometrySemi-Markov processStatus updatesSatellite mobilityProbe-before-transmission
Authors
Fangming Zhao, Nikolaos Pappas, Shi Jin, Howard H. Yang
Abstract
We analyze the timeliness of status-update delivery in a low Earth orbit (LEO) satellite-assisted energy-harvesting Internet of Things network using the Age of Information (AoI) metric. A ground source harvests ambient energy and sends status updates to a remote destination through LEO satellites. Because of satellite mobility, source-to-satellite connectivity alternates between on and off periods whose durations depend on the satellite-ground geometry. The source does not know the connectivity state a priori and therefore employs a probe-before-transmission mechanism: it first expends one energy unit to sense satellite availability and transmits an update only after a successful probe. We combine spherical stochastic geometry with semi-Markov analysis to characterize the coupled evolution of satellite connectivity and the source energy buffer, and derive an analytical expression for the time-average AoI. We then develop a lower-complexity approximation by replacing the instantaneous connectivity state in the energy process with the long-term on-state probability. The resulting approximation is accurate when the energy constraint is weak or satellite connectivity is highly intermittent. Numerical results show that probing can substantially reduce AoI relative to blind transmission by preventing energy expenditure during off periods, particularly under sparse satellite deployment, stringent decoding requirements, or limited energy harvesting.