Statistical Analysis for Average Peak Age of Information in LEO Satellite-Enabled IoT

In recent decades, minimizing data transmission delay has been a key metric for Ultra Reliable Low-Latency Communication (URLLC). However, low-delay transmission does not always ensure high-quality network service, particularly for real-time applications where the timeliness of data is crucial. This has led to the emergence of the Age of Information (Aol) as a key metric for tracking the freshness of transmitted updates. AoI is especially relevant in large-scale networks like the Internet of Things (IoT), where massive updates are frequently sent. IoT nodes in regions with poor terrestrial network coverage can benefit from Low Earth Orbit (LEO) satellites, which provide reliable connectivity. This work introduces a stochastic geometry-based model to study uplink AoI in fully loaded large-scale IoT networks, where both LEO satellites and ground nodes follow independent Poisson Point Processes (PPPs). In this model, each source node uses a non-preemptive transmission scheme, meaning it completes the current update transmission before handling new ones. Numerical results highlight the influence of varying satellite numbers and altitudes on AoI performance.