Semi-Markov modeling approach for the reliability analysis of a multiple high altitude platform station system

High Altitude Platform Stations (HAPS) are anticipated as a promising solution for providing wide-area coverage and resilient communication networks by deploying wireless infrastructure in the stratosphere, approximately 20 km above the Earth’s surface. With their extensive reach and capability to function as backup systems during disasters, HAPS are expected to play a vital role in enhancing mobile broadband capacity, particularly in future wireless networks. In this paper, the concept of deploying multiple HAPS within a single network is explored to deliver fast, stable, and efficient communication services across a region. To ensure the dependability of such a multiple HAPS system, a comprehensive reliability assessment becomes crucial. This research work proposes to consider a k-out-of-n system for estimating the reliability attributes of multiple HAPS system over 5G New Radio (NR) network. While traditional reliability assessments often utilize k-out-of-n frameworks and Markovian analysis for repairable systems, our investigation proposes an improved methodological approach. To assess the impact of system failures on HAPS availability, a Semi Markov Process (SMP) is adopted for probabilistic evaluation. The SMP framework demonstrates superior analytical capabilities compared to conventional methods. Particularly, in capturing time dependent variations in system failure probabilities when non-exponential sojourn times are considered. Additionally, the effectiveness of the SMP model is evaluated by analyzing steady-state probability, availability, reliability, and mean time to failure.