Stochastic modeling of enhancing energy efficiency for HAP in HAP-LEO systems using Markov regenerative process

Abstract

The sixth-generation (6G) communication systems heavily rely on space-air-terrestrial networks (SAT), which integrate high-altitude platforms (HAPs) and low Earth orbit (LEO) satellites. LEO satellites play a crucial role in ensuring global coverage and supporting a large number of users, while HAPs are strategically deployed to cover regions with high demand, providing a more reliable communication service to ground users. The principal aim of the proposed model is to explore techniques for energy conservation and efficient energy harvesting within the multi-layered system for HAP. In this energy harvesting scenario, it is assumed that HAPs will store the energy units generated through solar power. Moreover, the presented model incorporates two energy-saving states: standby and sleep states, during which HAPs consume minimal or zero energy. To analyze the described multi-layer system, a stochastic model is formulated using Markov regenerative process (MRGP), with consideration for the mean sojourn times of energy-saving states following a non-exponential distribution. The numerical results vividly demonstrate the significant contribution of energy-saving states in enhancing the energy efficiency of the HAP system. Also, trade-offs have been presented to analyze the impact of energy harvesting and energy saving in the proposed model. These findings are visually presented in graphs, and to validate the proposed model, simulation results have been carried out.