Satellite synergy: Navigating resource allocation and energy efficiency in IoT networks

Satellite-assisted internet of things (IoT) networks have emerged as a beacon of promise, offering global coverage and uninterrupted connectivity. However, the challenges of resource allocation and task offloading in such networks are intricate due to the unique characteristics of satellite communication systems. This research’s findings enrich the landscape of energy-efficient and dependable satellite-assisted IoT networks. The paper navigates the delicate balance between energy efficiency, network throughput, and fairness in distributing resources among IoT devices. The proposed techniques, notably the Outer Approximation Algorithm (OAA), usher in seamless connectivity and resource optimization. The central challenge at hand, a concave fractional programming problem, transforms through the Charnes–Cooper transformation, presenting as a concave optimization enigma. Herein, the proposed outer approximation algorithm takes flight, navigating the intricate paths of concave optimization. The performance of the epsilon-optimal solution faces scrutiny under diverse system parameters—the constellation of IoT devices, their affiliations, fairness considerations, and the equitable distribution of resource blocks. This contribution not only enriches research but also opens doors to the boundless possibilities of satellite-assisted IoT networks.