Resource management of GEO relays for real-time remote sensing

Abstract

Remote sensing is one of the main applications of satellite communication. With limited communication time between low earth orbit (LEO) sensing satellites and the ground, geostationary orbit (GEO) satellite relaying has become an effective solution. In practical applications, one GEO communication satellite usually needs to provide data forwarding services for multiple satellites or even multiple satellite constellations. Therefore, communication resource management of GEO satellites has become crucial. Existing methods only focus on resource allocation without taking data forwarding task scheduling into consideration, which limits their applicability in real-time applications. In this paper, we propose a real-time resource management approach for GEO relaying, aiming to maximize network throughputs as well as to reduce transmission delays. In this approach, resource allocation is modeled as a Stackelberg game while task scheduling is modeled as a real-time queuing problem. Furthermore, we propose two real-time algorithms, including an adaptive gradient descent method to find optimal price for data forwarding services with low computational complexity, and a queue-jumping algorithm for data forwarding scheduling to minimize transmission delays. With comparison with existing methods, simulations verify the effectiveness of our proposed method with respect to convergence speed of the algorithm, network throughputs, and transmission delays.