A tradeoff resource allocation based on MF‐TDMA scheme in the multibeam data relay satellite systems

Abstract

A tremendous increase in the number of distributed satellite constellations with the unscheduled burst data traffic will impose addition and diverse requirements on the DRS (data relay satellite) systems, which increases the complexity for beam management and affects a real-time data return and acquisition. In this paper, we suggested that a large capacity can be achieved by a multibeam DRS system based on multifrequency time division multiple access scheme providing multiaccess for the distributed satellite constellations. Because the space-based information network is characterized by the limited on-board resources, a highly dynamic topology and time-varying intersatellite links, we designed a 2-stage dynamic optimization approach to separate the multiobjective optimization for frequency/time blocks and power, aiming at the rapidly converging to the optimal solution and at the same time meeting the fairness resource allocation. In particular, a capacity-fairness tradeoff algorithm is proposed based on hybrid the enhanced genetic algorithm and the particle swarm optimization.Simulation results show that the tradeoff between maximizing total capacity and providing proportional fairness allocation is well balanced. The proposed algorithm can rapidly converge to adapt to the highly dynamic topology in data relay satellite systems. KEYWORDS data relay satellite systems, space-based information networks, multiple beams, resource allocation, satellite communications, proportional fairness 1 | INTRODUCTION Space-based information network (SBIN) with the cooperation scheme of the data relay satellite (DRS) systems have a significant role of achieving a real-time data return and acquisition for mission satellites in the low-earth orbit (LEO) or medium-earth orbit, which can offer an uninterrupted coverage and greatly improve monitoring capabilities. 1,2 The traditional on-board beam management technique 3 has been deployed in a DRS to schedule data packets from the DRS to a single satellite. In recent years, the distributed satellite constellation 4 contributes innovative applications (such as disaster prevention and mitigation, military reconnaissance, and removal of space debris) by replacing a single large satellite with several very capable spacecrafts, which opens the door to new applications. 5It can be predicted that a tremendous increase in the number of distributed satellite constellations will impose addition and very diverse requirements on the SBIN. More specially, far more stringent latency and greater capacity requirements are expected to support the real-time data interaction between the distributed satellite constellations, such as the proximity operations and cooperative communications. The different distributed satellite constellations with the unscheduled burst data traffic increase the complexity for beam management, which presents a new challenge for the DRS systems. To tackle the challenges aforementioned above, the multibeam DRS system 6 is ideally suited to deploy such a network as described. The ...

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“…Genetic algorithm is a global random search algorithm which simulates natural selection and evolution and has been used in various types of optimization problems [3][4][5][6] .…”

MILP formulation improvement with k-means clustering for the beam layout optimization in multibeam satellite systems

“…Because of the increasing demand in various data exchanges, there has been a significant amount of research devoted to performance improvement of such systems, as reviewed in [22], such as the use of optical link techniques [19], the coordination of two co-localized satellites [7] or the design of multibeam array antennas [21]. The literature on solution approaches for power and frequency allocation problems is rather rich [18,11,12,23,24,1,14,10]. However, papers dealing with beam layout algorithms are not frequently published.…”

An enhanced MAC protocol based on the IEEE 802.11 for data relay satellite systems

“…To solve the multiaccess for the increasing number of user satellites with diverse tasks, most returned data from a user satellite to DRS system are accomplished by mission's schedule based on the event timelines in the DRS systems . In this case, the performance of the network will be greatly limited by the computational capacity of the DRS systems.…”

“…To solve the multiaccess for the increasing number of user satellites with diverse tasks, most returned data from a user satellite to DRS system are accomplished by mission's schedule based on the event timelines in the DRS systems. 5,6 In this case, the performance of the network will be greatly limited by the computational capacity of the DRS systems. Additionally, future space missions are envisioned to become more complex, which will need the DRS systems to support autonomous multiaccess operations with minimal human intervention.…”

“…1 Moreover, over an intersatellite link (ISL), data from LEO satellites are transmitted to the DRS systems that can achieve a quick data return, such as the European Data Relay System (EDRS), 2 the tracking and DRS system (TDRSS), 3 and the Tianlian relay satellite system, 4 which are playing an important role in space information networks.To solve the multiaccess for the increasing number of user satellites with diverse tasks, most returned data from a user satellite to DRS system are accomplished by mission's schedule based on the event timelines in the DRS systems. 5,6 In this case, the performance of the network will be greatly limited by the computational capacity of the DRS systems. Additionally, future space missions are envisioned to become more complex, which will need the DRS systems to support autonomous multiaccess operations with minimal human intervention.…”