Dynamic Resource Allocation for Beam Hopping Satellites Communication System: An Exploration

Du, Xinqing; Hu, Xin; Wang, Yin; Wang, Weidong

doi:10.1109/trustcom56396.2022.00181

Cited by 5 publications

(1 citation statement)

References 12 publications

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“…In the literature, refs. [17,18] conducted a series of research works to verify the advantages of the highly flexible dynamic beam-hopping method in multi-beam satellite systems. In addition, the DVB-S2X standard has proposed several superframe specifications [19] to support beam-hopping transmission in future multi-beam satellites, which also means that beam-hopping technology has enormous potential.…”

Section: Related Workmentioning

confidence: 99%

Efficient Resource Allocation for Beam-Hopping-Based Multi-Satellite Communication Systems

2023

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With the rapid growth of data traffic, low earth orbit (LEO) satellite communication networks have gradually ushered in a new trend of development due to its advantages of low latency, wide coverage, and high capacity. However, as a result of the limited on-board resources and rapidly changing traffic demand, it is increasingly urgent to design an efficient resource-allocation scheme to satisfy the traffic demand. In this paper, we propose two resource allocation algorithms in the multi-satellite system based on beam-hopping technology. In the offline case, it is assumed that the channel gains in all time-slots are known in advance, and we propose a heuristic algorithm to allocate time and frequency resources, and a successive convex approximation (SCA) algorithm to allocate power resources. In the online case, it is assumed that only the instant channel gains information is known; therefore, we apply the dynamic programming (DP) algorithm to maximize the system throughput. The simulation results prove that the proposed resource-allocation algorithms based on beam-hopping technology have better performance than the traditional average allocation method, and the online algorithm has acceptable performance loss compared with the offline algorithm.

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Section: Related Workmentioning

confidence: 99%