A traffic-awareness dynamic resource allocation scheme based on multi-objective optimization in multi-beam mobile satellite communication systems

YuanZhi He, YiZhen Jia and XuDong Zhong

International Journal of Distributed Sensor Networks, 2017, vol. 13, issue 8, 1550147717723554

Abstract: Mobile satellite communication systems play an important role in space information networks. They mostly operate at the L or S band and have multiple beams efficiently reusing the limited spectrum. Advanced technologies, such as beamforming, are used to generate numerous beams through multiple feeders, and each beam’s power allocation is correlated and constrained. Frequency reuse among multiple beams results in co-channel interference issue, which makes bandwidth allocation among multiple beams coupled. It is a challenging topic to optimize the resource allocation in the real-time service traffic. In this article, a new multi-objective programming scheme is used to solve the dynamic resource allocation problem, guaranteeing high quality-of-service for multiple services of different priorities. Since the dynamic resource allocation problem is formulated as NP-hard, a new traffic-aware dynamic resource allocation (TADRA) algorithm is proposed. This algorithm is proved to be optimal in terms of the Pareto-front under constraints of co-channel interference and onboard transmit power. Simulation results show that the trade-off is well balanced between the call completion ratio in high priority and the throughput for video and data services in medium and low priorities. Additionally, it is shown that the new multi-objective programming scheme, based on the traffic-awareness dynamic resource allocation algorithm, can rapidly achieve the Pareto-front solutions and reduce the computing complexity to a large extent.

Keywords: Space information networks; multi-objective programming; traffic awareness; dynamic resource allocation; multiple beams; mobile satellite communication systems (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:13:y:2017:i:8:p:1550147717723554

DOI: 10.1177/1550147717723554

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