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.
Highlights
Mobile satellite communication systems (MSCSs) play an important role in space information networks, as they can establish a reliable wide-range mobile communication network under various scenarios, for example, remote areas, emergency situations, maritime, and aviation transportations
After we have described the traffic-aware dynamic resource allocation (TADRA) algorithm for solving the multi-objective programming (MOP) we proposed, we simulate the algorithm under different conditions
In order to further understand the significance of the TADRA algorithm we proposed and the Pareto-front solutions we obtained, we compare the performance of different allocation criterion with some results come from the Pareto-front under the same system model
Summary
Mobile satellite communication systems (MSCSs) play an important role in space information networks, as they can establish a reliable wide-range mobile communication network under various scenarios, for example, remote areas, emergency situations, maritime, and aviation transportations. Considering Problem (9, 10), for given available RBs and power resource, if more resource is allocated to voice users, g1 becomes larger while g2 becomes lower, and vice versa It means that these two objectives are conflicting to each other, and it makes the proposed problem become a Pareto optimization problem.[35] The process of finding the trade-off between these two conflicting objectives is a Pareto optimization for rejecting the dominated solutions and retaining the non-dominated solutions. The MOP problem in this system becomes more complex due to (1) the NP hardness and requirement of Pareto optimization and (2) multiple coupled constraints to the optimization These constraints are related with the cross-beam and interrelated MSCSs, especially in multi-beam MSCSs. According to the system model stated previously, three kinds of constraints to the MOP problem are analyzed in the system, comprising the timeslot-frequency resource constraint, the reuse time constraint, and the output power constraint.
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