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Anti-Jamming Routing For Internet of Satellites: a Reinforcement Learning Approach

机译:卫星互联网的抗干扰路由:一种强化学习方法

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The anti-jamming routing for the Internet of Satellites (IoS) has drawn increasing attentions due to the unknown interrupts, unexpected congestion and smart jamming. This paper investigates anti-jamming routing scheme for heterogeneous IoS, with the aim of minimizing anti-jamming routing cost. Firstly, to tackle the smart jamming which can automatically change jamming strategies according to the jamming effect, we formulate the routing anti-jamming problem as a hierarchical anti-jamming Stackelberg game. Secondly, we propose a deep reinforcement learning based routing algorithm (DRLR) to obtain an available routing path subset. Furthermore, based on this set, a fast response anti-jamming algorithm (FRA) is proposed to achieve fast and reliable antijamming routing. Finally, the simulations have shown that the proposed algorithm have lower routing cost and better antijamming performance than existing approaches.
机译:卫星互联网(IoS)的抗干扰路由由于未知的中断,意外的拥塞和智能干扰而引起了越来越多的关注。本文研究了异构IoS的抗干扰路由方案,目的是将抗干扰路由成本降到最低。首先,为了解决可以根据干扰效果自动更改干扰策略的智能干扰,我们将路由抗干扰问题表达为一个分层的抗干扰Stackelberg游戏。其次,我们提出了一种基于深度强化学习的路由算法(DRLR),以获得可用的路由路径子集。此外,在此基础上,提出了一种快速响应的抗干扰算法(FRA),以实现快速可靠的抗干扰路由。最后,仿真结果表明,与现有方法相比,该算法具有较低的路由成本和较好的抗干扰性能。

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