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Robust Topology Control in Multi-Hop Cognitive Radio Networks

机译:多跳认知无线电网络中的鲁棒拓扑控制

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The opening of under-utilized spectrum creates the opportunity of substantial performance improvement through cognitive radio techniques. However, the real network performance may be limited since unlicensed users must vacate and switch to other available spectrum if the current spectrum is reclaimed by the licensed (primary) users. During spectrum switching, network partitions may occur since multiple links may be affected if they use the channel reclaimed by the primary users. In this paper, we address this problem through robust topology control, where channels are assigned to minimize channel interference while maintaining network connectivity when primary users appear. The problem is proved to be NP-hard and a sufficient condition for a robust channel assignment is derived. To solve this problem, we first propose centralized algorithms which can reduce the channel interference while satisfying the robustness constraints. Moreover, we derive its performance bound on channel interference and its computational overhead through theoretical analysis. Then, we propose distributed algorithms based on channel hopping techniques, and prove their correctness. Simulation results show that our solutions outperform existing interference-aware approaches substantially when primary users appear and achieve similar performance at other times.
机译:未充分利用的频谱的开放创造了通过认知无线电技术大幅提高性能的机会。但是,实际的网络性能可能会受到限制,因为如果许可(主要)用户收回了当前频谱,则非许可用户必须撤离并切换到其他可用频谱。在频谱切换期间,可能会发生网络分区,因为如果多个链路使用主要用户回收的信道,则它们可能会受到影响。在本文中,我们通过健壮的拓扑控制解决了这个问题,当主要用户出现时,分配信道以最大程度地减少信道干扰,同时保持网络连接性。事实证明,该问题是NP困难的,并得出了用于可靠信道分配的充分条件。为了解决这个问题,我们首先提出集中式算法,该算法可以在满足鲁棒性约束的同时减少信道干扰。此外,我们通过理论分析推导了其性能对信道干扰的限制及其计算开销。然后,提出了基于信道跳变技术的分布式算法,并证明了其正确性。仿真结果表明,当主要用户出现并在其他时间获得相似的性能时,我们的解决方案将大大优于现有的干扰感知方法。

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