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首页> 外文期刊>IEEE transactions on mobile computing >Hierarchical Cooperation Improves Delay in Cognitive Radio Networks with Heterogeneous Mobile Secondary Nodes
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Hierarchical Cooperation Improves Delay in Cognitive Radio Networks with Heterogeneous Mobile Secondary Nodes

机译:分层协作改善了具有异构移动辅助节点的认知无线电网络的延迟

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摘要

This paper characterizes the throughput and delay performance of Cognitive Radio Networks (CRNs), where both primary and secondary networks coexist in a unit torus. Specifically, the primary network consists of static primary nodes (PNs) of density n, which have a higher priority to access the spectrum. In contrast, the secondary network consists of mobile secondary nodes (SNs) of density m = n(beta) with beta (>=) 1, which move according to a hybrid random walk mobility model and have opportunistic access to the spectrum without affecting primary packet transmissions. Motivated by the fact that cooperation between primary and secondary nodes leads to possible improvement on the performance of CRNs, as well as the fact that the heterogeneous moving regions of secondary nodes will bring about further improvement, we propose a novel hierarchical cooperative scheduling mechanism, where secondary nodes serve as relays for primary packet transmissions by exploiting their mobility heterogeneity and geographic information. Our findings include: (i) For the primary network, stronger mobility heterogeneity of secondary nodes leads to better delay performance of the primary network, and meanwhile the delay scaling can be significantly reduced to Theta(n root(beta/(4 log n)) log(3/2) n) when a near-optimal per-node throughput of Theta(1/log n) is obtained. (ii) For the secondary network, we also adopt a similar hierarchical cooperative scheduling mechanism, and obtain a near-optimal per-node throughput of Theta(1/log m) with the delay scaling of Theta(m1(-/(1)root(/log m)). (iii) The delay of secondary source-destination pairs is determined by the moving region of destinations and has no relation with sources. Our work provides deeper understandings of the cooperation, heterogeneous mobility, and geographic information on the performance of CRNs, and sheds light on designing more efficient CRNs.
机译:本文描述了认知无线电网络(CRN)的吞吐量和延迟性能,在该认知无线电网络中,主要和次要网络都共存于一个单元环中。具体来说,主要网络由密度为n的静态主要节点(PN)组成,它们具有更高的优先级来访问频谱。相比之下,辅助网络由密度为m = n(beta)和beta(> =)1的移动辅助节点(SN)组成,它们根据混合随机游动模型进行移动,并且有机会访问频谱而不会影响主节点分组传输。基于主节点和辅助节点之间的协作可导致CRN性能提高的事实,以及辅助节点的异构移动区域将带来进一步改进的事实,我们提出了一种新颖的分层协作调度机制,其中次要节点通过利用它们的移动性异质性和地理信息,充当主要分组传输的中继。我们的发现包括:(i)对于主网络,辅助节点的移动性异质性越强,主网络的延迟性能越好,同时延迟比例可显着降低为Theta(n root(beta /(4 log n) )log(3/2)n)当获得Theta(1 / log n)的接近最佳单节点吞吐量时。 (ii)对于辅助网络,我们还采用了类似的分层协作调度机制,并以Theta(m1(-/(1))的延迟定标获得了接近最优的Theta(1 / log m)节点吞吐量。 root(/ log m))。(iii)次要源-目的地对的延迟由目的地的移动区域决定,与源无关,我们的工作对以下方面的合作,异构移动性和地理信息有更深入的了解CRN的性能,并为设计更有效的CRN提供了启示。

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