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The Impact of Network Size and Mobility on Information Delivery in Cognitive Radio Networks

机译:网络规模和移动性对认知无线电网络中信息传递的影响

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摘要

There have been extensive works on the design of opportunistic spectrum access and routing schemes to improve spectrum efficiency in cognitive radio networks (CRNs), which becomes an integral component in the future communication regime. Nonetheless, the potentials of CRNs in boosting network performance yet remain to be explored to reach the full benefits of such a phenomenal technique. In this paper, we study the end-to-end latency in CRNs in order to find the sufficient and necessary conditions for real-time applications in finite networks and large-scale deployments. We first provide a general mobility framework which captures most characteristics of the existing mobility models and takes into account. Under this general mobility framework, secondary users are mobile with an , which indicates how far a mobile node can reach in spatial domain. We find that there exists a cutoff point on , below which the latency has a heavy tail and above which the tail of the latency is bounded by some distributions. As the network grows large, the latency is asymptotically scalable (linear) with respect to the dissemination (e.g., the number of hops or euclidean distance). An interesting observation is that although the density of primary users adversely impacts the expected latency, it makes no influence on the of the latency tail in finite networks and the linearity of latency in large networks. Our results encourage CRN deployment for real-time and large applications, when the mobility radius of secondary u- ers is large enough.
机译:在机会频谱接入和路由方案的设计方面已经进行了广泛的工作,以提高认知无线电网络(CRN)的频谱效率,这已成为未来通信体系中不可或缺的组成部分。尽管如此,CRN在提高网络性能方面的潜力还有待探索,以实现这种惊人技术的全部好处。在本文中,我们研究了CRN中的端到端延迟,以便为有限网络和大规模部署中的实时应用找到充分和必要的条件。我们首先提供一个通用的移动性框架,该框架捕获并考虑了现有移动性模型的大多数特征。在此通用移动性框架下,辅助用户使用进行移动,该指示移动节点可以在空间域中到达多远。我们发现在上存在一个截止点,在该截止点以下,潜伏期有一条沉重的尾巴,在此之上,潜伏期的尾巴受到某些分布的限制。随着网络的扩大,相对于分发(例如,跳数或欧几里得距离),等待时间是渐近可缩放的(线性的)。有趣的观察是,尽管主要用户的密度对预期的等待时间有不利影响,但它对有限网络中的等待时间尾部和大型网络中的等待时间线性均无影响。当辅助用户的移动半径足够大时,我们的结果鼓励在实时和大型应用程序中部署CRN。

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