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Effective Channel Assignment Based on Dynamic Source Routing in Cognitive Radio Networks

机译:认知无线电网络中基于动态源路由的有效信道分配

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The channel assignment problem is one of the most important issues in cognitive radio networks (CRNs). Under a SINR-driven model, we consider channel assignments in a network using dynamic source routing (DSR). In this unicasting model, channel assignments are conducted in a relatively small scale of nodes, which are on the chosen route. In addition, we can make use of the route reply (RREP) message in DSR to estimate the SINR and the maximum data transmission rate of nodes on the chosen route. In this way, the source node can conduct the channel assignment in a more efficient way. We propose two algorithms for the single route and multi-route channel assignments, where the multi-route scheme uses alternative nodes to help transmitting. We give a complexity analysis of two algorithms and an extension of reducing complexity for the multi-route channel assignment algorithm. In addition, we conduct simulations of our two algorithms under networks with different densities and study the performance of our algorithms. Finally, we testify our channel assignment model of a single route in the USRP/Gnuradio testbed, and show the efficiency of our scheme using experimental results.
机译:信道分配问题是认知无线电网络(CRN)中最重要的问题之一。在SINR驱动模型下,我们考虑使用动态源路由(DSR)的网络中的信道分配。在此单播模型中,信道分配是在相对较小规模的节点上进行的,这些节点位于所选的路由上。另外,我们可以利用DSR中的路由回复(RREP)消息来估计SINR和所选路由上节点的最大数据传输速率。这样,源节点可以以更有效的方式进行信道分配。对于单路由和多路由信道分配,我们提出了两种算法,其中多路由方案使用备用节点来帮助传输。我们给出了两种算法的复杂度分析,并给出了降低多路由信道分配算法复杂度的扩展。此外,我们在不同密度的网络下对两种算法进行了仿真,并研究了算法的性能。最后,我们在USRP / Gnuradio测试平台上验证了单个路由的信道分配模型,并使用实验结果证明了该方案的效率。

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