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Delay based channel allocations in multi-hop cognitive radio networks

机译:多跳认知无线电网络中基于延迟的信道分配

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Delay issue is a challenge in multi-hop cognitive radio networking because of the dynamic change of channels available to the cognitive radio nodes. To address this challenge, we propose a channel allocation and rate allocation scheme with low complexity in this paper. Our scheme is flexible so that it can react to the dynamic change of channel availability, and it can minimize the delay by considering the primary user activities. First, we model the primary users' activity, channel availability and the interference among the cognitive radio nodes in a cognitive radio network environment, and show how to implement a channel allocation algorithm and a rate allocation scheme in multi-hop cognitive radio networks. Second, we formulate an optimization problem to minimize the end-to-end delay of the network. We consider the channel availability constraint and the primary user activities jointly, and analyze the end-to-end delay in multi-hop cognitive radio networks. In order to reduce the computing complexity, we propose a graph coloring based channel allocation and rate selection algorithm using gradient descent method. Furthermore, we show the performance of our schemes and compare them with existing schemes for different scenarios of channel availability and number of channels through simulations. Our work brings insights on how to make rate selection and channel allocation in multi-hop cognitive radio networks.
机译:由于认知无线电节点可用信道的动态变化,延迟问题在多跳认知无线电网络中是一个挑战。为了解决这一挑战,我们提出了一种复杂度较低的信道分配和速率分配方案。我们的方案是灵活的,因此它可以对信道可用性的动态变化做出反应,并且可以通过考虑主要用户活动来最大程度地减少延迟。首先,我们在认知无线电网络环境中对主要用户的活动,信道可用性和认知无线电节点之间的干扰进行建模,并展示如何在多跳认知无线电网络中实现信道分配算法和速率分配方案。其次,我们提出一个优化问题,以最小化网络的端到端延迟。我们共同考虑了信道可用性约束和主要用户活动,并分析了多跳认知无线电网络中的端到端延迟。为了降低计算复杂度,我们提出了一种使用梯度下降法的基于图着色的信道分配和速率选择算法。此外,我们展示了方案的性能,并通过仿真将它们与现有方案针对不同的信道可用性和信道数量场景进行了比较。我们的工作为如何在多跳认知无线电网络中进行速率选择和信道分配带来了见识。

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