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Maximum connectivity-based channel allocation algorithm in cognitive wireless networks for medical applications

机译:用于医学应用的认知无线网络中基于最大连接性的信道分配算法

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With the advent of multimedia and pattern recognition based medical technology, intelligence medical applications in smart hospital, smart clinic, and smart medical for Individual, such as disease diagnosis, rehabilitation, health monitoring, and so on, have received extensive attentions. However, the communication infrastructure of supporting these applications is facing a larger challenge. This paper studies the channel allocation problem in cognitive wireless networks for these medical applications. Channel allocations are of importance for cognitive wireless networks. How to assign the appropriate channels to each cognitive user is fairly challenging. In this paper we study this problem by combining collaborations of network nodes. We take the maximum network connectivity as an optimal objective to build our collaborative channel allocation model. Our approach takes in account the channel idle status and the transmission radiuses of cognitive users. We allocate firstly the idle channel to bottleneck node and assign the suited channels to all other cognitive users as possible. In such a way, we present three channel allocation strategies with the maximum network connectivity via the omni-directional and direction antennas. We also propose the corresponding algorithm to perform the channel allocation for all cognitive users in cognitive wireless networks. Simulation results show that our approach is promising. (C) 2016 Elsevier B.V. All rights reserved.
机译:随着基于多媒体和模式识别的医疗技术的出现,智能医院,智能诊所和个人智能医疗中的智能医疗应用,如疾病诊断,康复,健康监测等,受到了广泛的关注。但是,支持这些应用程序的通信基础架构面临更大的挑战。本文针对这些医学应用研究认知无线网络中的信道分配问题。信道分配对于认知无线网络很重要。如何为每个认知用户分配适当的渠道是相当具有挑战性的。在本文中,我们通过结合网络节点的协作来研究此问题。我们将最大的网络连接性作为建立协作渠道分配模型的最佳目标。我们的方法考虑了信道空闲状态和认知用户的传输半径。我们首先将空闲通道分配给瓶颈节点,然后将合适的通道分配给所有其他认知用户。通过这种方式,我们提出了三种通过全向和定向天线实现最大网络连通性的信道分配策略。我们还提出了相应的算法来为认知无线网络中的所有认知用户执行信道分配。仿真结果表明我们的方法是有前途的。 (C)2016 Elsevier B.V.保留所有权利。

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