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Sensor placement algorithm for radio environment map construction in cognitive radio networks

机译:认知无线电网络中无线电环境图构建的传感器放置算法

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In cognitive radio, current trend is to utilize geolocation database for TV bands. Considering more dynamic bands in terms of primary user activity, however, necessitates the use of Radio Environment Map (REM), which is an advanced knowledge base that stores live multidomain information on the entities in the network and the environment. In Cognitive Radio Networks (CRNs), mobile nodes that are capable of measuring the energy of the frequency bands are less capable compared to dedicated sensing nodes in the network. Therefore, deployment algorithm of the dedicated sensor nodes is of great importance and affects the constructed REM interference map quality. We propose a novel deployment algorithm for CRNs that considers user distribution probabilities. Numerical results confirm that the proposed deployment algorithm significantly improves the REM performance. The proposed algorithm is compared with random deployments and it is applied on Kriging and LIvE REM construction techniques.
机译:在认知无线电中,当前的趋势是将地理位置数据库用于电视波段。但是,考虑到主要用户活动的更多动态范围,必须使用无线电环境地图(REM),后者是一种先进的知识库,用于存储有关网络和环境中实体的实时多域信息。在认知无线电网络(CRN)中,与网络中的专用传感节点相比,能够测量频带能量的移动节点的能力较弱。因此,专用传感器节点的部署算法具有重要意义,并且会影响所构造的REM干扰图的质量。我们提出了一种考虑用户分布概率的新颖的CRN部署算法。数值结果证实,所提出的部署算法显着提高了REM性能。将所提出的算法与随机部署进行比较,并将其应用于克里金法和LIvE REM构造技术。

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