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Joint Relay Selection and Power Allocation for Energy-Constrained Multi-Hop Cognitive Networks

机译:能量受限多跳认知网络的联合中继选择和功率分配

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摘要

Cognitive relay is considered as a remarkable technology that increases the network coverage and raises the system spectral utilization by exploiting those detected spectrum holes. We mainly investigate a multi-hop scenario that is more complex than a dual-hop network because of the high correlation between hops. In this article, we consider an energy-constrained network which includes a source node, a destination node and a group of network clusters each consisting of several cognitive relay nodes. To accomplish data transmission from source to destination, the best path including nodes with optimal power is selected to maximize the network capacity using proposed efficient algorithms, taking into account the sensing results of relay nodes, the channel gains and the connectivity of links. In addition, these algorithms can also be adopted in the situation of selecting two relay paths by making only a few slight modifications, which means that the scheme provides good expansibility. Simulation results illustrate the strategies of relay selection and power allocation constrained by different energy consumptions and compare the performance between one-path and two-paths selection.
机译:认知中继被认为是一项非凡的技术,可通过利用那些检测到的频谱漏洞来增加网络覆盖范围并提高系统频谱利用率。由于跳数之间的高度相关性,我们主要研究比双跳网络更复杂的多跳场景。在本文中,我们考虑一个能源受限的网络,其中包括一个源节点,一个目标节点和一组网络集群,每个网络集群都由几个认知中继节点组成。为了完成从源到目的地的数据传输,考虑到中继节点的感测结果,信道增益和链路的连通性,使用建议的高效算法选择包括具有最佳功率的节点在内的最佳路径以最大化网络容量。另外,这些算法也可以在仅需进行少量修改的情况下选择两条中继路径的情况下采用,这意味着该方案提供了良好的可扩展性。仿真结果说明了受不同能耗限制的继电器选择和功率分配策略,并比较了单路径选择和两路径选择的性能。

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