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A graph-based approach for relay selection and resource allocation in cognitive two-way relay networks

机译:认知双向中继网络中基于图的中继选择和资源分配方法

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In this paper, the problems of relay selection and channel allocation in a cognitive two-way relay network are modelled as a classical weighted bipartite graph matching problem and are solved by the Hungarian algorithm. In the proposed radio resource management algorithm, firstly, some of cognitive radio (CR) nodes are selected to establish the primary user connection as a two-way relay scheme. Then, a power updating algorithm is used to give the maximum signal-to-interference-plus-noise ratio (SINR) in the CR nodes, while keeping the minimum SINR level at the primary transceivers and the best channel assignment is done for CR nodes in order to maximize the SINR value of them. Simulation results show that the proposed algorithm improves the performance of the whole network in comparison with conventional power allocation and relay selection algorithms.
机译:本文将认知双向中继网络中的中继选择和信道分配问题建模为经典的加权二部图匹配问题,并通过匈牙利算法进行求解。在提出的无线电资源管理算法中,首先,选择一些认知无线电(CR)节点以将主要用户连接建立为双向中继方案。然后,使用功率更新算法在CR节点中给出最大信号干扰加噪声比(SINR),同时在主要收发器处保持最小SINR电平,并为CR节点完成最佳信道分配为了使它们的SINR值最大化。仿真结果表明,与传统的功率分配和中继选择算法相比,该算法提高了整个网络的性能。

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