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首页> 外文期刊>Arabian Journal for Science and Engineering. Section A, Sciences >Diversity-Based Weighted Data Fusion
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Diversity-Based Weighted Data Fusion

机译：基于多样性的加权数据融合

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摘要

Cooperative spectrum sensing (CSS) is used in cognitive radio (CR) networks to improve the spectrum sensing performance in shadow fading environments. Moreover, clustering in CR networks is used to reduce reporting time and bandwidth overhead during CSS. Thus, cluster-based cooperative spectrum sensing (CBCSS) has manifested satisfactory spectrum sensing results in harsh environments under processing constraints. On the other hand, the antenna diversity of multiple input multiple output CR systems can be exploited to further improve the spectrum sensing performance. This paper presents the CBCSS performance in a CR network which is comprised of single-as well as multipleantenna CR systems.We give theoretical analysis of CBCSS for orthogonal frequency division multiplexing signal sensing and propose a novel fusion scheme at the fusion center which takes into account the receiver antenna diversity of the CRs present in the network.We introduce the concept of weighted data fusion in which the sensing results of different CRs are weighted proportional to the number of receiving antennas they are equipped with. Thus, the receiver diversity is used to the advantage of improving spectrum sensing performance in a CR cluster. Simulation results show that the proposed scheme outperforms the conventional CBCSS scheme.
机译：合作频谱感测（CSS）用于认知无线电（CR）网络，以改善阴影衰落环境中的光谱感测性能。此外，CR网络中的聚类用于减少CSS期间的报告时间和带宽开销。因此，基于群集的协作频谱感测（CBCS）表现出令人满意的频谱感测，在处理约束下的恶劣环境中导致了令人满意的频谱感测。另一方面，可以利用多输入多输出CR系统的天线分集进一步提高频谱感测性能。本文介绍了CR网络中的CBCSS性能，该CR网络中的单一以及多个和多功能频率分割复用信号感应的理论分析，并提出了融合中心的新型融合方案网络中存在的CRS的接收器天线分集。我们介绍了加权数据融合的概念，其中不同CRS的感测结果与它们配备的接收天线的数量成比例。因此，接收器分集用于提高CR簇中的频谱感测性能的优点。仿真结果表明，该方案优于传统的CBCSS方案。

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