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User social activity-based routing for cognitive radio networks

机译:基于用户社交活动的认知无线电网络路由

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摘要

The social activities of Primary Users (PUs) and Secondary Users (SUs) affect actual accessible whitespace in Cognitive Radio Networks (CRNs). However, the impacts of primary activities on available whitespace have been extensively investigated due to the dominating priority of PUs, while the impacts of secondary activities on actual accessible whitespace have been ignored. Therefore, we propose to incorporate the primary and secondary activities in the analysis and decision of the accessible whitespace, namely, both the dominance of PUs over SUs and the competitions among SUs are simultaneously taken into account. Specifically, we first approximate primary activity probability based on the real datasets of mobile phone usage records, then the spectrum opportunity between a pair of communication SUs is deduced based on primary activities. Next, we infer the access probability limit of SUs successfully accessing the whitespace according to the primary activity probability, and depict the secondary activity probability from the views of social activity patterns and social networks respectively. Furthermore, the actual accessible probability of whitespace is given by introducing the competitions among SUs. Finally, a greedy routing algorithm, considering the accessible whitespace and the distance to the destination, is proposed to verify our idea. The experiment results based on the real datasets demonstrate the correctness of our analysis and the advantages of the proposed algorithm.
机译:主要用户(PU)和次要用户(SU)的社交活动影响认知无线电网络(CRN)中的实际可访问空白。但是,由于PU的优先级较高,已经广泛研究了主要活动对可用空白的影响,而次要活动对实际可访问空白的影响却被忽略了。因此,我们建议将主要和次要活动纳入可访问空白的分析和决策中,即同时考虑到PU在SU上的优势和SU之间的竞争。具体而言,我们首先基于手机使用记录的真实数据集来估算主要活动概率,然后根据主要活动推导一对通信SU之间的频谱机会。接下来,我们根据主要活动概率来推断SU成功访问空白的访问概率极限,并分别从社交活动模式和社交网络的角度描述次要活动概率。此外,通过引入SU之间的竞争来给出空白的实际可访问概率。最后,提出了一种考虑可访问空白和到目的地的距离的贪婪路由算法,以验证我们的想法。基于真实数据集的实验结果证明了我们分析的正确性和所提出算法的优势。

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  • 来源
    《Personal and Ubiquitous Computing》 |2018年第3期|471-487|共17页
  • 作者单位

    Key Laboratory for Modern Teaching Technology, Ministry of Education,School of Computer Science, Shaanxi Normal University;

    Department of Computer Science, Georgia State University;

    Key Laboratory for Modern Teaching Technology, Ministry of Education,School of Computer Science, Shaanxi Normal University;

    Key Laboratory for Modern Teaching Technology, Ministry of Education,School of Computer Science, Shaanxi Normal University;

    Key Laboratory for Modern Teaching Technology, Ministry of Education,School of Computer Science, Shaanxi Normal University;

    Department of Computer Science, Georgia State University;

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  • 入库时间 2022-08-17 13:18:23

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