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A grass-root based radio environment data collections in user participation for improving frequency utilization of cognitive radio and heterogeneous networks

机译:基于基于基于基于的无线电环境数据收集,用于提高认知无线电和异构网络的频率利用

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Large-scale radio environment data can provide good reference knowledge for self-organization based wireless networks, such as cognitive radio as well as heterogeneous network. However, it is usually difficult to obtain the data of real spectrum usage due to the constrains of radio monitor capability and cost. In this sense, we believe grass-root based spectrum data collection is important. In this paper, we propose a grass-root based spectrum database architecture by encouraging network users to monitor radio environment data and share it with the database through integrating cognitive radio network as well as heterogeneous network. We apply coalitional game to formulate the cooperation among autonomous network users and design an effective algorithm to improve individual benefit of the users in the game. The details of game property is analyzed, and the algorithm can yield stable partition of coalition for network users, through which each user can obtain improved benefit. Simulations have been performed to demonstrate the advantage of the proposal. The proposed spectrum data collection in user participation is expected to enhance radio frequency optimization for self-organization based wireless networks.
机译:大型无线电环境数据可以为基于自组织的无线网络提供良好的参考知识,例如认知无线电以及异构网络。然而,由于无线电监视能力和成本的约束,通常难以获得实际频谱使用的数据。从这个意义上讲,我们认为基于基于基于基于基于的频谱数据收集很重要。在本文中,我们通过鼓励网络用户来监视无线电环境数据并通过集成认知无线电网络以及异构网络来利用数据库与数据库共享基础的频谱数据库架构。我们申请了合作游戏,制定自主网络用户的合作,并设计一种有效的算法,以提高游戏中用户的个人利益。分析了游戏属性的细节,并且该算法可以产生网络用户联盟的稳定分区,每个用户都可以获得改进的益处。已经进行了模拟以证明提案的优势。预计用户参与中所提出的频谱数据收集将增强基于自组织的无线网络的射频优化。

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