Fine-Grained Incentive Mechanism for Sensing Augmented Spectrum Database
Fine-Grained Incentive Mechanism for Sensing Augmented Spectrum Database
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DOI：
10.1109/glocom.2017.8254447
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发表时间：
2017-12
期刊：
影响因子：
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通讯作者：
Xiaoyan Wang;M. Umehira;Peng Li;Yu Gu;Yusheng Ji
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文献类型：
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作者：
Xiaoyan Wang;M. Umehira;Peng Li;Yu Gu;Yusheng Ji
为了提高频谱利用效率，基于无线电传播模型的频谱数据库最近得到了广泛的研究。然而，由于经验模型不考虑本地环境细节，因此它很容易提供不准确和过时的频谱可用性。一种有前途的解决方案是将实时频谱测量纳入准静态频谱数据库。在本文中，我们提出了一种用于感知增强频谱数据库的新型细粒度激励机制。我们首先提出一个逆向拍卖框架，该框架根据需要增加的每个点的质量要求，最大限度地减少运营商的总支出。然后我们提出了一种实用的激励机制来解决拍卖问题，该机制被证明是真实的、个体理性的和计算高效的。模拟结果表明，与两个基准方案相比，所提出的机制可以节省显着的支出。
To improve the spectrum utilization efficiency, radio propagation model based spectrum database is widely investigated recently. However, it is prone to offer inaccurate and stale spectrum availability since the empirical models do not count for local environment details. One promising solution is to incorporate real- time spectrum measurement into the quasi-static spectrum database. In this paper, we propose a novel fine-grained incentive mechanism for sensing augmented spectrum database. We first present a reverse auction framework, which minimizes the operator's total expenditure subject to the quality requirement of each spot that needs to be augmented. Then we propose a practical incentive mechanism to solve the auction problem, which is proven to be truthful, individual rational and computationally efficient. Simulation results demonstrate that the proposed mechanism could save noticeable expenditure compared to two baseline schemes.