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Low Storage, but Highly Accurate Measurement-Based Spectrum Database via Mesh Clustering
Rei HASEGAWA Keita KATAGIRI Koya SATO Takeo FUJII
IEICE TRANSACTIONS on Communications
Publication Date: 2018/10/01
Online ISSN: 1745-1345
Type of Manuscript: Special Section PAPER (Special Section on Wireless Distributed Networks for IoT Era)
cognitive radio, spectrum sensing, spectrum sharing, spectrum database, clustering,
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Spectrum databases are required to assist the process of radio propagation estimation for spectrum sharing. Especially, a measurement-based spectrum database achieves highly efficient spectrum sharing by storing the observed radio environment information such as the signal power transmitted from a primary user. However, when the average received signal power is calculated in a given square mesh, the bias of the observation locations within the mesh strongly degrades the accuracy of the statistics because of the influence of terrain and buildings. This paper proposes a method for determining the statistics by using mesh clustering. The proposed method clusters the feature vectors of the measured data by using the k-means and Gaussian mixture model methods. Simulation results show that the proposed method can decrease the error between the measured value and the statistically processed value even if only a small amount of data is available in the spectrum database.