An Improved White Space Prediction Algorithm for Cognitive Radio Systems

Nguyen Huu Phong, Vo Nguyen Quoc Bao, Huu-Tue Huynh


Cognitive radio (CR) is a promising technology to enhance the current low usage of limited frequency resources. TV white space (TVWS) - TV bands at a particular time in a particular geographic area that are not being used by licensed services - is perceived as the most suitable frequency bands for CR. This paper proposes a new prediction TVWS algorithm for CR systems based on the ITU 1546.1 and the Okumura-Hata models. The proposed algorithm is verified with the data of 22 provinces in the South of Vietnam. The numerical results confirm the advantage of the proposed algorithm as well as the possibility of TVWS CR networks.

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