Yuandao Sun

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iii Acknowledgments I would like to thank my advisors, Professor Brian L. Mark and Professor Yariv Ephraim, for being such amazing advisors throughout my four years research in George Mason University. They have provided me with their in-depth technical knowledge and invaluable research skills. Meanwhile, they also provided me research assistant scholarship(More)
—We develop a computationally efficient online parameter estimation algorithm for temporal spectrum sensing of a cognitive radio channel using a hidden bivariate Markov model. The online estimator is based on a block-recursive parameter estimation algorithm developed by Rydén for hidden Markov models. This approach requires the score function only. We(More)
This paper analyzes the aggregate interference in a cognitive radio network. We consider a model in which the secondary transmitters are geographically distributed according to a Poisson point process in a wireless environment subject to shadowing noise and path loss. The secondary transmitters may transmit simultaneously and consequently incur an aggregate(More)
—The purpose of spectrum sensing is to determine idle portions of a licensed spectrum band that could be used by unlicensed or secondary users without causing harmful interference to primary users. Collaborative spectrum sensing involves multiple secondary users to make joint decisions about spectrum occupancy. By exploiting multiuser diversity,(More)
iii Acknowledgments I would like to thank my advisors, Professor Brian L. Mark and Professor Yariv Ephraim, for being such amazing advisors throughout my four years research in George Mason University. They have provided me with their in-depth technical knowledge and invaluable research skills. Meanwhile, they also provided me research assistant scholarship(More)
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