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SPECTRUM SENSING FOR COGNITIVE RADIO NETWORKS Yuandao Sun, PhD George Mason University, 2015 Dissertation Co-director: Dr. Brian L. Mark Dissertation Co-director: Dr. Yariv Ephraim Cognitive radio has been proposed as a technology for reclaiming highly under-utilized spectrum resources to satisfy the increasing spectrum demand. In a cognitive radio network,(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)
Collaborative spectrum sensing exploits multiuser diversity by combining spectrum sensing information from multiple secondary users to make joint decisions about spectrum occupancy. In hard fusion schemes, each secondary user makes a hard decision on spectrum occupancy and a fusion center makes a final decision by combining the individual hard decisions(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)
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