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In this work, a soft-hard combination is employed to propose a hierarchical cluster based spectrum sensing algorithm. The proposed algorithm maximizes the detection performances while satisfying the probability of false alarm constraint. Simulation results of the proposed algorithm are presented and compared with existing algorithms over the Nakagami fading channel. Moreover, the results show that...
The smart use of the radio spectrum is viable with the use of Cognitive Radio (CR) techniques and Software Defined Radio (SDR) hardware. With that, this project aims to detect and utilize vacant TV channels for secondary users. The lack of spectrum sensing techniques and methods to identify the state of the TV spectrum in a particular time and location is a problem which is delaying the effective...
Trade-off between performance and overhead of cooperative spectrum sensing (CSS) in cognitive radio Networks (CRNs) still attracts researchers' attention. In this paper, novel energy efficient strategies are proposed for the centralized CSS systems using hard decision fusion rules. The strategies considerably minimize the number of collaborating cognitive radios (CRs) required for the CSS system,...
Striking a balance between detection performance and overhead in cooperative spectrum sensing is a very critical design factor. For a conventional cluster-based spectrum sensing (CBSS) algorithms, all cognitive radios (CRs) in one cluster forward their local decisions through only one channel which leads to incur large sensing overhead. In this work the multi-levels hierarchical cluster-based spectrum...
With cognitive radio networks, opportunistic dynamic access to underutilized frequency bands without harmful interferences to a licensed user can be achieved by several spectrum sensing approaches. Most of these approaches consider static spectrum sensors. Recent researches tend to consider mobile spectrum sensors. This paper extends available work to consider the impact of acceleration on the spectrum...
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