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Article Dans Une Revue EURASIP Journal on Advances in Signal Processing Année : 2019

Wideband signal detection for cognitive radio applications with limited resources

Résumé

Wideband signals are expected to be used to achieve the required quality of service (QoS) in the next generation ofwireless communications, civil and military radar, and many wireless sensor network (WSN) scenarios. Widebandsignal detection has been identified as one of the most challenging problems in the proliferation of the cognitiveradio technology. Moreover in many applications, spectrum sensing in cognitive radio (CR) is expected to beperformed with limited resources in terms of time, computation, and complexity. This paper is dedicated to thedetection of a wideband signal with small sample size. Aiming at using small sample size, a statistical model ofsamples is given based on Student’s t distribution. However, the limited number of channel observations brings areduction of confidence in the decision. A set of new basic probability assignments associated with the hypothesis ofthe occupied or vacant channel are then proposed to perform the Dempster-Shafer (D-S) decision process. Simulationresults show that the proposed method has much higher sensitivity to sense an occupied channel than the traditionalenergy detection method (ED) and the decision fusion method when small sample size is used.
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Dates et versions

hal-01991776 , version 1 (07-07-2020)

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Shaoyang Men, Pascal Chargé, Yide Wang, Jianzhong Li. Wideband signal detection for cognitive radio applications with limited resources. EURASIP Journal on Advances in Signal Processing, 2019, 2019 (1), pp.2. ⟨10.1186/s13634-018-0600-6⟩. ⟨hal-01991776⟩
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