spectrum sensing in a wideband regime for cognitive radio network(CRN) faces considerably technical challenge due to the constraints on analog-to-digital converters(ADCs).To solve this problem,an eigenvalue-based comp...
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spectrum sensing in a wideband regime for cognitive radio network(CRN) faces considerably technical challenge due to the constraints on analog-to-digital converters(ADCs).To solve this problem,an eigenvalue-based compressivewidebandspectrum sensing(ECWSS) scheme using random matrix theory(RMT) was proposed in this *** ECWSS directly utilized the compressive measurements based on compressive sampling(CS) theory to perform widebandspectrum sensing without requiring signal recovery,which could greatly reduce computational complexity and data acquisition *** the ECWSS,to alleviate the communication overhead of secondary user(SU),the sensors around SU carried out compressive sampling at the sub-Nyquist rate instead of ***,the exact probability density function of extreme eigenvalues was used to set the *** analyses and simulation results show that compared with the existing eigenvalue-based sensing schemes,the ECWSS has much lower computational complexity and cost with no significant detection performance degradation.
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