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Compressive sensing (CS) technologies present many advantages over other existing approaches for implementing wideband spectrum sensing in cognitive radios (CRs), such as reduced sampling rate and computational complexity. However, there are two significant challenges: 1) choosing an appropriate number of sub-Nyquist measurements and 2) deciding when to terminate the greedy recovery algorithm that...
Compressive spectrum sensing techniques present many advantages over traditional spectrum sensing approaches, e.g., low sampling rate, and reduced energy consumption. However, when the spectral sparsity level is unknown, there are two significant challenges. They are: 1) how to choose an appropriate number of measurements, and 2) when to terminate the greedy recovery algorithm. In this paper, a compressive...
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