Abstract
With the ability to solve the hidden terminal problem, cooperative spectrum sensing (CSS) in cognitive radio networks has attracted much attention. However, existing CSS mainly focuses on detecting the spectrum usage status of primary users (PUs) in time dimension under the premise of known center frequency and bandwidth of PU, which is limited in practical scenarios. For the emerging time-frequency localization based two-dimensional wideband spectrum sensing (SS), how to incorporate cooperation into secondary users (SUs) to enhance sensing performance is still a challenging problem. In this letter, considering the limited storage and computation capacity of SUs, we first propose a lightweight detector for time-frequency localization. Then, through analyzing the characteristics of the sensed spectrogram, we propose a non-maximum suppression based fusion algorithm. Finally, simulation results validate the advantages of the proposed lightweight detector compared with existing detectors, and show the recognition performance of CSS is superior to that of the individual SUs.
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