The cognitive wireless sensor network (CWSN) is an important development direction of wireless sensor networks (WSNs), and spectrum sensing technology is an essential prerequisite for CWSN to achieve spectrum sharing. However, the existing non-cooperative narrowband spectrum sensing technology has difficulty meeting the application requirements of CWSN at present. In this paper, we present a non-cooperative spectrum sensing algorithm for CWSN, which combines the multi-resolution technique, phase space reconstruction method, and singular spectrum entropy method to sense the spectrum of narrowband wireless signals. Simulation results validate that this algorithm can greatly improve the detection probability at a low signal-to-noise ratio (SNR) (from −19dB to −12dB), and the detector can quickly achieve the best detection performance as the SNR increases. This algorithm could promote the development of CWSN and the application of WSNs.

With the development of wireless communication technology, cognitive radio needs to solve the spectrum sensing problem of wideband wireless signals. Due to performance limitation of electronic components, it is difficult to complete spectrum sensing of wideband wireless signals at once. Therefore, it is required that the wideband wireless signal has to be split into a set of sub-bands before the further signal processing. However, the sequence of sub-band perception has become one of the important factors, which deeply-impact wideband spectrum sensing performance. In this paper, we develop a novel approach for sub-band selection through the non-stationary multi-arm bandit (NS-MAB) model. This approach is based on a well-known order optimal policy for NS-MAB mode called discounted upper confidence bound (D-UCB) policy. In this paper, according to different application requirements, various discount functions and exploration bonuses of D-UCB are designed, which are taken as the parameters of the policy proposed in this paper. Our simulation result demonstrates that the proposed policy can provide lower cumulative regret than other existing state-of-the-art policies for sub-band selection of wideband spectrum sensing.

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