An energy detection algorithm using generalized stochastic resonance under low signal-to-noise ratios

An improved energy detection (IED) algorithm using generalized stochastic resonance (GSR) is proposed to reduce the error probability of the energy detection based spectrum sensing method in cognitive radio systems at low signal-to-noise ratio (SNR). A direct current (dc) component is added to the received signal and the optimal amplitude of the dc component is determined by the offset coefficient so that the GSR between the dc component and the dc in the signal is generated. A test statistic is obtained by sampling and energy accumulation of resonant signals. The optimal detection threshold is determined based on the minimum average error probability criterion and then a decision result is obtained from a comparison between the test statistic and the detection threshold. The performance analyses of the proposed algorithm are given. The theoretical analyses, simulation results and a comparison with the conventional ED algorithm show that the error probability of the IED algorithm improves by about 3 dB when SNR is -15 dB, and less samples are needed for the IED algorithm under same error probability conditions. ©, 2015, Xi'an Jiaotong University. All right reserved.