OFDM and FH Signal Recognition Based on Cumulants and SPWVD Spectrum Cancellation for Internet of Things

Considering the Gaussian asymptotic features of OFDM signals,the identification method of it is proposed in this paper by using the cumulants of the wavelet transform coefficients in different layer in a low SNR circumstance.Furthermore,taking the coexistence of the OFDM and Frequency Hopping(FH) signals into account,a new way to separate FH and OFDM signals is proposed based on SPWVD spectrum cancellation,and it can be used to estimate the FH parameters.The simulation results show that the OFDM and single-carrier signals can be identified with a high correct rate of 95% even at-6 dB SNR;meanwhile,the separation of mixed OFDM and FH signals can be achieved with a low SNR of-6 dB,and FH parameters can be estimated accurately.It shows that the recognition performance is improved by about 5 dB compared with the traditional method.

Considering the Gaussian asymptotic features of OFDM signals, the identification meth-od of it is proposed in this paper by using the cu-mulants of the wavelet transform coefficients in different layer in a low SNR circumstance. Further-more, taking the coexistence of the OFDM and Frequency Hopping （FH） signals into account, a new way to separate FH and OFDM signals is pro- posed based on SPWVD spectrum cancellation, and it can be used to estimate the FH parameters. The simulation resuks show that the OFDM and single-carrier signals can be identified with a high correct rate of 95% even at-6 dB SNR; mean-while, the separation of mixed OFDM and FH sig-nals can be achieved with a low SNR of-6 dB, and FH parameters can be estirmted accurately.It shows that the recognition performance is improved by about 5 dB compared with the traditional method.