Toward the co-channel signal interference problem in wireless communications

inspired by sparse representation and cyclostationary characteristics

the dictionary matrix is constructed by establishing the sample set of position coordinates

and the sparse signal is reconstructed in cyclic frequency domain using optimization method. Then

the position of the transmitter is directly determined from the cyclic spectrum slice of the received signal. Simulation results show that the localization performance of the proposed algorithm is close to the derived Cramer-Rao lower bound

and outperforms the existing frequency domain direct localization algorithm and two-step localization algorithm

especially in cases of low signal-to-noise ratios and signal-to-interference ratios.