Baseband Communication Signal Blind Separation Algorithm Based on Complex Nonparametric Probability Density Estimation

In this paper, a blind separation algorithm based on nonparametric probability density estimation (NPDE) for baseband communication signals is proposed. The NPDE method can precisely estimate the probability density of signals, and its good data-driven property guarantees the adaptability of the proposed algorithm. The NPDE method is extended to complex field to fit the complex characteristics of baseband communication signals. The complex update procedure of demixing matrix corresponding to complex channel matrix and signals is also derived in this paper. The experimental results indicate that the proposed algorithm not only can effectively separate the mixture of baseband communication signals, which are modulated with the same or different modulation schemes, but also has better convergence properties and greater signal interference ratio gains than the contrast algorithms. Moreover, even if the local carrier of receiver is unsynchronized to the carrier of received signals due to carrier offsets, the proposed algorithm can also achieve a valid separation.