A Tensor-Based Approach to Blind Despreading of Long-Code Multiuser DSSS Signals

In this paper, a tensor-based approach to blind despreading of long-code multiuser DSSS signals is proposed. We aim generalize the methods originally developed for separation short-code cases. Firstly, we model intercepted with an antenna-array receiver as three-order tensor missing values, and then, problem can be formulated canonical or parallel factor (CANDECOMP/PARAFAC) decomposition missing-data tensor, which solved using optimum methods. Secondly, constrained Cramér–Rao Bound (CRB) also derived provide performance benchmark proposed approach. Simulation results verify feasibility our in case low signal-to-noise (SNR) conditions.