Blind Estimation of Pseudo Random Sequence of DS-CDMA Signals with ICA Method

Abstract

The estimation of pseudo random sequence is of great importance of the security in DS-CDMA system, which remains a hot research topic in reconnaissance and supervision of wireless communication. In DS-CDMA system, the information sequences of different users are independent and the pseudo random sequences are none correlation, thus Independent Component Analysis (ICA) technology can be adopted to separate the DS-CDMA signals with little prior knowledge. An estimation method of pseudo random sequences based on ICA is proposed, projected with the unmixing matrix calculated through ICA, the pseudo random sequences could be estimated from the eigenvector subspace. In multipath situations, the estimation is the overlapped form of the pseudo random sequences, a triple correlation function is introduced to eliminate the influence of multipath, which increases the estimation correct ratio more than 18%. The validity of the method proposed is proved well by the simulation results at last.