Blind Estimation of Spreading Sequence based on the Wide Window and PAST Algorithm

Abstract

The problem of blind estimation of spreading sequence is an important aspect in the context of spectrum surveillance, which the pseudo-random sequence used by the transmitter is unknown. In this paper, the approach of the spreading sequence recovery is proposed by using projection approximation subspace tracking (PAST) method and sliding window technique, when the received signal is sampled and divided into temporal windows, the size of which is double the pseudorandom sequence period. The calculation of the main eigenvector is only needed, and sliding window technique is used to realize the spreading sequence synchronization. The PAST method avoids the calculation of eigenvalue decomposition, the main way is to obtain the convergence weights in an iterative method. Therefore, it is easy to realize in hardware and has less computational cost. Experimental results show that the proposed method eliminates the problem of phase ambiguity and can provide a good estimation, even when the received signal is far below the noise level.