Cluster-Based Blind Estimation of Mary DSSS Signals

Blind estimation of multi-sequence direct sequence spread spectrum signals with unknown spreading codes are discussed in this paper. The dominant mode despreading (DMDS) algorithm is certified to be a successful solution for the blind estimation of the conventional DSSS signals. However, it is not applicable to M-ary DSSS signals. Borrowing unsupervised cluster analysis ideas, we propose a novel method named K-means clustering despreading (KCDS) algorithm for M-ary DSSS signals. The basic flow of the algorithm is introduced, and the choice of dissimilarity measure is given. It's demonstrated to be effective via simulation results for a 32-ary DSSS signal in the presence of zero-mean noise. The tradeoff between the computational complexity and the estimation accuracy is discussed at the end of this paper.