Simulation of A Novel Algorithm for,MultiruserDetection in Long Code CDMA"

Abstract

Computation of the Cholesky decomposition of the autocorrelation matrix is essential in developing zero-forcing, MMSE and decision feedback detectors for a long code CDMA system. However, computing the Cholesky decomposition of the time varying correlation matrix requires many computer operations. This is because the computation of the filter weights is segment specific (varies from one symbol interval to next). In this dissertation, a novel and fast algorithm is developed for computing the Cholesky decomposition of the autocorrelation matrix for a long code CDMA system. The smart update algorithms to compute the solution (filter weights) of one segment from the solution of the previous segment reduces the computational complexity especially for large sized autocorrelation matrices. We exploit the fact that the channel matrix AM(m) of a long code CDMA system is block banded with a shift structure. Though AM(m) is not Toeplitz for a long code CDMA system, the shift structure of the matrix, along with its banded structure, allows the development of fast smart update recursive algorithms for data estimation. The relevance of this algorithm is discussed in for channels with multipath delays extending over many symbol intervals.