Signal Subspace Methods for Delay Estimation in Wireless Cdma Systems

We consider the problem of delay estimation in an asyn-chronous wireless CDMA communication system. The received observations are decomposed into orthogonal signal and noise subspaces via the singular value decomposition (SVD). A class of techniques known as subspace tting techniques is used to estimate the individual user delays by maximizingthe t between the signal subspace and the observed data. Since we only require knowledge of the signal subspace, the noise subspace can be spher-icalized, i.e., reduced to one dimension, which leads to a reduction in computational complexity over the full SVD. A computationally eecient algorithm is used to update the signal subspace and spherical noise subspace for each newly received observation vector. The delays can then be estimated in closed form through the roots of a quadratic equation.