Wavelet-based separating kernels for array processing of cellular DS/CDMA signals in fast fading

We propose new detectors for direct-sequence code-division multiple-access (CDMA) signals that outperform known approaches in rapidly fading multipath channels. Multipath compensation in CDMA systems is a problem of significant complexity especially when rapidly fading is afflicting the radio frequency channel. In this work, we depart from typical approaches in search of new kernels that can more accurately characterize the time-varying nature of the estimation problem and focus on a multiresolution representation of the fading processes. The unknown channel time variations are in fact decomposed using optimal unconditional bases in the family of the orthonormal wavelets. We show that it is possible to represent the channel in a reduced-order dimensional space by matching the scattering function of the multipath channel to its decomposition and obtain an approach that is effective in fast fading environments, such as those practically found in macrocell wireless communication applications. We apply this representation to the development of a practical multiscale filter that achieves multiuser separation minimizing a time-averaged squared error. The technique is studied by means of computer simulations and hardware experiments that employ a currently deployed base-station system