Adaptive blind equalization for multicarrier CDMA systems with receiver diversity

In this paper we present a new adaptive blind equalization algorithm for multicarrier CDMA systems with single or multiple receive antennas. We analyze the cost function in the well-known subspace method and interpret it in terms of the noise projection matrix. The projection matrix is shown to be a special weighted spectral decomposition of the data autocorrelation matrix, which can be effectively approximated by inverting the data autocorrelation matrix. By adding a user specific correction term to the common cost function, we show that all user channel impulse responses can be estimated in parallel. In this way we develop a block algorithm with low complexity first. We then derive a recursive algorithm using RLS-type matrix updating. Simulations show our algorithm has fast convergence and is near-far resistant. The bit error rate performance is also shown to improve as receiver diversity increases.