A two-stage Independent Component Analysis-based method for blind detection in CDMA systems

We propose an ICA-based method for blind detection of users in asynchronous DS-CDMA communications systems with multipaths channels with the only knowledge of the desired userʼs code. The method can handle both the uplink and the downlink situations, since it does not require the synchronism between users. We convert the received cyclostationary signal into an observations vector that follows the ICA model with instantaneous mixture. The selection of the estimated source is carried out by means of the desired userʼs code. Unlike previous works, we avoid to project the results after each iteration. Instead, we introduce a preprocessing based on a linear transformation of the data that enforces the extraction vector to lie in the desired userʼs subspace. The detection is done in two stages. The second stage is a fine tuning in which the constraint is removed from the data in order to obtain more accurate results. Computer simulations show that the proposed method compares favorably with other well-known methods, in terms of mean-square error (MSE) of the output, symbol error rate and robustness against the near-far problem.