An application of ICA to blind DS-CDMA detection: a joint optimization criterion
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
A two-stage Independent Component Analysis-based method for blind detection in CDMA systems
Digital Signal Processing
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A code-constrained inverse filter criterion based approach is presented for blind detection of asynchronous short-code direct sequence code division multiple access (DS-CDMA) signals in multipath channels. Only the spreading code of the desired user is assumed to be known; its transmission delay may be unknown. We focus on maximization of the normalized fourth cumulant of inverse filtered (equalized) data with respect to (w.r.t.) the equalizer coefficients subject to the equalizer lying in a subspace associated with the desired user's code sequence. Constrained maximization leads to extraction of the desired user's signal, whereas unconstrained maximization leads to the extraction of any one of the active users. Illustrative simulation examples are provided