Minimum probability of error for asynchronous Gaussian multiple-access channels
IEEE Transactions on Information Theory
Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
Equivariant adaptive source separation
IEEE Transactions on Signal Processing
Blind adaptive multiuser detection
IEEE Transactions on Information Theory
Multi-user detection for DS-CDMA communications
IEEE Communications Magazine
A class of neural networks for independent component analysis
IEEE Transactions on Neural Networks
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The performance of a conventional single user DS-CDMA receiver is severely limited by multiple access interference (MAI) and near---far effects. This severity has motivated research into adaptive filtering, near---far resistant detectors and power control strategies for DS-CDMA systems. In this paper, we propose a near---far resistant detector based on independent component analysis (ICA) of the received signal. Since ICA is a blind technique, the proposed ICA based detector has the potential to combat the near---far problem. The ICA is a higher order statistical technique based on the assumption of independence of source signals. The assumptions in ICA algorithm are the realistic conditions in a DS-CDMA system and therefore ICA algorithm can be applied successfully to detect the signal of the desired user. The focus of this paper is to illustrate the near---far resistance capability of the ICA based detector. Simulation studies performed on the proposed detector show that it is resistant to the near-far problem and has low bit error rate.