Independent component analysis for multiple access interference noise cancellation
Ming Ye, Harold H Szu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2001
Multiple access interference cancellation system is based on the emerging unsupervised neural network learning technique called Independent Component Analysis (ICA) which can determine both the channel propagation transfer function [A] and independent sources S, provided that the channel is linear and an array of receiver antenna exists. The proposed technique works at various levels in a base band synchronous Direct Sequence Code Division Multiple Access (DS- CDMA) system. Simulation results show that the performance equivalent to single user is achievable in principle. The realistic channel propagation case involving time delay and multiple path effects will be considered for a practical system implementation.