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Effect of Noise on the Performance Comparisons of ICA Algorithms to DS-CDMA Detection

S. D. Parmar, Bhuvan Unhelkar


Commercial cellular networks, like the systems based on DS-CDMA, face many types of interferences such as multi-user interference inside each sector in a cell to interoperate interference. Independent Component Analysis (ICA) has been used as an advanced preprocessing tool for blind suppression of interfering signals in DS-CDMA communication systems. The role of ICA is to provide an interference-mitigated signal to the conventional detection. This paper evaluates the performance of some major ICA algorithms like Pearson-ICA, Cardoso’s joint approximate diagonalization of eigen matrices (JADE), and Bell and Sejnowski’s infomax algorithm to solve the symbol estimation problem of the multi users in a DS-CDMA communication system. The main focus is on blind separation of convolved CDMA mixture and the improvement of the downlink symbol estimation. The results of numerical experiment are compared with those obtained by the Single User Detection (SUD) receiver, ICA detector and combined SUD-ICA detector.


ICA, DS-CDMA, SUD Detection.

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