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Multiple-access interference (\LAI) suppression techniques in DS/CD\L\. systems usually assTime additive Gaussian noise. Minimum mean squared error (\IMSE) detec­ tors are near-far resistant in additive Gaussian noise channels. But the additive channel noise in many communication channels is often non-Gaussian and impulsive. Signal de­ tection in non-Gaussian impidsive noise is traditionedly focused on single-user channels. Symmetric alpha-stable (SaS) probability density functions can accurately model kirge classes of impulsive noise. The MMSE performance criterion cannot be used for SaS processes with 0 < a < 2 since they have infinite variance. This dissertation considers the problems of MAI suppression for DS/CDMA systems in the presence of additive nonGaussian impulsive channel noise modeled as a SaS process with 1 < a < 2. These \L\I suppression techniques help combat the near-far problem. First, the minimum dispersion (MD) criterion is introduced to suppress MAI. Linear MD defection can be viewed as expansion of the concept of the MMSE detection for Gaussian multiple-access channels to SaS non-Gaussian impulsive multiple-access channels. The linear MD detector is implemented adaptively using leiist mean p-norm (L^^tP) algorithm. The performance of the linear MD detector is analyzed in the context of a SaS process. Simulation re­ sults indicate that the adaptive MD detector shows good near-far resistance. Next, this dissertation presents a MAI suppression method using the least Lp-norm criterion. The iteratively reweighted least squares (IRLS) algorithm recursively approximates the least Lp-norm solution from weighted norm

Interference suppression for DS/CDMA systems in non-Gaussian impulsive channels