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• W2106352335 endingPage "2028" @default.
• W2106352335 startingPage "2013" @default.
• W2106352335 abstract "We consider the problem of simultaneous parameter estimation and data restoration in a synchronous CDMA system in the presence of either additive Gaussian or additive impulsive white noise with unknown parameters. The impulsive noise is modeled by a two-term Gaussian mixture distribution. Bayesian inference of all unknown quantities is made from the superimposed and noisy received signals. The Gibbs sampler (a Markov chain Monte Carlo procedure) is employed to calculate the Bayesian estimates. The basic idea is to generate ergodic random samples from the joint posterior distribution of all unknown and then to average the appropriate samples to obtain the estimates of the unknown quantities. Adaptive Bayesian multiuser detectors based on the Gibbs sampler are derived for both the Gaussian noise synchronous CDMA channel and the impulsive noise synchronous CDMA channel. A salient feature of the proposed adaptive Bayesian multiuser detectors is that they can incorporate the a priori symbol probabilities, and they produce as output the a posteriori symbol probabilities. (That is, they are soft-input soft-output algorithms.) Hence, these methods are well suited for iterative processing in a coded system, which allows the adaptive Bayesian multiuser detector to refine its processing based on the information from the decoding stage, and vice versa-a receiver structure termed the adaptive turbo multiuser detector." @default.
• W2106352335 created "2016-06-24" @default.
• W2106352335 creator A5040205022 @default.
• W2106352335 creator A5063514061 @default.
• W2106352335 date "2000-07-01" @default.
• W2106352335 modified "2023-09-23" @default.
• W2106352335 title "Adaptive Bayesian multiuser detection for synchronous CDMA with Gaussian and impulsive noise" @default.
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• W2106352335 doi "https://doi.org/10.1109/78.847787" @default.
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