The problem of optimum signal reception in the synchronous CDMA systems in the presence of non-Gaussian intersystem noise

V. V. Kadushkin
A.N.Tupolev Kazan National Research Technical University - KAI

The paper is received on October 1, 2016, after correction - on November 15, 2016

 

Abstract. The problem of optimum signal reception in the synchronous CDMA systems in the presence of non-Gaussian intersystem and industrial noise as well as multiple access interference (MAI) is considered. Analytical representation of the noise can be achieved via probabilistic mixture of a number of Gaussian PDFs with a-priori known parameters.

In order to solve the problem a novel optimum ML-signal resolution algorithm is proposed, that makes estimations of transmitted information bits.

The basic idea, contained in the proposed algorithm, is to form the complete set of statistical hypotheses that correspond to various super-impositions of non-Gaussian noise components as well as spreading chip sequences of interfering users. Because of each spreading chip sequence for particular user corresponds to one of two binary bit, signal resolution problem can be reduced to the problem of distinguishing of paired antithetical hypotheses. Final decision about the transmitted bits is made based on the maximization of the likelihood ratios.

The proposed statistical signal processing (SSP) algorithm takes into account MAI by means of calculating complete set of super-impositions of spreaded chip sequences from multiple interfering users, contained in the structure of corresponding likelihood ratios. It leads to enhancement of likelihood for correct hypotheses.

It is shown that computational complexity has linear dependence of number of samples per chip and noise components and has nonlinear dependence of number of users. The proposed algorithm can serve as the basis for the further synthesis of quasi-optimum SSP algorithms with lower computational complexity and near optimum performance.

Keywords. Optimal reception, non-Gaussian interference and distributions, probabilistic mixtures, statistical signal processing, CDMA systems.

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