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In Direct-Sequence Code Division Multiple Access(DS-CDMA) mobile communication systems, it is very important to obtain accurate estimation of the channel parameters, especially that of the propagation delay. But the near-far problem may make the estimation complicated and can degrade the estimation performance significantly. In this paper, an efficient Maximum Likelihood (ML) method is presented for channel parameter estimation of multi-rate DS-CDMA systems in slow fading multipath channels in a near-far scenario. The algorithm extended the ML approach to multi-rate DS-CDMA systems, and proposes decomposing a multidimensional optimization problem into a series of one-dimensional optimization and has improved computational efficiency. Theoretical analysis and numerical examples show that the estimator proposed is effective and near-far resistant.
In Direct-Sequence Code Division Multiple Access (DS-CDMA) mobile communication systems, it is very important to obtain accurate estimation of the channel parameters, especially that of the propagation delay. But the near-far problem may make the estimation complicated and can In this paper, an efficient Maximum Likelihood (ML) method is presented for channel parameter estimation of multi-rate DS-CDMA systems in slow fading multipath channels in a near-far scenario. The algorithm extended the ML approach to multi-rate DS-CDMA systems, and made decomposing a multidimensional optimization problem into a series of one-dimensional optimization and has improved computational efficiency. Theoretical analysis and numerical examples show that the estimator proposed is effective and near-far resistant.