In Direct-Sequence Code Division Multiple Access(DS-CDMA) mobile communi-cation systems, it is very important to obtain accurate estimation of the channel parameters,especially that of the propagation delay. But the n...In Direct-Sequence Code Division Multiple Access(DS-CDMA) mobile communi-cation 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 estimationcomplicated and can degrade the estimation performance significantly. In this paper, an efficientMaximum Likelihood (ML) method is presented for channel parameter estimation of multi-rateDS-CDMA systems in slow fading multipath channels in a near-far scenario. The algorithmextended the ML approach to multi-rate DS-CDMA systems, and proposes decomposing a multi-dimensional optimization problem into a series of one-dimensional optimization and has improvedcomputational efficiency. Theoretical analysis and numerical examples show that the estimatorproposed is effective and near-far resistant.展开更多
基金the National Natural Science Foundation of China under Grant 60102005
文摘In Direct-Sequence Code Division Multiple Access(DS-CDMA) mobile communi-cation 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 estimationcomplicated and can degrade the estimation performance significantly. In this paper, an efficientMaximum Likelihood (ML) method is presented for channel parameter estimation of multi-rateDS-CDMA systems in slow fading multipath channels in a near-far scenario. The algorithmextended the ML approach to multi-rate DS-CDMA systems, and proposes decomposing a multi-dimensional optimization problem into a series of one-dimensional optimization and has improvedcomputational efficiency. Theoretical analysis and numerical examples show that the estimatorproposed is effective and near-far resistant.
