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Joint channel estimation, partial successive interference cancellation, and data decoding for DS-CDMA based on the SAGE algorithm
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DOI：10.1109/TCOMM.2007.898855.png)
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Abstract
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This paper deals with the derivation and optimization of an iterative receiver architecture performing joint multiuser decoding and channel estimation. We consider an asynchronous multirate convolutional coded DS-CDMA system that communicates over quasi-static flat Rayleigh fading channels. The proposed receiver is derived within the space-alternating generalized expectation-maximization (SAGE) framework in connection with the noise-splitting approach. The used theoretical framework guarantees convergence of the receiver, as opposed to many other iterative receiver structures. Furthermore, the noise-splitting approach provides a set of noise-weighting coefficients that can be optimized under weak constraints. The inputs to the single-user decoders are linear combinations of two kinds of soft values with weights determined by the noise-weighting coefficients. These two kinds of soft values can be interpreted as a priori information and extrinsic information, respectively, if the channels are known. In the case of unknown channels, they are asymptotically a priori and asymptotically extrinsic, i.e., they become a priori and extrinsic when the length of the observed frame tends to infinity. In most cases, the optimum coefficients lead to extrinsic or asymptotically extrinsic values fed to the input of the single-user decoders. Monte Carlo simulations show that the proposed receiver is resistant to channel estimation errors and supports high system loads.
Keywords:
iterative information processing
iterative joint data decoding and channel estimation
multiuser decoding
SAGE algorithm
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