Linear Detection via Belief Propagation
نویسندگان
چکیده
In this paper, the paradigm of linear detection is reformulated as a Gaussian belief propagation (GaBP) scheme, without resorting to direct matrix inversion. The derived iterative framework allows for a distributive message-passing implementation of this important class of sub-optimal tractable estimators. The properties of GaBP-based linear detection are addressed, while its faster convergence, in comparison with conventional iterative solution methods, is demonstrated experimentally.
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تاریخ انتشار 2007