Graph-based soft channel and data estimation for MIMO systems with asymmetric LDPC codes

Authors

T. Wo, C. Liu, P. A. Hoeher,

Abstract

        In this paper, we propose an iterative soft channel
estimation and data detection algorithm based on a factor
graph. Channel coefficients as well as data symbols are treated
as variable nodes and are all estimated in a low-complexity
element-wise manner. Applying asymmetric LDPC codes, this
algorithm is able to deliver ambiguity-free outputs for MIMO
systems with or without training symbols. Training symbols
are inherently utilized as a type of a priori information. This
algorithm thoroughly relaxes the troublesome constraints on
training design in the sense that an arbitrary (even zero) number
of training symbols can be placed at arbitrary positions within
a data burst.

BibTEX Reference Entry 

@inproceedings{WoLiHo08,
	author = {Tianbin Wo and Chunhui Liu and Paul Adam Hoeher},
	title = "Graph-based soft channel and data estimation for {MIMO} systems with asymmetric {LDPC} codes",
	booktitle = "Int. Conf. Commun. ({ICC})",
	address = {Beijing, China},
	year = 2008,
	hsb = RWTH-CONV-223572,
	}

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