Iterative turbo decoder analysis based on density evolution

337 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Belief Propagation, Dykstra's Algorithm, and Iterated Information Projections (2010, background): “The various formal results available appeal to asymptotic approximations [17]–[20] in the problem dimension, isolating conditions under which the factor graph girth (which is the number of iterations before the shortest loop in the factor graph closes itself) becomes arbitrarily large; the loops nea”
On interleave-division multiple-access (2004, methodology): “The method is semi-analytical since some of the functions involved (related to the FEC codes) are pre-calculated by simulation (similar to the methods in [12][13]).”
Design of efficiently encodable moderate-length high-rate irregular LDPC codes (2004, background): “This is discussed in [6] and [7] in the context of density evolution, where it is noted that the slope of the versus curve for v-nodes is equal to the node degree minus one.”
Interleave division multiple-access (2006, background): “[ 23 ] to estimate the bit-error rate (BER) performance of these algorithms.”
The art of error correcting coding (2002, background): “182 ITERATIVELY DECODABLE CODES In addition, a number of interesting semianalytical tools have appeared, in density evolution (Richardson and Urbanke 2001), Gaussian approximation (Gamal and Hammons 2001), and mutual information (ten Brink 1999, 2001) or SNR transfer (Divsalar et al. 2001) character”