Iterative soft decoding of binary linear codes using a generalized Tanner graph
Eirik Rosnes · 2011
In this work, we consider iterative soft-decision decoding of binary linear codes using a generalized Tanner graph. A generalized Tanner graph is constructed from the code's Tanner graph representation under the objective of mitigating the effect of small cycles. Then, iterative decoding is applied to the generalized Tanner graph using trellis-based soft-input soft-output decoding in the generalized check nodes. When combined with the stochastic shifting algorithm of Jiang and Narayanan (IEEE Commun. Letters, 2004), the proposed decoding method provides both improved error rate performance and reduced average decoding complexity, without increasing the worst-case decoding complexity.