Title :
Importance sampling for tanner trees
Author :
Xia, Bo ; Ryan, William E.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Arizona, Tucson, AZ, USA
fDate :
6/1/2005 12:00:00 AM
Abstract :
This correspondence presents an importance sampling (IS) simulation scheme for the soft iterative decoding on loop-free multiple-layer trees. It is shown that this scheme is asymptotically efficient in that, for an arbitrary tree and a given estimation precision, the required number of samples is inversely proportional to the noise standard deviation. This work has its application in the simulation of low-density parity-check (LDPC) codes.
Keywords :
importance sampling; iterative decoding; message passing; parity check codes; trees (mathematics); IS simulation scheme; LDPC; importance sampling; loop-free multiple-layer tree; low-density parity-check code; message-passing decoding; noise standard deviation; precision estimation; soft iterative decoding; tanner graph tree; AWGN; Acceleration; Error analysis; Information analysis; Iterative decoding; Monte Carlo methods; Parity check codes; Sampling methods; Tree data structures; Tree graphs; Importance sampling; Tanner graph; Tanner tree; low-density parity-check (LDPC) code; message-passing decoding;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2005.847748
