Title :
Universal Context Based Decoding with Low-Density Parity-Check Codes
Author :
Wang, Li ; Shamir, Gil I.
Author_Institution :
Univ. of Utah, Salt Lake City
fDate :
9/1/2007 12:00:00 AM
Abstract :
Universal estimation strategies are proposed to improve channel decoding of sequences that contain context based redundancy. The new methods combine techniques from universal compression, such as the Burrows-Wheeler Transform (BWT) and segmentation of piecewise stationary memoryless sources (PSMS´s) with recently proposed methods of discrete denoising. Simulation results with systematic low density parity check (LDPC) codes show significant improvements of the proposed methods on standard decoding, even when the actual sequence context model is unknown in advance. The combined methods inherit advantages of each of the separate methods.
Keywords :
channel coding; data compression; decoding; parity check codes; Burrows-Wheeler transform; channel decoding; discrete denoising; low-density parity-check codes; piecewise stationary memoryless sources segmentation; sequence context model; universal compression; universal context based decoding; Code standards; Context modeling; Discrete transforms; Gas insulated transmission lines; Iterative decoding; Maximum likelihood decoding; Maximum likelihood estimation; Noise reduction; Parity check codes; Statistics;
Journal_Title :
Communications Letters, IEEE
DOI :
10.1109/LCOMM.2007.070338