Title
MAP algorithms for decoding linear block codes based on sectionalized trellis diagrams
Abstract
The MAP algorithm is a trellis-based maximum a posteriori probability decoding algorithm. It is the heart of the turbo decoding or iterative decoding which can achieve an error performance near the Shannon limit. Unfortunately, the implementation of this algorithm requires large computation and storage. Furthermore, its forward and backward recursions cause long decoding delay. For practical applications, this decoding algorithm must be simplified and its decoding complexity and delay must be reduced. In this paper, the MAP and max-log-MAP algorithms are first applied to sectionalized trellises for linear block codes. Using the structural properties of properly sectionalized trellises, the decoding complexity and delay of the MAP algorithms can be reduced. Also presented in this paper are bi-directional and parallel MAP decoding
Year
DOI
Venue
2000
10.1109/GLOCOM.1998.775790
IEEE Transactions on Communications
Keywords
Field
DocType
backward recursion,symbol error probability,sectionalized trellis diagrams,maximum likelihood decoding,delay,linear codes,turbo decoding,parallel map decoding,max-log-map algorithm,shannon limit,structural properties,forward recursion,block codes,delays,computational complexity,storage,decoding algorithm,decoding complexity,iterative decoding,bi-directional map decoding,linear block codes,error statistics,maximum a posteriori probability decoding algorithm,map algorithms,convolutional codes,error performance,long decoding delay,decoding,algorithms,error probability,trellis coding,computation,heart,linear systems,probability theory,complexity,viterbi algorithm
Convolutional code,Berlekamp–Welch algorithm,Sequential decoding,Computer science,Block code,Algorithm,Linear code,Decoding methods,List decoding,Difference-map algorithm
Journal
Volume
Issue
ISBN
1
4
0-7803-4984-9
Citations 
PageRank 
References 
16
1.48
4
Authors
3
Name
Order
Citations
PageRank
Ye Liu1161.48
Shu Lin2575133.22
M. P. C. Fossorier354640.68