Paper Info
Title
Block Markov Superposition Transmission: Construction of Big Convolutional Codes from Short Codes
Abstract
A construction of big convolutional codes from short codes called block Markov superposition transmission (BMST) is proposed. The BMST is very similar to superposition block Markov encoding (SBME), which has been widely used to prove multiuser coding theorems. The BMST codes can also be viewed as a class of spatially coupled codes, where the generator matrices of the involved short codes (referred to as basic codes) are coupled. The encoding process of BMST can be as fast as that of the basic code, while the decoding process can be implemented as an iterative sliding-window decoding algorithm with a tunable delay.More importantly, the performance of BMST can be simply lower-bounded in terms of the transmission memory given that the performance of the short code is available. Numerical results show that, 1) the lower bounds can be matched with a moderate decoding delay in the low bit-error-rate (BER) region, implying that the iterative sliding-window decoding algorithm is near optimal; 2) BMST with repetition codes and single parity-check codes can approach the Shannon limit within 0.5 dB at the BER of 10−5 for a wide range of code rates; and 3) BMST can also be applied to nonlinear codes.
Year
DOI
Venue
2013
10.1109/TIT.2015.2422296
IEEE Transactions on Information Theory
Keywords
DocType
Volume
big convolutional codes,block markov superposition transmission,sliding-window decoding,spatial coupling,superposition coding
Journal
PP
Issue
ISSN
Citations 
99
0018-9448
16
PageRank 
References 
Authors
0.76
46
4
Name
Order
Citations
PageRank
Xiao Ma148764.77
Chulong Liang210312.50
Kechao Huang3605.65
Qiutao Zhuang4443.56