Journal
IEEE TRANSACTIONS ON INFORMATION THEORY
Volume 55, Issue 1, Pages 6-15Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIT.2008.2008114
Keywords
Asymptotic growth; concatenated codes; minimum distance; repeat-accumulate-accumulate (RAA) codes; turbo codes
Funding
- ARO [DAA L03-92-G-0115]
- MURI [DAAD 19-00-1-0466]
- NSF [CCR: 9701304]
Ask authors/readers for more resources
Worst-case upper bounds are derived on the minimum distance of parallel concatenated turbo codes, serially concatenated convolutional codes, repeat-accumulate codes, repeat-convolute codes, and generalizations of these codes obtained by allowing nonlinear and large-memory constituent codes. It is shown that parallel-concatenated turbo codes and repeat-convolute codes with sub-linear memory are asymptotically bad. It is also shown that depth-two serially concatenated codes with constant-memory outer codes and sublinear-memory inner codes are asymptotically bad. Most of these upper bounds hold even when the convolutional encoders are replaced by general finite-state automata encoders. In contrast, it is proven that depth-three serially concatenated codes obtained by concatenating a repetition code with two accumulator codes through random permutations can be asymptotically good.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available