The Minimum Distance of Turbo-Like Codes

被引:12
|
作者
Bazzi, Louay [1 ]
Mahdian, Mohammad [4 ]
Spielman, Daniel A. [2 ,3 ]
机构
[1] Amer Univ Beirut, Dept Elect & Comp Engn, Beirut, Lebanon
[2] Yale Univ, Dept Comp Sci, New Haven, CT 06520 USA
[3] Yale Univ, Program Appl Math, New Haven, CT 06520 USA
[4] Yahoo Res, Santa Clara, CA 95054 USA
关键词
Asymptotic growth; concatenated codes; minimum distance; repeat-accumulate-accumulate (RAA) codes; turbo codes; SERIAL CONCATENATION;
D O I
10.1109/TIT.2008.2008114
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:6 / 15
页数:10
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