Search results
Results from the WOW.Com Content Network
The description above is given for what is now called a serially concatenated code. Turbo codes, as described first in 1993, implemented a parallel concatenation of two convolutional codes, with an interleaver between the two codes and an iterative decoder that passes information forth and back between the codes. [6]
Serial concatenated convolutional codes have not found widespread commercial use, although they were proposed for communications standards such as DVB-S2. Nonetheless, the analysis of SCCCs has provided insight into the performance and bounds of all types of iterative decodable codes including turbo codes and LDPC codes.
Low-density parity-check (LDPC) codes are a class of highly efficient linear block codes made from many single parity check (SPC) codes. They can provide performance very close to the channel capacity (the theoretical maximum) using an iterated soft-decision decoding approach, at linear time complexity in terms of their block length.
The distance d was usually understood to limit the error-correction capability to ⌊(d−1) / 2⌋. The Reed–Solomon code achieves this bound with equality, and can thus correct up to ⌊(n−k) / 2⌋ errors. However, this error-correction bound is not exact.
The Justesen code is the concatenation of an (,,) outer code and different (,,) inner codes , for.. More precisely, the concatenation of these codes, denoted by (,...,), is defined as follows.
The first class of turbo code was the parallel concatenated convolutional code (PCCC). Since the introduction of the original parallel turbo codes in 1993, many other classes of turbo code have been discovered, including serial concatenated convolutional codes and repeat-accumulate codes. Iterative turbo decoding methods have also been applied ...
Typically, the soft output is used as the soft input to an outer decoder in a system using concatenated codes, or to modify the input to a further decoding iteration such as in the decoding of turbo codes. Examples include the BCJR algorithm and the soft output Viterbi algorithm.
Consider the received word = (, …,) [] which was corrupted by a noisy channel.The following is the algorithm description for the general case. In this algorithm, we can decode y by just declaring an erasure at every bad position and running the errors and erasure decoding algorithm for on the resulting vector.