Non-iterative optimum super-trellis decoding of turbo codes

The Super-Trellis Structure of Turbo Codes

The super-trellis structure of turbo codes

In this contribution we derive the super-trellis structure of turbo codes. We show that this structure and its associated decoding complexity depend strongly on the interleaver applied in the turbo encoder. We provide upper bounds for the super-trellis complexity. Turbo codes are usually decoded by an iterative decoding algorithm, which is suboptimum. Applying the super-trellis structure, we ca...

Near-optimum decoding of product codes: block turbo codes

This paper describes an iterative decoding algorithm for any product code built using linear block codes. It is based on soft-input/soft-output decoders for decoding the component codes so that near-optimum performance is obtained at each iteration. This soft-input/soft-output decoder is a Chase decoder which delivers soft outputs instead of binary decisions. The soft output of the decoder is a...

Iterative Decoding Algorithms for Turbo Product Codes

In this paper we introduce the iterative decoding principle, “the turbo principle”, for the bidimensional Turbo Product Codes (TPC’s). The constituent codes used for encoding on rows and columns are two concatenated (7,4) Hamming block codes. Several Soft Input Soft Output (SISO) algorithms can be used for the iterative decoding process. At each iteration, the two decoders decode all rows, then...

Soft-Output Decoding Algorithms in Iterative Decoding of Turbo Codes

In this article, we present two versions of a simplified maximum a posteriori decoding algorithm. The algorithms work in a sliding window form, like the Viterbi algorithm, and can thus be used to decode continuously transmitted sequences obtained by parallel concatenated codes, without requiring code trellis termination. A heuristic explanation is also given of how to embed the maximum a poster...