Steven S. Pietrobon

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A soft–in/soft–out algorithm which estimates the a posteriori probabilities (APP) for each transmitted bit is investigated. The soft outputs can be used at the next decoding stage, which could be an outer code or another iteration in an iterative decoding process. This algorithm is estimated to have approximately four times the complexity of the Viterbi(More)
A method of efficiently implementing a continuous MAP decoding algorithm is presented. A sliding window technique is used to reduce the block size at the expense of extra computations. The smaller block size results in a large reduction in memory storage requirements, reduced delay, and the ability to implement a continuous MAP decoder. A technique for(More)
This is a tutorial paper meant to introduce the reader to the new concept of turbo codes. This is a new and very powerful error correction technique which outperforms all previous known coding schemes. It can be used in any communication system where a significant power saving is required or the operating signal–to–noise ratio (SNR) is very low. Deep space(More)
We define super codes as the serial concatenation of punctured convolutional codes. Puncturing pattern and interleaver design techniques are presented so as to maximise the free distance of the code, and thus the performance at very low bit error rates (BER). The performance of super codes is compared to turbo codes. For BERs around 10–5, turbo codes(More)
This paper deals with a posteriori probability (APP) decoding of high-rate convolutional codes, using the dual code's trellis. After deriving the dual APP (DAPP) algorithm from the APP relation, its trellis-based implementation is addressed. The challenge involved in practical implementation of a DAPP decoder is then highlighted. Metric representation(More)