Motivated by a recently published robust geometric programming approximation, a generalized approach for approximating efficiently the max* operator is presented. Using this approach, the max* operator is approximated by means of a generic and yet very simple max operator, instead of using additional correction term as previous approximation methods require. Following that, several turbo decoding algorithms are obtained with optimal and near-optimal bit error rate (BER) performance depending on a single parameter, namely the number of piecewise linear (PWL) approximation terms. It turns out that the known max-log-MAP algorithm can be viewed as special case of this new generalized approach. Furthermore, the decoding complexity of the most popular previously published methods is estimated, for the first time, in a unified way by hardware synthesis results, showing the practical implementation advantages of the proposed approximations against these methods.
On optimal and near-optimal turbo decoding using generalized max operator / Papaharalabos, S; Mathiopoulos, P. T.; Masera, Guido; Martina, Maurizio. - In: IEEE COMMUNICATIONS LETTERS. - ISSN 1089-7798. - STAMPA. - 13:7(2009), pp. 522-524. [10.1109/LCOMM.2009.090537]
On optimal and near-optimal turbo decoding using generalized max operator
MASERA, Guido;MARTINA, MAURIZIO
2009
Abstract
Motivated by a recently published robust geometric programming approximation, a generalized approach for approximating efficiently the max* operator is presented. Using this approach, the max* operator is approximated by means of a generic and yet very simple max operator, instead of using additional correction term as previous approximation methods require. Following that, several turbo decoding algorithms are obtained with optimal and near-optimal bit error rate (BER) performance depending on a single parameter, namely the number of piecewise linear (PWL) approximation terms. It turns out that the known max-log-MAP algorithm can be viewed as special case of this new generalized approach. Furthermore, the decoding complexity of the most popular previously published methods is estimated, for the first time, in a unified way by hardware synthesis results, showing the practical implementation advantages of the proposed approximations against these methods.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2265278
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