Efficient Search Algorithm for Determining Optimal R=1/2 Systematic Convolutional Self-Doubly Orthogonal Codes

Kowarzyk, G.; Belanger, N.; Haccoun, D.; Savaria, Yvon

doi:10.1109/tcomm.2011.100611.100171

Cited by 4 publications

(21 citation statements)

References 19 publications

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“…This faster technique has allowed finding several new optimal-span codes having larger J values. Moreover, short of obtaining optimal codes for some yet higher J values, we have also been able to obtain, within an acceptable amount of computation time, new codes with significantly shorter spans than the ones previously published in [8], [9], [14], [15].…”

Section: Introductionmentioning

confidence: 90%

“…In this section, we present a brief overview of previous (S-)CDO code searching techniques and the key concepts behind the implicitly-exhaustive search algorithm developed in [14]. Then, we describe a novel and efficient parallel implicitly-exhaustive search algorithm.…”

Section: Novel Efficient Parallel Implicitly-exhaustive Search Amentioning

confidence: 99%

“…Although the resulting technique showed that the search for optimal-span codes lends itself well to parallel processing, it is also plagued by many of the inefficiencies that are present in the reference algorithm. In fact, a more efficient technique for reducing the search time through an improved implicitly-exhaustive search process was described in [14], but its operation being sequential in nature, it does not fully take advantage of the performance offered by modern multi-core computer systems.…”

Section: Introductionmentioning

confidence: 99%

“…We show that the drastic increase in speed and efficiency is achieved through very significant algorithmic improvements over the algorithm presented in [14], in particular: a parallel search, an incremental computation with data-reuse, and an enhanced dynamic search-space reduction based on a stricter set of constraints to identify and concentrate the search on only potentially valid codes. This faster technique has allowed finding several new optimal-span codes having larger J values.…”

Section: Introductionmentioning

confidence: 99%

“…A novel and more efficient parallel implicitly-exhaustive search algorithm is described in Section III. In Section IV, new optimal-span codes, as well as novel codes with a shorter span than previously obtained in [8], [9], [14], [15] are presented. The shortest S-CDO code spans and their CDO counterparts are compared.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Parallel Search Algorithm for Determining Optimal R=1/2 Systematic Convolutional Self-Doubly Orthogonal Codes

Kowarzyk

Belanger

Haccoun

et al. 2013

IEEE Trans. Commun.

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A novel parallel and implicitly-exhaustive search algorithm for finding, in systematic form, rate R = 1 2 optimalspan Convolutional Self-Doubly Orthogonal (CDO) codes and Simplified Convolutional Self-Doubly Orthogonal (S-CDO) codes is presented. In order to obtain high-performance low-latency codecs with these codes, it is important to minimize their constraint length (or "span") for a given J number of generator connections. The proposed exhaustive algorithm uses algorithmic enhancements over the best previously published searching techniques, yielding new and improved codes: we were able to obtain new optimal-span CDO/S-CDO codes (having order J ∈ {9} and J ∈ {10, 11} respectively), as well as new codes having the shortest spans published to date for higher values of J (J ∈ {10, 12, ..., 17} and J ∈ {12, ..., 20} for CDO and S-CDO codes respectively). The new codes and their error performance are provided. An analysis of the evolution of the CDO/S-CDO code error performance as J increases is presented, and the shortest CDO/S-CDO code span values for each given J are compared.

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