A new computational decoding complexity measure of convolutional codes

被引：3

作者：

Benchimol, Isaac B. ^{[1
]}

Pimentel, Cecilio ^{[2
]}

Souza, Richard Demo ^{[3
]}

Uchoa-Filho, Bartolomeu F. ^{[4
]}

机构：

[1] Fed Inst Amazonas IFAM, BR-69077000 Manaus, Amazonas, Brazil

[2] Fed Univ Pernambuco UFPE, BR-50670901 Recife, PE, Brazil

[3] Fed Univ Technol Parana UTFPR, BR-80230901 Curitiba, Parana, Brazil

[4] Univ Fed Santa Catarina, BR-88040900 Florianopolis, SC, Brazil

来源：

EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING | 2014年

关键词：

Convolutional codes; Computational complexity; Decoding complexity; Distance spectrum; Trellis module; Viterbi algorithm; TRELLIS COMPLEXITY; MINIMAL TRELLIS;

D O I：

10.1186/1687-6180-2014-173

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents a computational complexity measure of convolutional codes well suitable for software implementations of the Viterbi algorithm (VA) operating with hard decision. We investigate the number of arithmetic operations performed by the decoding process over the conventional and minimal trellis modules. A relation between the complexity measure defined in this work and the one defined by McEliece and Lin is investigated. We also conduct a refined computer search for good convolutional codes (in terms of distance spectrum) with respect to two minimal trellis complexity measures. Finally, the computational cost of implementation of each arithmetic operation is determined in terms of machine cycles taken by its execution using a typical digital signal processor widely used for low-power telecommunications applications.

引用

页码：1 / 10

页数：10

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