2024, issue 2, p. 39-46

Received 22.03.2024; Revised 28.04.2024; Accepted 28.05.2024

Published 09.06.2024; First Online 14.06.2024

https://doi.org/10.34229/2707-451X.24.2.4

Previous  |  FULL TEXT (in Ukrainian)  |  Next

 

MSC 90C15

Improved Decoding Algorithms for Convolutional Codes

Kateryna Sosnenko

V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine, Kyiv

Correspondence: This email address is being protected from spambots. You need JavaScript enabled to view it.

 

Introduction. The considered implementation of the Viterbi algorithm provides a reduction in hardware and time costs for decoding convoluted code sequences, and can be used for semi-realistic modeling of existing means of data transmission (for example, in satellite communication).

The purpose of the article. Show how when modeling the processes of encoding and decoding convolutional codes according to the improved Viterbi algorithm, as well as its implementation based on programmable logic devices of the FPGA type, it was possible to reduce the number of clocks of reading metrics and tracks from RAM by 2 times.

The results. A two-fold decrease in the number of reading cycles of metrics and tracks (input sequences or reverse pointers) from RAM is achieved by joint processing of two receiver nodes that share two source nodes.

Relatively small costs for a hardware calculator of edge metrics allow you to organize parallel calculation, comparison and multiplexing of metrics and tracks of two sources at the inputs of block RAM. Two-port block memory makes it possible to significantly (up to two times) speed up the decoding process, to abandon metric and track buffer registers.

Conclusions: The Viterbi decoder is widely used in communication systems and is a practical method of error correction at high signal transmission speed in modern telecommunication systems. The Viterbi decoder is designed for decoding convolutional codes and is optimal in the sense of minimizing the probability of an error. The advantage of the Viterbi decoder is that its complexity is a linear function of the number of symbols in the codeword sequence.

In addition, the Viterbi algorithm is widely used in pattern recognition systems using hidden Markov models.

 

Keywords: Convolutional codes, Viterbi algorithm, FPGA basis, metrics.

 

Cite as: Sosnenko K. Improved Decoding Algorithms for Convolutional Codes. Cybernetics and Computer Technologies. 2024. 2. P. 39–46. (in Ukrainian) https://doi.org/10.34229/2707-451X.24.2.4

 

References

           1.     Sklar B. Digital Communications: Fundamentals and Applications. New Jersey: Prentice Hall PTR, 2001.

           2.     US patent 8943392 Choudhury et al. 27 January 2015.

           3.     Patent of Ukraine No. 73867. Publ. 2006, Bull No. 6. (in Ukrainian)

           4.     US Patent 4979175 Porter; Jeffrey A. (Tempe, AZ). December 18, 2015.

           5.     Morelos-Zaragosa R. The art of noise-resistant coding. Methods, algorithms, application. M.: Technosphere, 2005. (in Russian)

           6.     Zolotaryov V.V., Ovechkin G.V. Noise-resistant coding. Methods and algorithms: Handbook. M.: Hotline–Telecom, 2004. (in Russian)

           7.     Chichiryn E.N. The reconfigurable structure of the Viterba decoder in the Xilinx FPGA base. Computer tools, networks and systems. 2015. No. 14. P. 40–49. (in Russian) http://nbuv.gov.ua/UJRN/Kzms_2015_14_6

           8.     Sosnenko К.P. Comparative analysis of convolutional code decoder implementations. Computer tools, networks and systems. 2015. No. 14. P. 127–133. (in Russian) http://dspace.nbuv.gov.ua/handle/123456789/122852

           9.     Opanasenko V.M., Lisovyi O.M. Formalization of the design process of computer devices and systems based on FPGA. Computer tools, networks and systems. 2009. No. 8. P. 58–63. (in Ukrainian) http://dspace.nbuv.gov.ua/handle/123456789/6528.

       10.     Kartashevsky V.G., Myshin D.V. Reception of coded signals in channels with memory. M.: Radio I Sviaz', 2004. (in Russian)

 

 

ISSN 2707-451X (Online)

ISSN 2707-4501 (Print)

Previous  |  FULL TEXT (in Ukrainian)  |  Next

 

 

            Archive

 

© Website and Design. 2019-2024,

V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine,

National Academy of Sciences of Ukraine.