Comparative analysis of channel coding methods in wireless networks

DOI: 10.31673/2412-9070.2021.044651

Abstract

Currently, wireless communication networks are rapidly developing in the field of data transmission. The proliferation of these networks is due to their ease of use, low cost and acceptable bandwidth. At the same time, for efficient transmission of information, it is necessary to obtain error-free data, which is often distorted when transmitting them over wireless communication channels. Most often, the quality of data transmission is affected by such factors as dispersion effect, fading, attenuation, interference, noise in the channel, etc. Therefore, in order to avoid errors when receiving information, channel coding methods are used, the main task of which is to search for quickly transmitted codes that can correct or detect errors. Channel coding techniques take up a wider bandwidth because excess bits are added to them. In communication networks, the two most common codes are used in the process of transmitting data: codes for detecting errors and codes for correcting errors. Error detection codes make it easy to determine if errors are present. As a rule, such codes are used in conjunction with certain protocols of the data link or transport layer. In this case, the receiver simply rejects the received data block, in which an error was detected, after which the transmitter transmits this block again. Error correction codes allow not only detecting errors, but also correcting them without resorting to re-transmission of information. These codes are often used in wireless networks where retransmission of data is extremely inefficient and error rates are high. The aim of this work is to compare and analyze the bit error rates (further — BER) when using various methods of channel coding. Moreover, the number of transmitted bits is almost the same for different channel coding methods.

Keywords: Bernoulli binary; channel coding techniques; AWGN; BER analysis.

References
1. Голиков А. М. Модуляция, кодирование и моделирование в телекоммуникационных системах. Теория и практика. Томск: Томск. гос. ун-т систем упр. и радиоэлектроники, 2016. 516 с.
2. Berrou C., Glavieux A. Near optimum error correcting coding and decoding // IEEE Trans. Comm., 1996. Vol. 44, No. 10. P. 1261–1271.
3. Vucetic B., Yuan J. Turbo codes: principles and applications // Kluwer Academic, Norwell, MA, 2000. P. 12.
4. Abbasfar A., Divsalar D., Kung Y. Accumulaterepeat accumulate codes, Proc. // IEEE Global Telecommunications Conference (GLOBECOM 2004), Dallas, TX, December 2004. P. 509–513.
5. The F-LDPC family: High-performance flexible modern codes for flexible radio, in Proc. / T. R. Halford, M. Bayram, C. Kose [et al.] // ISSSTA 2008, Bologna, Italy, September 2008. P. 376–380.
6. Jin H., Khandekar A., McEliece R. Irregular repeat-accumulate codes, In Proc. // 2nd Int. Symp. Turbo codes and related topics, Brest, France, September 2000. Р. 1–8.
7. Forney G. D., Jr. Codes on graphs: Normal realizations // IEEE Trans. Inform. Theory. 2001. Vol. IT-13. P. 520–548.
8. Moreira J. C., Farrell P. G. Essentials of error control coding // John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, England, 2006. P. 361.
9. Скляр Б. Цифровая связь. Теоретические основы и практическое применение, 2-е изд. / пер. с англ. Е. Г. Грозы [и др.]; под ред. А. В. Назаренко. Москва: Вильямс, 2003. 1104 с.
10. Canteaut A., Filiol E. Cipher text only reconstruction of stream ciphers based on combination generators. Berlin, Springer, 2001. P. 16.