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Research on Channel Coding of Convolutional Codes Cascading with Turbo Codes

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Communications, Signal Processing, and Systems (CSPS 2020)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 654))

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Abstract

In this paper, we mainly studied the coding and decoding principles of convolutional codes and turbo codes and verified the coding and decoding process and bit error rate performance of the two codes. In different channel conditions (AWGN and Rayleigh fading channels), with different code rates (1/2 code rate and 1/3 code rate), the convolutional codes with different constraint lengths (3 and 7) and turbo codes are simulated and compared. We can know from the simulation results that the performance of the two codes in AWGN channel is better than that in Rayleigh channel. In these two channels, the performance of the two codes with small bit rate is better than that of the ones with large bit rate; the performance of turbo codes improves with the increase of the constraint length. The performance of convolution code decreases with the increase of the constraint length when the SNR is small, but it improves with the increase of the constraint length when the SNR is large.

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Acknowledgements

This work is supported by National Natural Science Foundation of China (61661018), Research on key technologies of 5G MIMO-OFDM wireless communication system, a general project of Hainan Natural Science Foundation (619MS029), The key technology of MIMO-OFDM and its offshore communication in Hainan University Science Research Project (Hnky2019-8) and Hainan Provincial Natural Science Foundation High-level Talent Project (2019RC036). Hui Li is the corresponding author.

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Correspondence to Hui Li .

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Shi, CY., Li, H., Xu, J., Li, Q., Wang, H., Xue, LX. (2021). Research on Channel Coding of Convolutional Codes Cascading with Turbo Codes. In: Liang, Q., Wang, W., Liu, X., Na, Z., Li, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2020. Lecture Notes in Electrical Engineering, vol 654. Springer, Singapore. https://doi.org/10.1007/978-981-15-8411-4_37

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  • DOI: https://doi.org/10.1007/978-981-15-8411-4_37

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-8410-7

  • Online ISBN: 978-981-15-8411-4

  • eBook Packages: EngineeringEngineering (R0)

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