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Erschienen in:
2021 | OriginalPaper | Buchkapitel
Research on Channel Coding of Convolutional Codes Cascading with Turbo Codes
verfasst von : Chong-Yue Shi, Hui Li, Jie Xu, Qian Li, Hou Wang, Liu-Xun Xue
Erschienen in: Communications, Signal Processing, and Systems
Verlag: Springer Singapore
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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.