## 3 Channel Coding Technology  
Turbo code, also known as parallel cascaded convolutional code, has two component code decoders, and the decoding is iteratively decoded between the two component decoders, so the whole decoding process is similar to turbine work [27; 28]. Turbo code can bring the efficiency of channel coding close to the Shannon limit and be used as the coding technology in 3G/4G mobile communication. Because Turbo code adopts iterative decoding, it is difficult for it to meet the needs of ultra-high speed and ultra-low latency 5G scenarios where real-time performance requirements are very high. The check matrix of LDPC code has the characteristic of sparsity, which makes its coding and iterative decoding algorithm less complex and easier to implement in hardware and, compared with other coding methods, the code rate composition of LDPC code is flexible, with lower error leveling. When the code length is long enough, the information transmission rate of the communication system can approach the Shannon limit [29; 30]. Both Turbo codes and LDPC codes have certain randomness during construction, such as constructing an interleaver for Turbo code and the node distribution design of LDPC codes. Therefore, when designing a specific coding scheme, it is necessary to carry out code structure traversal or heuristic construction according to design parameters. This random construction makes it difficult for the final encoding scheme of a finite code length to achieve the theoretical optimal performance. Professor [PERSON] [31] proposed polarization code for the first time in 2008, which was the first channel coding technology that could theoretically reach [PERSON]'s theoretical limit. Because of the low complexity of encoding and decoding of polarization codes, the performance of polarization codes is very good in the case of long codes, and the performance is improved with the increase in code length. When the code length goes to infinity, the channel polarization can be completely carried out, that is, only the perfect channel and the full noise channel exist. Common construction methods of Polar codes include the Barcanalis parameter construction, Gaussian approximation construction, evolutionary degradation construction, and Monte Carlo construction. The Barcanalis parameter construction method is applied only to binary deletion channels. Suppose that the code length is D. When the channel index is between 0 and 0.5D, the channel capacity of most molecular channels tends to \"0\". When the channel index is between 0.5D-D, the channel capacity of most molecular channels tends to \"1\". When the channel index is near 0.5D, the channel capacity of the corresponding sub-channel is uncertain. The Gaussian approximation construction method is applied to the Gaussian channel. When the channel index is small, the expected value of the logarithmic likelihood ratio is also small. When the channel index is large, the expected value of the logarithmic likelihood ratio is also large. When the channel index is in the  
Figure 4: System block diagram. middle, the expected value of the logarithmic likelihood ratio of the corresponding channel increases in a stepped trend. Professor [PERSON] [31] introduced the principle of Polar code compilation in detail in his own paper, which will not be repeated in this article. Next, the channel polarization method of ocean turbulence channels will be introduced. The degenerate construction method is only suitable for binary symmetric input channels, while ocean turbulence channels have a more complex channel environment, thus these three construction methods are not suitable. The Monte Carlo construction method is more suitable for ocean turbulence channels because of its universality. The Monte Carlo construction method is a more commonly used method in mathematical statistics.