Polar code construction method based on general partial sequence and genetic algorithm under SCL decoder

Abstract

The invention provides a new polar code construction method, and the method comprises the following steps: selecting a reliable bit channel, an unreliable bit channel and an uncertain bit channel according to an improved universal partial order UPO algorithm; improving the genetic algorithm, and by introducing measures such as Hamming distance initialization and an elite individual protection mechanism, increasing the convergence speed and precision of a traditional genetic algorithm; searching an optimal solution in the uncertain bit channel according to an improved genetic algorithm, namely an information bit in the optimal solution, wherein the population is continuously evolved through own bit error rate performance, and finally converges to a bit set corresponding to the lowest bit error rate. The method has the advantages that compared with a traditional polarization code construction method, the bit set error code performance obtained through the algorithm is better.

Description

technical field [0001] The invention relates to the technical fields of data transmission and 5G mobile communication, in particular to a polar code construction method based on a universal partial order and a genetic algorithm under an SCL decoder. Background technique [0002] In the field of channel coding technology, the pursuit of Shannon's limit capacity has always been the goal of communication scholars. The early Turbo codes and LDPC codes were very close to this goal, but they failed to obtain strict mathematical proofs. At present, the only channel coding technology that can reach the Shannon limit is polar code technology. Polar codes are channel-specific codes based on channel polarization phenomena. Theoretical research on polar codes can be divided into polar code construction methods and polar code decoding algorithms. The main purpose of studying the construction method of polar code is to accurately select the bit channel whose channel capacity tends to be ...

AI Technical Summary

Problems solved by technology

Although the accuracy of the density evolution algorithm is very high, the method involves convolution calculation in the calculation process, which is very demanding on the hardware

The Gaussian approximation method has the problem that the polarization rate is too low

Recently, the polarization weight algorithm is used in the construction of polar codes. Although this algorithm can quickly construct bit sets, the error performance is relatively poor.

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