Segmented cyclic redundancy check method for polarization codes

Abstract

The invention discloses a segmented cyclic redundancy check method for polarization codes mainly in order to solve the problems of high decoding complexity and high block error rate in the prior art. According to the technical scheme, the method comprises the steps as follows: first, the correct probability of the estimated value of each bit channel is calculated, and a channel for transmitting non-fixed bits is selected according to the probability; then, according to the correct probability of the estimated value of the channel for transmitting non-fixed bits, an information bit sequence is divided into sub information bit sequences, and segmented CRC check is carried out; next, polarization coding is carried out on the bit sequence joining in the segmented CRC check; and finally, the coded sequence is transmitted in the channel. Compared with the prior art, the method has the advantage that the method reduces the decoding complexity, improves the block error rate of decoding, and can be used to reduce the transmission error probability in the process of wireless communication.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, in particular to a segmented cyclic redundancy check (CRC) method of a polar code, which can be used in communication to reduce transmission error probability. Background technique [0002] Polar codes were originally proposed by Arikan. This code uses the theory of channel polarization. When the code length tends to be infinite, the channel capacity can be achieved by using the continuous elimination SC decoding scheme. But when the code length is limited, the performance of polar codes is not ideal. In this regard, scholars have proposed a variety of corresponding improvement and performance-enhancing methods: [0003] The first is the improved coding method proposed by B.Li et al. This method is a method for selecting the generation matrix of the polar code, and its scheme is to select according to the first error probability in the generation matrix of the high code rate RM c...

AI Technical Summary

Problems solved by technology

This algorithm can significantly improve the BLER performance of polar codes, and its performance can reach the lower bound of maximum likelihood ML decoding. The disadvantage is that this algorithm will cause error propagation.

This algorithm can effectively improve the performance of the polar code through a reasonable concatenated code design, but the CRC check for the entire polar code has a high complexity and is difficult to implement when the code length is long

[0007] In addition to the above four improvement methods, there are many other improvement methods, but none of these methods can improve decoding performance and complexity at the same time

Images