Successive cancellation list polarization code decoding algorithm with effective low complexity based on random binary data flows and decoding structural frame thereof

Abstract

The invention discloses a successive cancellation list polarization code decoding algorithm with effective low complexity based on random binary data flows and a decoding structural frame thereof. The algorithm comprises the steps of converting received vectors to be decoded into corresponding input probability values through a channel message scaling algorithm; generating corresponding random binary data flows from the computed input probability values, and respectively inputting the data flows into two basic disk-type decoding frames; obtaining the conditional probability values of decoding through computing the data flows by the mixed node of the two basic disk-type decoding frames; working out the conditional probability random data flows of four paths by a phase inverter; obtaining the final judgment of the path probabilities through allowing the four condition probabilities to pass through an AND gate; through the computation of a feedback module, integrating signals, feeding back into the basic disk-type frames, allowing the data flows to pass through the basic disk-type decoding frames for the second time, and thereby obtaining the conditional probability values; and obtaining the optimal path decoding result. According to the algorithm provided by the invention, the complexity of the system is reduced, and meanwhile the random data flow decoding performance is improved.

Description

technical field [0001] The present invention relates to the effective decoding of polar codes in encoding technology, in particular to a decoding algorithm of low complexity serial cancellation list suitable for polar codes and its decoding framework. Background technique [0002] It is proposed that polar codes are the first class of channel coding that can achieve almost the capacity of symmetric binary-input discrete memoryless channels (B-DMCs). Due to its lower computational complexity of O(NlogN), where N is the polar code length; and the decoding structure in the form of Fast Fourier Transformation (FFT), the serial cancellation decoding (SC) algorithm has become the most One of the efficient polar decoding algorithms. However, compared with the maximum likelihood (ML) decoder, the decoding performance of the serial cancellation decoder still has a large decline. In order to narrow the performance gap caused by the sub-optimal path selection of the traditional ser...

AI Technical Summary

Problems solved by technology

However, directly applying the serial offset list decoder based on the random data stream in practice will lead to a serious degradation in decoding performance due to the continuous loss of randomness of the random sequence in the operation

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