LDPC-Polar cascaded system intermediate channel selection and distribution method

Abstract

The invention provides an LDPC (Low Density Parity Check) and polarization code cascaded intermediate channel selection and distribution method. According to the intermediate channel selection method, the first two information bits of a Rate-1 node are used as a selection set of the intermediate channel. The selected intermediate channels are subjected to reliability sorting through partial order, leaf set size and polarization weight. After the intermediate channel is selected, the variable nodes of the intermediate channel and the LDPC code are allocated. A bad channel and a plurality of good channels are distributed to variable nodes connected with a check node of the LDPC. In the decoding process, unreliable channels can be corrected in reliable channels. The invention aims to sort the intermediate channels by using a proper intermediate channel selection method, and design the corresponding relationship between the sorted intermediate channels and the variable nodes of the LDPC code so as to improve the bit error rate performance of the LDPC-Polar cascaded system.

Description

technical field [0001] The invention relates to channel coding technology, in particular to polar codes, and in particular to an intermediate channel selection and allocation method of an LDPC-Polar cascade system. Background technique [0002] Polar codes, proposed by Arikan, are the first channel coding schemes to theoretically reach the Shannon limit under Binary Input Discrete Memoryless Symmetric Channel (BI-DMSC). Two well-known decoding algorithms are Serial Cancellation (Successive Cancellation, SC) and Belief Propagation (Belief Propagation, BP) decoding algorithms. However, the SC decoding algorithm is a serial decoding algorithm, the decoding delay is high, and the error performance of the SC decoding algorithm under the limited code length is not ideal. In addition to the SC decoding algorithm, the BP decoding algorithm is an iterative parallel decoding algorithm, and its parallel characteristics make it suitable for low-latency and high-throughput systems. [...

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Problems solved by technology

[0004] However, the intermediate channel selection method proposed in the article (Abbas S M, Fan Y Z, Chen J, et al. Concatenated LDPC-PolarCodes Decoding Through Belief Propagation [C]. ISCAS, 2017.) uses the Bhattachary parameter as the selection method Part of it, but the Bach parameter can only be accurately calculated under the binary erasure channel (Binary Erasure Channel, BEC), so it is not appropriate to use the Bh parameter to select the middle channel under the non-BEC channel, which will lead to the decoding performance of the cascaded system bad

Bit mapping method (Yu Q P, Shi Z P, Deng L, et al.An improved belief propagation decoding of concatenated polarcodes with bit mapping[J].IEEE Communications Letters,2018,22(6):1160-1163.) in the middle The corresponding relationship between the channel and the variable nodes of the LDPC code does not consider the ordering of the reliability of the intermediate channel in detail, but only divides it into reliable and unreliable, which makes the bit error performance of the cascaded system poor.

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