Construction method of low-rank cyclic matrix and multivariate LDPC code associated with low-rank cyclic matrix

Abstract

The invention relates to the technical field of wireless communication and image processing, and discloses a construction method of a low-rank cyclic matrix and a multivariate LDPC code associated with the low-rank cyclic matrix. The search space of the cyclic matrix is reduced by using an isomorphism theory, and cyclic matrixes with different ranks are searched out by utilizing a rank algorithm.According to the method, the low-rank cyclic matrix which is easy to realize by hardware is obtained, and the construction method of the low-rank cyclic matrix is provided. A non-zero domain element assignment method is adopted, and a multivariate LDPC code construction method under different orders is provided. Compared with a binary LDPC code constructed based on a PEG algorithm, the constructedmultivariate LDPC code has 0.9 dB coding gain near the 10 <-5 > bit error rate in a BPSK modulation mode; and when the method is combined with high-order modulation, the performance is greatly improved. In an additive white Gaussian noise channel, the constructed multivariate LDPC code has good iterative decoding performance, and performance curves under five iterations and 50 iterations are almost overlapped.

Description

technical field [0001] The present invention relates to the field of wireless communication technology and image processing technology, in particular to a method for constructing a low-rank cyclic matrix and its associated multivariate LDPC code. Background technique [0002] At present, the basic functional stage of 5G standardization has been completed, and the next stage of standardization is mainly oriented to the main Internet of Things / vertical industry application scenarios, providing wireless communication transmission solutions to support the information society in the next 10 years. Standardization mainly includes two aspects: highly reliable and low-latency communication service (URLLC) and large-scale machine communication (mMTC). Different from 5G, 6G's "everything as you like" vision needs to meet the requirements of real-time, reliability, throughput and massive connections at the same time, which will pose new challenges to the new generation of wireless comm...

AI Technical Summary

Problems solved by technology

At present, the number of cyclic matrices constructed based on Euclidean geometry, Reed-Solomon codes, and two-dimensional maximum distance separable codes is limited; while the computer poor search method based on cyclic codes and isomorphism theory, with the matrix size and row (or column) weight increases, its search space will increase sharply, and it will become extremely difficult to find and determine different conformers

[0004] Through the above analysis, the existing problems and defects of the prior art are: the number of cyclic matrices constructed based on algebraic structures is extremely limited, which is difficult to meet the needs of practical applications; and the computational complexity of computer search algorithms based on cyclic codes and isomorphism theory is very high. High, the search space is large, especially when the matrix and row (column) weight is large, it is extremely difficult to complete the poor search

[0005] The difficulty of solving the above problems and defects is: it is very difficult to find a new algebraic structure to construct a cyclic matrix; when the weight of the matrix and rows (columns) is large, the computer-based search space is very large, and it is difficult to complete the poor search scheme, and It is also unrealistic to find matrices that are not isomorphic

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