Low-complexity system linear block code decoding method

Abstract

The invention relates to the technical field of communication, in particular to a low-complexity system linear block code decoding method, which comprises the following steps of: performing hard decision on an element m with the maximum k-dimensional vector absolute value in a candidate set V of a decoding result, traversing to obtain all elements forming the candidate set V, and calculating a correlation value to obtain the decoding result. The relationship between the decoding performance and the calculated amount is judged according to the numerical value of the element m, so that the balance between the calculated performance and the calculated amount is considered, and accurate reference value is provided for different use scenes and requirements.

Description

Technical Field

[0001] The invention relates to the field of communication technology, in particular to a decoding method for a low-complexity system linear block code. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Linear block codes divide information bits into several groups, perform linear transformation on each group of information bit vectors on a finite field, and generate codewords of fixed length. When only the finite field F(2) is considered, the encoding process is expressed by the following formula: .

[0004] Where x is the input information bit vector on the F(2) field, and its length is represented by k; G is a finite field F(2). The dimension of the field called linear block code is Generator matrix of , where n>k; The codeword y is a row vector over the F(2) field.

[0005] For systematic linear block codes, the first The vector y(1:k) composed of elements is equal to x. Equivalently, the submatrix composed of the first k column vectors in G is The identity matrix of , The main diagonal elements of are 1, and the other elements are 0. G can be expressed as ,in for (nk)-dimensional matrix. Based on the generator matrix, we can get the check matrix ,here for The unit matrix of dimension, for The transposed matrix of .

[0006] In the prior art, the commonly used decoding algorithm for system linear block codes is a syndrome decoding algorithm based on hard decision, and the decoder input is the received codeword after hard decision. First, the received codeword and the check matrix are used to Calculate the syndrome, then look up the syndrome table to get the error pattern vector e, and then add the error pattern vector e and the receiving system bit vector obtained by hard decision Add and get the decoding result .

[0007] In addition, there is a maximum likelihood decoding algorithm with better performance. Encode all possible information words, and for each encoded codeword c, calculate The correlation value of the received soft bit is the information word corresponding to the largest correlation value, which is the decoding result. This algorithm has better performance than the above syndrome decoding algorithm based on hard decision, but the amount of calculation is too large when the codeword length is large, and it cannot be used in scenarios with high delay requirements or low power consumption.

[0008] Based on the above reasons, the present invention designs a low-complexity decoding method for system linear block codes, which achieves a decoding method with better performance than the syndrome decoding algorithm based on hard decision and lower computational complexity than the maximum likelihood decoding algorithm. Summary of the invention

[0009] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a low-complexity decoding method for system linear block codes, which achieves a decoding method with better performance than a syndrome decoding algorithm based on hard decision and lower computational complexity than a maximum likelihood decoding algorithm.

[0010] In order to achieve the above object, the present invention provides a decoding method of a low-complexity system linear block code, comprising the following steps: S1, determine the candidate set V of the decoding result, and the elements in the candidate set V are represented as k-dimensional vectors v; S2, for the received soft bit vector before decoding , where the first k elements is the received soft systematic bit, and the m elements with the largest absolute value among the k elements are taken, where m is a fixed positive integer, and ; S3, let the position corresponding to m elements be ; S4, make a hard decision on the m elements: each subscript of the element v Need to meet: A hard decision, where ; If the received element is less than 0, the corresponding original bit is judged to be 1; if the received element is greater than or equal to 0, the corresponding original bit is judged to be 0; S5, for index Elements other than vectors, constituting all elements of the candidate set V; S6, for each element v in the candidate set V, calculate its encoding result c by multiplying the encoding matrix and the element v, and then calculate and The largest correlation value corresponds to the information word The judgment is the decoding result; S7, the specific value of m is determined according to system requirements. When m is smaller, the decoding performance is better, but the decoding calculation amount is larger; conversely, when m is larger, the decoding calculation amount is smaller, but the decoding performance is lower.

[0011] Compared with the prior art, the present invention achieves a balance between computing performance and computing amount. DETAILED DESCRIPTION

[0012] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in the present invention have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0013] This embodiment provides a decoding method for a low-complexity system linear block code, comprising the following steps: S1, determine the candidate set V of the decoding result, and the elements in the candidate set V are represented as k-dimensional vectors v; S2, for the received soft bit vector before decoding , where the first k elements is the received soft systematic bit, and the m elements with the largest absolute value among the k elements are taken, where m is a fixed positive integer, and ; S3, let the position corresponding to m elements be ; S4, make a hard decision on the m elements: each subscript of the element v Need to meet: A hard decision, where ; If the received element is less than 0, the corresponding original bit is judged to be 1; if the received element is greater than or equal to 0, the corresponding original bit is judged to be 0; S5, for index For elements other than , we traverse all their possibilities. Since each element has two possibilities, 0 and 1, we get vectors, constituting all elements of the candidate set V; S6, for each element v in the candidate set V, calculate its encoding result c by multiplying the encoding matrix and the element v, and then calculate and The correlation value here is calculated by multiplying the corresponding elements of the two vectors and then summing them up. The information word corresponding to the largest correlation value is The judgment is the decoding result; S7, the specific value of m is determined according to system requirements. When m is smaller, the decoding performance is better, but the decoding calculation amount is larger; conversely, when m is larger, the decoding calculation amount is smaller, but the decoding performance is lower.

[0014] The above are only preferred embodiments of the present invention, which are only used to help understand the method and core ideas of the present application. The protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

[0015] The present invention solves the problems of insufficient performance or insufficient application scenarios due to large amount of calculation in the syndrome decoding algorithm based on hard decision and the maximum likelihood decoding algorithm in the prior art as a whole, and achieves a balance between computing performance and amount of calculation.

Claims

1. A decoding method for a low-complexity systematic linear block code, characterized in that: The following steps are involved: S1, determining a candidate set V of decoding results, where the elements in the candidate set V are represented as k-dimensional vectors v; S2, for the received soft bit vector before decoding , where the first k elements is the received soft systematic bit, and the m elements with the largest absolute values ​​among the k elements are taken, where m is a fixed positive integer, and ; S3, let the positions corresponding to the m elements be ; S4, make a hard decision on the m elements: each subscript of the element v Need to meet: A hard decision, where ; If the received element is less than 0, the corresponding original bit is judged to be 1; if the received element is greater than or equal to 0, the corresponding original bit is judged to be 0; S5, for index Elements other than vectors, constituting all elements of the candidate set V; S6, for each element v in the candidate set V, calculate its encoding result c by multiplying the encoding matrix and the element v, and then calculate and The largest correlation value corresponds to the information word The judgment is the decoding result; S7, the specific value of m is determined according to system requirements. When m is smaller, the decoding performance is better, but the decoding calculation amount is larger; conversely, when m is larger, the decoding calculation amount is smaller, but the decoding performance is lower.