WO2019120119A1 - Ldpc encoding method and device for communication signal - Google Patents

Ldpc encoding method and device for communication signal Download PDF

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Publication number
WO2019120119A1
WO2019120119A1 PCT/CN2018/120556 CN2018120556W WO2019120119A1 WO 2019120119 A1 WO2019120119 A1 WO 2019120119A1 CN 2018120556 W CN2018120556 W CN 2018120556W WO 2019120119 A1 WO2019120119 A1 WO 2019120119A1
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lcma
matrix
check
vector
communication signal
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PCT/CN2018/120556
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French (fr)
Chinese (zh)
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梁继业
刘华斌
孙宇佳
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华为技术有限公司
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    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M13/00—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
    • H03M13/03—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words
    • H03M13/05—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words using block codes, i.e. a predetermined number of check bits joined to a predetermined number of information bits
    • H03M13/11—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words using block codes, i.e. a predetermined number of check bits joined to a predetermined number of information bits using multiple parity bits
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received

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  • the present application relates to the field of codecs, and in particular to an LDPC encoding method and apparatus for communication signals.
  • Codec is widely used in various communication technologies such as electronic computers, televisions, and remote control. As the requirements for communication rates become higher and higher, more stringent requirements are placed on the codec method.
  • the related art popularly uses a low density parity check (LDPC) coding scheme.
  • LDPC is a forward error correction coding scheme that can flexibly implement parallel decoding, and can be applied to various modern communication systems and fields. For example, deep space communications, fiber optic communications, satellite digital video and audio broadcasting.
  • LDPC is a type of linear code defined by a check matrix.
  • the basic check matrix includes a system partial matrix N(x) and a check partial matrix M(x).
  • each element in M(x) represents a Z*Z unit matrix that is rotated rightward, and Z represents a scaling factor.
  • the first column vector of M(x) can be represented by Q(x).
  • the non-zero element in the first column vector of M(x) may be in the form of ABA or ABC.
  • the ABA form indicates that two non-zero elements in the first column vector of M(x) are the same.
  • the ABC form indicates that the non-zero elements in the first column vector of M(x) are different from each other. In the case of a short code length, the ABC form may result in decoding an error floor.
  • This method can eliminate the error leveling layer, but the coding complexity is large.
  • the operation of inverting Q(x) is involved. Since the matrix inversion needs to calculate the square matrix and the product of the square matrix and the polynomial, the square operation increases the computational complexity and increases with the scaling factor Z. Large, the coding complexity is higher. therefore.
  • the current LDPC coding scheme is computationally complex and supports fewer scaling factors. In order to adapt to higher communication rates, we hope to reduce the coding complexity as much as possible.
  • the present application provides an LDPC encoding method and apparatus for communication signals, which can reduce coding complexity and save computing resources.
  • an LDPC encoding method for a communication signal comprising: acquiring (NM) ⁇ 1 information bit vector I(x) according to information bits of a communication signal to be transmitted, wherein each element in I(x) Including Z information bits, N, M, and Z are positive integers respectively, N>M; according to the I(x) and M ⁇ (NM) system partial matrix N(x), the check set vector D(x), D is obtained.
  • the first column vector Q(x) of the check partial matrix M(x) is set, so that the vector D(x) can be performed in the encoding process.
  • Multiple linear cyclic shifts and summation to obtain the check bits avoid squared operations on Q(x), thereby reducing the complexity of encoding the communication signals and improving the communication quality.
  • a C a ⁇ lcmA 1 ⁇ h
  • b C b ⁇ lcmA 2 ⁇ h
  • lcmA 1 represents the least common multiple of the elements included in the set A 1
  • lcmA 2 represents the set A 2 included a least common multiple of the elements, the set A 1 and the set A2 respectively comprising at least one odd number
  • the intersection of the set A 1 and the set A 2 is an empty set
  • Z ⁇ 2 j
  • ⁇ is 2 or Any one of the set A 1 and the set A 2 , C a and C b are constants, and the C 0 (x) is respectively passed Performing GF(2) accumulation acquisition after cyclically shifting Z-2* ⁇ *h, (C a ⁇ lcmA 1 -2 ⁇ ) ⁇ h, and (C b ⁇ lcmA 2 -2 ⁇ ) ⁇ h
  • Z ⁇ ⁇ 2 j , ⁇ ⁇ ⁇ 2 A 1 A 2 ⁇ , ⁇ ⁇
  • a communication device for performing the method of any of the above first aspect or any of the possible implementations of the first aspect.
  • the apparatus comprises means for performing the method of any of the above-described first aspect or any of the possible implementations of the first aspect.
  • an encoder including a nonvolatile storage medium, and a processor, the nonvolatile storage medium storing an executable program, the processor being coupled to the nonvolatile storage medium And executing the executable program to implement the method of the first aspect or various implementations thereof.
  • a computer program product that, when executed by a communication device, causes the communication device to perform the method of the first aspect or various implementations thereof.
  • a computer readable medium storing program code for device execution, the program code comprising instructions for performing the method of the first aspect or various implementations thereof.
  • FIG. 1 is a schematic diagram of an application scenario of an encoding method according to an embodiment of the present application.
  • FIG. 2 is a schematic diagram of a check matrix of an embodiment of the present application.
  • FIG. 3 is a schematic diagram of a parity check matrix according to still another embodiment of the present application.
  • FIG. 4 is a schematic flowchart diagram of an encoding method according to an embodiment of the present application.
  • Figure 5 is a schematic illustration of an apparatus of an embodiment of the present application.
  • FIG. 6 is a schematic illustration of an apparatus in accordance with yet another embodiment of the present application.
  • GSM Global System of Mobile communication
  • CDMA Code Division Multiple Access
  • WCDMA Wideband Code Division Multiple Access
  • GPRS General Packet Radio Service
  • LTE Long Term Evolution
  • FDD Frequency Division Duplex
  • TDD Time Division Duplex
  • UMTS Universal Mobile Telecommunication System
  • WiMAX Worldwide Interoperability for Microwave Access
  • 5G fifth generation
  • 5G new radio
  • FIG. 1 is a schematic diagram showing a scenario of performing an LDPC codec method on a communication signal.
  • an LDPC encoder can transmit information bits of a communication signal to be transmitted from a source to an LDPC encoder for encoding to obtain an encoded codeword.
  • the encoded codeword includes check bits and information bits.
  • the communication signal modulated by the encoded codeword can be sent to the channel for transmission.
  • the channel may include interference and noise.
  • the LDPC decoder can obtain data to be decoded from the channel, and the LDPC decoder decodes the data, that is, performs error detection and error correction on the data to be decoded according to the check bits in the data to be decoded, and then The decoded information is output.
  • the LDPC encoding method can apply the various communication systems described above. And LDPC coding methods have potential applications in many other communication fields, such as deep space communications, fiber optic communications, satellite digital video, digital watermarking, magnetic/optical/holographic storage, mobile and fixed wireless communications, cable modems and digital users. Fields such as lines.
  • the embodiment of the present application provides an encoding method, which improves the parity part matrix M(x) on the basis of the LDPC encoding scheme, thereby reducing the complexity of the encoding, and expanding the range of the scaling factor, thereby improving the range.
  • the flexibility of coding is a part of the parity part matrix M(x) on the basis of the LDPC encoding scheme, thereby reducing the complexity of the encoding, and expanding the range of the scaling factor, thereby improving the range.
  • LDPC is a linear block code defined by a check matrix.
  • the linear block code can be uniquely determined by the check matrix.
  • the check matrix represents the correspondence between the information bits and the check bits.
  • the LDPC check matrix consists of a two-part matrix. A part of the matrix is the system partial matrix N(x), which corresponds to the systematic bits; the other part is the check partial matrix M(x), which corresponds to the check bits.
  • I represents the identity matrix.
  • M(x) is a double diagonal matrix.
  • A, B, and C in FIG. 2 indicate that the non-zero elements in the first column vector of M(x) are different from each other.
  • Each element in the check matrix represents a unit matrix that is rotated right by Z ⁇ Z.
  • Z is the scaling factor and represents the size of the unit matrix.
  • the value of each element represents the right shift number of the corresponding unit array loop.
  • the LDPC check matrix is a sparse matrix. Relative to the length of the row and column, the number of non-zero elements (or row weight, column weight) in each row and column of the LDPC check matrix is very small, which is why the LDPC code is called a low density code.
  • FIG. 3 is a schematic diagram of an LDPC check matrix of still another embodiment of the present application.
  • the LDPC check matrix of FIG. 2 may be further extended to add an additional parity matrix according to the extended parity check matrix.
  • the extended check bit can be calculated and added to the coded codeword.
  • FIG. 4 is a schematic flowchart diagram of an encoding method 400 according to an embodiment of the present application.
  • the coding method of the embodiment of the present application is introduced below with reference to FIG. 4.
  • an (N-M) x 1 information bit vector I(x) is acquired according to the information bits of the communication signal to be transmitted, wherein each element in I(x) includes Z information bits.
  • N, M, and Z are positive integers, respectively, N>M.
  • Z is the scaling factor.
  • the to-be-transmitted communication signal may be a to-be-transmitted communication signal to be encoded in the foregoing various communication systems.
  • the above-mentioned communication signal to be transmitted may belong to a video field, an audio field, an image field or any other communication signal to be encoded in the field of codec.
  • the communication signal to be transmitted includes a plurality of information bits.
  • the plurality of information bits may be sequentially divided into information bit vectors I(x) of 1 column of NM rows, wherein each of I(x) The element includes Z information bits.
  • the above information bits are vectors I(x) including N-M elements, and each element in the vector I(x) includes Z information bits.
  • the above information bits are divided into (N-M) ⁇ Z ⁇ 1 vectors.
  • a check set vector D(x) is obtained from the I(x) and Mx(N-M) system partial matrices N(x).
  • the LDPC check matrix is an M ⁇ N matrix including I(x) and M(x).
  • I(x) is an M ⁇ (N-M) matrix
  • M(x) is an M ⁇ M matrix.
  • the element represents a vector consisting of Z check bits.
  • the M x M check partial matrix M(x) is determined.
  • M(x) is a double diagonal matrix
  • Q -1 ( x) x -2 ⁇ h Q(x)
  • a and b are constants different from each other
  • h 2 j-1
  • ⁇ is a positive integer
  • j is a positive integer.
  • h represents the scaling factor index.
  • M(x) can be expressed as:
  • I(x) represents an identity matrix of Z ⁇ Z.
  • the inverse matrix Q -1 (x) for Q(x) can be obtained by linearly cyclically shifting Q(x) without squaring Q(x). This reduces the complexity of the encoding.
  • the check bit vector C(x) corresponding to I(x) is determined according to D(x) and M(x).
  • C(x) denotes a parity bit vector corresponding to I(x), and each element in C(x) represents a vector composed of Z parity bits.
  • S405. Generate an encoded codeword corresponding to the to-be-transmitted communication signal according to I(x) and C(x). For example, after determining the value of each element in C(x), that is, after determining the parity bit corresponding to the information bit of the communication signal to be transmitted, the parity bit is added after the information bit to generate an encoded codeword.
  • the first column vector Q(x) of the check partial matrix M(x) is set, so that the vector D(x) can be performed in the encoding process.
  • Multiple linear cyclic shifts and summation to obtain the check bits avoid squared operations on Q(x), thereby reducing the complexity of the encoding.
  • the polynomial matrix Q(x) will be further described below.
  • lcmA represents the least common multiple of the elements included in set A, and said set A includes at least one odd number.
  • a ⁇ 3,5,7,9,... ⁇ . h 2 j-1
  • h is the scaling factor index.
  • a supportable scaling factor Z ⁇ ⁇ 2 j , where ⁇ can be referred to as a scaling factor coefficient.
  • ⁇ can be 2 or any element in set A. For example, ⁇ 2,3,5,7,9,... ⁇ .
  • lcmA 1 represents the least common multiple of the elements included in the set A 1
  • lcmA 2 represents the least common multiple of the elements included in the set A 2
  • the set A 1 and the set A 2 respectively comprise at least one odd number
  • the set A 1 The intersection with the set A 2 is an empty set.
  • h 2 j-1
  • h is the scaling factor index.
  • a supportable scaling factor Z ⁇ ⁇ 2 j , where ⁇ can be 2 or any of the set A 1 and the set A 2 . For example, ⁇ 2,3,5,7,9,... ⁇ .
  • the inversion of Q(x) can be obtained by shifting the Q(x) cycle to the right by -2 ⁇ ⁇ ⁇ h bits.
  • the inverse matrix Q -1 (x) can be further decomposed into:
  • C 0 (x) According to the double diagonal property of M(x), C 0 (x) can be obtained by:
  • Rotate Right value Z corresponds to a different scaling factor and store, in real time without having to calculate Z-2 ⁇ ⁇ ⁇ h coding, (C a ⁇ lcmA 1 -2 ⁇ ⁇ ) ⁇ h and (C b ⁇ lcmA 2 - 2 ⁇ ⁇ ) ⁇ h three values.
  • the inverse matrix Q -1 (x) can be further decomposed into:
  • C 0 (x) According to the double diagonal property of M(x), C 0 (x) can be obtained by:
  • Rotate Right value Z corresponds to a different scaling factor and store, in real time without having to calculate Z-2 ⁇ ⁇ ⁇ h coding, (C a ⁇ lcmA 1 -2 ⁇ ⁇ ) ⁇ h and (C b ⁇ lcmA 2 - 2 ⁇ ⁇ ) ⁇ h three values.
  • the coding method provided by the embodiment of the present application reduces the calculation delay of the matrix multiplication, and at the same time expands the range of the supportable scaling factor Z due to the reduction of the coding complexity.
  • embodiments of the present application are able to provide a larger range of scaling factors Z for the same computing resources due to the reduced coding complexity.
  • the encoding method of the embodiment of the present application and the principle thereof are described above. Specific embodiments of the encoding method of the present application are further described below.
  • the range of the set A is A ⁇ 3, 5, 7, 9, 11, 13, 15 ⁇ , thereby scaling
  • the factor coefficients range from ⁇ 2,3,5,7,9,11,13,15 ⁇ .
  • the range of the scaling factor coefficient ⁇ may be determined first, and then the range of the set A may be determined according to ⁇ .
  • the above value is only an example, the range of the set A may be a combination of any odd number, and ⁇ may be 2 or any element in the set A.
  • the above polynomial matrix Q(x) and x 2 can be represented by a Z ⁇ Z matrix, respectively:
  • Q -1 (x) can be obtained by shifting the Q(x) cycle to the right by 2 columns, that is, Q -1 (x) can be expressed by the Z ⁇ Z matrix as:
  • Vector C 0 (x) can be obtained by performing GF(2) accumulation on the result of linear shifting by 2, 4, and 5 bits respectively.
  • the ranges of the sets A 1 and A 2 are A 1 ⁇ 3, 5, 7, 9, 15 ⁇ , respectively.
  • a 2 ⁇ 11,13 ⁇ . Therefore, the scaling factor coefficient ranges from ⁇ 2,3,5,7,9,11,13,15 ⁇ .
  • the range of the scaling factor coefficient ⁇ may be determined first, and the range of the sets A 1 and A 2 may be determined according to ⁇ .
  • the above values are only an example, and the range of the sets A 1 and A 2 may be a combination of any odd number, and ⁇ may be 2 or any of the elements A 1 and A 2 .
  • Q -1 (x) can be represented by a Z ⁇ Z matrix:
  • Vector C 0 (x) can be obtained by performing GF(2) accumulation by shifting the 0 , 1, and 3 bits to the right and cyclically shifting the result of the linear cyclic shift.
  • the coding method provided by the embodiment of the present application reduces the calculation delay of the matrix multiplication, and at the same time expands the range of the supportable scaling factor Z due to the reduction of the coding complexity.
  • embodiments of the present application are able to provide a larger range of scaling factors Z for the same computing resources due to the reduced coding complexity.
  • FIG. 5 is a schematic block diagram of a communication device 500 in accordance with an embodiment of the present application. It should be understood that the apparatus 500 is capable of performing the various steps of the method of FIGS. 1 through 4, and to avoid repetition, it will not be described in detail herein. Apparatus 500 includes:
  • D(x) ⁇ M(x)C(x) ⁇ mod2, where C 0 (x) is passed separately After performing multiple linear cyclic shifts and then acquiring the Galois field GF(2), C 0 (x) is the first element of C(x), and D i (x) is represented by D(x). The i+1th element.
  • the generating module 530 is configured to generate, according to I(x) and C(x), an encoded codeword corresponding to the to-be-transmitted communication signal.
  • FIG. 6 is a schematic structural diagram of a communication device 600 according to an embodiment of the present application.
  • device 600 includes one or more processors 620, one or more memories 610.
  • the memory 610 is for storing a computer program for calling and running the computer program from the memory 610 such that the apparatus performs the respective processes and/or operations in the encoding method of the present application.
  • Any processor 620 can be a central processing unit (CPU), a Convolutional Neural Network (CNN) processor, a general purpose processor, a digital signal processor (DSP), and a micro processing unit. Or any other component of an executable software program or code, or any combination thereof.
  • CPU central processing unit
  • CNN Convolutional Neural Network
  • DSP digital signal processor
  • apparatus 600 also includes a communication interface 630 for communicating with other devices, such as a decoder or receiver.
  • the communication interface 630 can be a transceiver or a transceiver circuit.
  • the device 600 can transmit the communication signal to be sent through the communication interface 630.
  • the communication interface 630 is configured to send an encoded codeword corresponding to the to-be-transmitted communication signal.
  • the processor 620 determines that the encoded codeword needs to be transmitted by executing a computer program and controls or drives the communication interface 630 to perform the transmitting.
  • communication interface 630 is the executor of the transmission action and processor 620 is the trigger or determinator of the action.
  • the apparatus 500 shown in FIG. 5 can be implemented by the apparatus 600 shown in FIG. 6.
  • the acquisition module 510, the determination module 520, and the generation module 530 can each be a software module executed by the processor 620 in FIG.
  • the disclosed systems, devices, and methods may be implemented in other manners.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division.
  • there may be another division manner for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not executed.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the functions may be stored in a computer readable storage medium if implemented in the form of a software functional unit and sold or used as a standalone product.
  • the technical solution of the present application which is essential or contributes to the prior art, or a part of the technical solution, may be embodied in the form of a software product, which is stored in a storage medium, including
  • the instructions are used to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present application.
  • the foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like, which can store program codes. .

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Abstract

The present application provides an LDPC encoding method and a device for a communication signal, for reducing encoding complexity. The encoding method comprises: acquiring an (N-M) × 1 information bit vector I(x) according to information bits of a communication signal to be sent; acquiring a check set vector D(x) according to I(x) and an M × (N-M) system partial matrix N(x), where D(x) meets the following condition: D(x) = {N(x) I(x)} mod 2; determining an M × M check partial matrix M(x), wherein M(x) is a bidiagonal matrix, a polynomial matrix Q(x) corresponding to a first column vector of M(x) is represented as Q(x) = I + x ah + x bh , Q -1 (x) = x -2×β×h Q(x), a and b are different constants, h = 2 j-1 , and β and j are positive integers; determining, according to D(x) and M(x), a check bit vector C(x) corresponding to I(x), where C(x) meets the following condition: D(x) = {M(x) C(x)} mod 2; and generating, according to I(x) and C(x), a code word corresponding to the communication signal to be sent.

Description

通信信号的LDPC编码方法和装置LDPC encoding method and device for communication signal
本申请要求于2017年12月21日提交中国专利局、申请号为201711390059.6、申请名称为“通信信号的LDPC编码方法和装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。The present application claims priority to Chinese Patent Application No. PCT Application No. No. No. No. No. No. No. No. No. No. No. in.
技术领域Technical field
本申请涉及编解码领域，尤其涉及通信信号的LDPC编码方法和装置。The present application relates to the field of codecs, and in particular to an LDPC encoding method and apparatus for communication signals.
背景技术Background technique
编解码在电子计算机、电视、遥控等各类通信技术方面广泛使用。随着对通信速率的要求越来越高，对编解码方法提出了更严格的要求。相关技术流行使用低密度奇偶校验(low density parity check,LDPC)编码方案。LDPC为一种可灵活实现并行译码的前向纠错编码方案，其可以应用于多种现代通信***和领域。例如，深空通信、光纤通信、卫星数字视频和音频广播等领域。Codec is widely used in various communication technologies such as electronic computers, televisions, and remote control. As the requirements for communication rates become higher and higher, more stringent requirements are placed on the codec method. The related art popularly uses a low density parity check (LDPC) coding scheme. LDPC is a forward error correction coding scheme that can flexibly implement parallel decoding, and can be applied to various modern communication systems and fields. For example, deep space communications, fiber optic communications, satellite digital video and audio broadcasting.
LDPC是通过校验矩阵定义的一类线性码。为了简化LDPC编码过程，现代通信***通常采用一种基于准循环的LDPC码作为基本码，其基本校验矩阵包括***部分矩阵N(x)和校验部分矩阵M(x)。其中，M(x)中的每一个元素代表一个循环右移的Z*Z单位阵，Z表示缩放因子。M(x)的第一列向量可以用Q(x)表示。其中若M(x)的第一列向量中的非零元素可以为ABA或ABC的形式。其中ABA形式表示M(x)的第一列向量中有两个非零元素相同。ABC形式表示M(x)的第一列向量中的非零元素互不相同。在码长较短的情况下，ABC形式可能会导致解码误码平层(error floor)。ABC形式下，相关技术中的Q(x)通常采用的多项式为Q(x)＝I+x 5h+x 12h，h＝2 j-2，j为大于2的整数。这种方式可以消除误码平层，但编码复杂度较大。在LDPC编码过程涉及到对Q(x)求逆的运算，由于矩阵求逆需要计算平方矩阵及平方矩阵与多项式的乘积得到，求平方运算增加了运算复杂度，且随着缩放因子Z的增大，编码复杂度越高。因此。当前LDPC编码方案的计算复杂度较大且可支持的缩放因子较少。为了适应更高的通信速率，我们希望能够尽可能地降低编码复杂度。 LDPC is a type of linear code defined by a check matrix. In order to simplify the LDPC encoding process, modern communication systems usually adopt a quasi-cyclic based LDPC code as a basic code, and the basic check matrix includes a system partial matrix N(x) and a check partial matrix M(x). Wherein, each element in M(x) represents a Z*Z unit matrix that is rotated rightward, and Z represents a scaling factor. The first column vector of M(x) can be represented by Q(x). Wherein the non-zero element in the first column vector of M(x) may be in the form of ABA or ABC. The ABA form indicates that two non-zero elements in the first column vector of M(x) are the same. The ABC form indicates that the non-zero elements in the first column vector of M(x) are different from each other. In the case of a short code length, the ABC form may result in decoding an error floor. In the ABC form, the polynomial commonly used for Q(x) in the related art is Q(x)=I+x 5h +x 12h , h=2 j-2 , and j is an integer greater than 2. This method can eliminate the error leveling layer, but the coding complexity is large. In the LDPC encoding process, the operation of inverting Q(x) is involved. Since the matrix inversion needs to calculate the square matrix and the product of the square matrix and the polynomial, the square operation increases the computational complexity and increases with the scaling factor Z. Large, the coding complexity is higher. therefore. The current LDPC coding scheme is computationally complex and supports fewer scaling factors. In order to adapt to higher communication rates, we hope to reduce the coding complexity as much as possible.
发明内容Summary of the invention
本申请提供一种通信信号的LDPC编码方法和装置，能够降低编码复杂度，节约计算资源。The present application provides an LDPC encoding method and apparatus for communication signals, which can reduce coding complexity and save computing resources.
第一方面，提供了一种通信信号的LDPC编码方法，包括：根据待发送通信信号的信息比特，获取(N-M)×1信息比特向量I(x)，其中I(x)中的每个元素包括Z个信息比特，N、M、Z分别为正整数，N＞M；根据I(x)和M×(N-M)***部分矩阵N(x)，获取校验集合向量D(x)，D(x)满足以下条件：D(x)＝{N(x)I(x)}mod2；确定M×M校验部分矩阵M(x)，M(x)为双对角线矩阵，M(x)的第一列向量对应的多项式矩阵Q(x)表示为 Q(x)＝I+x ah+x bh，且Q -1(x)＝x -2×β×hQ(x)，a、b为互不相同的常数，h＝2 j-1，β为正整数，j为正整数；根据D(x)和M(x)，确定I(x)对应的校验比特向量C(x)，C(x)表示I(x)对应的校验比特向量，C(x)中的每个元素表示由Z个校验比特组成的一个向量，C(x)满足以下条件：D(x)＝{M(x)C(x)}mod2，其中，C 0(x)是通过分别对
Figure PCTCN2018120556-appb-000001
进行多次线性循环移位之后再进行伽罗华域GF(2)累和获取的，C 0(x)为C(x)的第一个元素，D i(x)表示D(x)中的第i+1个元素；根据I(x)和C(x)，生成所述待发送通信信号对应的编码码字。 In a first aspect, an LDPC encoding method for a communication signal is provided, comprising: acquiring (NM)×1 information bit vector I(x) according to information bits of a communication signal to be transmitted, wherein each element in I(x) Including Z information bits, N, M, and Z are positive integers respectively, N>M; according to the I(x) and M×(NM) system partial matrix N(x), the check set vector D(x), D is obtained. (x) satisfying the following condition: D(x)={N(x)I(x)} mod2; determining M×M check partial matrix M(x), M(x) is a double diagonal matrix, M( The polynomial matrix Q(x) corresponding to the first column vector of x) is represented as Q(x)=I+x ah +x bh , and Q -1 (x)=x -2×β×h Q(x), a, b are constants different from each other, h=2 j-1 , β is a positive integer, j is a positive integer; according to D(x) and M(x), the parity bit vector C corresponding to I(x) is determined. (x), C(x) denotes a parity bit vector corresponding to I(x), and each element in C(x) represents a vector consisting of Z parity bits, and C(x) satisfies the following condition: D (x)={M(x)C(x)}mod2, where C 0 (x) is passed separately
Figure PCTCN2018120556-appb-000001
After performing multiple linear cyclic shifts and then acquiring the Galois field GF(2), C 0 (x) is the first element of C(x), and D i (x) is represented by D(x). The i+1th element; according to I(x) and C(x), generating an encoded codeword corresponding to the to-be-transmitted communication signal.
在本申请实施例中，在LDPC编码方案的基础上，对校验部分矩阵M(x)的第一列向量Q(x)进行设置，使得在编码过程中能够通过对向量D(x)进行多次线性循环移位并求和以获取校验比特，避免了对Q(x)的求平方运算，从而降低了对通信信号编码的复杂度，提高了通信质量。In the embodiment of the present application, on the basis of the LDPC coding scheme, the first column vector Q(x) of the check partial matrix M(x) is set, so that the vector D(x) can be performed in the encoding process. Multiple linear cyclic shifts and summation to obtain the check bits avoid squared operations on Q(x), thereby reducing the complexity of encoding the communication signals and improving the communication quality.
在一种可能的实现方式中，a＝2，b＝lcmA×h，lcmA表示集合A包括的元素的最小公倍数，所述集合A包括至少一个奇数，Z＝α×2 j，α为2或集合A中的任一元素，所述C 0(x)是通过分别对
Figure PCTCN2018120556-appb-000002
进行循环右移Z-2×β×h、2×(1-β)×h以及(lcmA-2×β)×h之后再进行GF(2)累和获取的，Z＝α×2 j，α∈{2 A}，β∈{2 lcmA}。 In a possible implementation manner, a=2, b=lcmA×h, lcmA represents the least common multiple of the elements included in the set A, the set A includes at least one odd number, Z=α×2 j , and α is 2 or Any element in set A, the C 0 (x) is passed separately
Figure PCTCN2018120556-appb-000002
Performing GG(2) accumulation acquisition after cyclically shifting Z-2×β×h, 2×(1-β)×h, and (lcmA-2×β)×h, Z=α×2 j , Α∈{2 A}, β∈{2 lcmA}.
在本申请实施例中，通过对Q(x)的系数a和b进行设置，使得在编码过程中能够通过对向量D(x)进行多次循环右移并求和以获取校验比特，避免了对Q(x)的求平方运算，从而降低了编码的复杂度，并能够扩展缩放因子的范围，提高了编码的灵活度。In the embodiment of the present application, by setting the coefficients a and b of Q(x), it is possible to obtain a check bit by multi-looping and summing the vector D(x) in the encoding process to obtain a check bit. The squaring operation on Q(x) reduces the complexity of the encoding and extends the range of the scaling factor, improving the flexibility of encoding.
在一种可能的实现方式中，a＝C a×lcmA 1×h，b＝C b×lcmA 2×h，lcmA 1表示集合A 1包括的元素的最小公倍数，lcmA 2表示集合A 2包括的元素的最小公倍数，所述集合A 1和所述集合A2分别包括至少一个奇数，且所述集合A 1和所述集合A 2的交集为空集，Z＝α×2 j，α为2或集合A 1和集合A 2中的任一元素，C a和C b均为常数，所述C 0(x)是通过分别对
Figure PCTCN2018120556-appb-000003
进行循环右移Z-2*β*h、(C a×lcmA 1-2×β)×h以及(C b×lcmA 2-2×β)×h之后再进行GF(2)累和获取的，Z＝α×2 j，α∈{2 A 1 A 2}，β∈{0 C a×lcmA 1 C b×lcmA 2}。 In a possible implementation, a=C a ×lcmA 1 ×h, b=C b ×lcmA 2 ×h, lcmA 1 represents the least common multiple of the elements included in the set A 1 , and lcmA 2 represents the set A 2 included a least common multiple of the elements, the set A 1 and the set A2 respectively comprising at least one odd number, and the intersection of the set A 1 and the set A 2 is an empty set, Z=α×2 j , α is 2 or Any one of the set A 1 and the set A 2 , C a and C b are constants, and the C 0 (x) is respectively passed
Figure PCTCN2018120556-appb-000003
Performing GF(2) accumulation acquisition after cyclically shifting Z-2*β*h, (C a ×lcmA 1 -2×β)×h, and (C b ×lcmA 2 -2×β)×h , Z = α × 2 j , α ∈ {2 A 1 A 2 }, β ∈ {0 C a × lcmA 1 C b × lcmA 2 }.
在本申请实施例中，通过对Q(x)的系数a和b进行设置，使得在编码过程中能够通过对向量D(x)进行多次循环右移并求和以获取校验比特，避免了对Q(x)的求平方运算，从而降低了编码的复杂度，并能够扩展缩放因子的范围，提高了编码的灵活度。In the embodiment of the present application, by setting the coefficients a and b of Q(x), it is possible to obtain a check bit by multi-looping and summing the vector D(x) in the encoding process to obtain a check bit. The squaring operation on Q(x) reduces the complexity of the encoding and extends the range of the scaling factor, improving the flexibility of encoding.
在一种可能的实现方式中，Q(x)符合以下条件中的至少一项：a与b为奇数，且a与b互质；c＝a-b为偶数且不为4或4的倍数；c与a、b均互质；lcmA 1与lcmA 2互质。 In a possible implementation manner, Q(x) meets at least one of the following conditions: a and b are odd numbers, and a and b are relatively prime; c=ab is even and not a multiple of 4 or 4; Both a and b are relatively prime; lcmA 1 and lcmA 2 are relatively prime.
在一种可能的实现方式中，
Figure PCTCN2018120556-appb-000004
In a possible implementation,
Figure PCTCN2018120556-appb-000004
第二方面，提供了一种通信装置，该装置用于执行上述第一方面或第一方面的任意可能的实现方式中的方法。具体地，该装置包括用于执行上述第一方面或第一方面的任意可能的实现方式中的方法的模块。In a second aspect, there is provided a communication device for performing the method of any of the above first aspect or any of the possible implementations of the first aspect. In particular, the apparatus comprises means for performing the method of any of the above-described first aspect or any of the possible implementations of the first aspect.
第三方面，提供一种编码器，包括非易失性存储介质，以及处理器，所述非易失性存储介质存储有可执行程序，所述处理器与所述非易失性存储介质连接，并执行所述可执行程序以实现所述第一方面或其各种实现方式中的方法。In a third aspect, an encoder is provided, including a nonvolatile storage medium, and a processor, the nonvolatile storage medium storing an executable program, the processor being coupled to the nonvolatile storage medium And executing the executable program to implement the method of the first aspect or various implementations thereof.
第四方面，提供一种计算机程序产品，当所述计算机程序产品被通信装置运行时，使得所述通信装置执行所述第一方面或其各种实现方式中的方法。In a fourth aspect, a computer program product is provided that, when executed by a communication device, causes the communication device to perform the method of the first aspect or various implementations thereof.
第五方面，提供一种计算机可读介质，所述计算机可读介质存储用于设备执行的程序代码，所述程序代码包括用于执行第一方面或其各种实现方式中的方法的指令。In a fifth aspect, a computer readable medium storing program code for device execution, the program code comprising instructions for performing the method of the first aspect or various implementations thereof.
附图说明DRAWINGS
图1是本申请实施例的编码方法的应用场景示意图。FIG. 1 is a schematic diagram of an application scenario of an encoding method according to an embodiment of the present application.
图2是本申请实施例的校验矩阵的示意图。2 is a schematic diagram of a check matrix of an embodiment of the present application.
图3是本申请又一实施例的校验矩阵的示意图。3 is a schematic diagram of a parity check matrix according to still another embodiment of the present application.
图4是本申请实施例的编码方法的流程示意图。FIG. 4 is a schematic flowchart diagram of an encoding method according to an embodiment of the present application.
图5是本申请实施例的装置的示意图。Figure 5 is a schematic illustration of an apparatus of an embodiment of the present application.
图6是本申请又一实施例的装置的示意图。Figure 6 is a schematic illustration of an apparatus in accordance with yet another embodiment of the present application.
具体实施方式Detailed ways
下面将结合附图，对本申请中的技术方案进行描述。The technical solutions in the present application will be described below with reference to the accompanying drawings.
本申请实施例的技术方案可以应用于各种通信***，例如：全球移动通讯(Global System of Mobile communication，GSM)***、码分多址(Code Division Multiple Access，CDMA)***、宽带码分多址(Wideband Code Division Multiple Access，WCDMA)***、通用分组无线业务(General Packet Radio Service，GPRS)、长期演进(Long Term Evolution，LTE)***、LTE频分双工(Frequency Division Duplex，FDD)***、LTE时分双工(Time Division Duplex，TDD)、通用移动通信***(Universal Mobile Telecommunication System，UMTS)、全球互联微波接入(Worldwide Interoperability for Microwave Access，WiMAX)通信***、未来的第五代(5th Generation，5G)***或新无线(New Radio，NR)等。在通信***中，对通信信号进行编码可提高通信质量。The technical solutions of the embodiments of the present application can be applied to various communication systems, such as a Global System of Mobile communication (GSM) system, a Code Division Multiple Access (CDMA) system, and a wideband code division multiple access. (Wideband Code Division Multiple Access, WCDMA) system, General Packet Radio Service (GPRS), Long Term Evolution (LTE) system, LTE Frequency Division Duplex (FDD) system, LTE Time Division Duplex (TDD), Universal Mobile Telecommunication System (UMTS), Worldwide Interoperability for Microwave Access (WiMAX) communication system, and the future fifth generation (5th Generation, 5G) system or new radio (New Radio, NR) and so on. In a communication system, encoding a communication signal improves communication quality.
图1示出了对通信信号做LDPC编解码方法的场景示意图。如图1所示，在编码方面，LDPC编码器可以从信源获取待发送通信信号的信息比特发送至LDPC编码器进行编码，以得到编码码字。编码码字包括校验比特和信息比特。对编码码字进行调制之后的通信信号可以送入信道进行传输。所述信道可能包括干扰和噪声。相应地，在解码方面，LDPC解码器可以从信道获取待解码的数据，LDPC解码器对该数据进行解码，即根据待解码数据中的校验比特对待解码数据进行误码检查以及纠错，然后输出解码后的信息。FIG. 1 is a schematic diagram showing a scenario of performing an LDPC codec method on a communication signal. As shown in FIG. 1, in terms of coding, an LDPC encoder can transmit information bits of a communication signal to be transmitted from a source to an LDPC encoder for encoding to obtain an encoded codeword. The encoded codeword includes check bits and information bits. The communication signal modulated by the encoded codeword can be sent to the channel for transmission. The channel may include interference and noise. Correspondingly, in terms of decoding, the LDPC decoder can obtain data to be decoded from the channel, and the LDPC decoder decodes the data, that is, performs error detection and error correction on the data to be decoded according to the check bits in the data to be decoded, and then The decoded information is output.
LDPC编码方法可以应用上文所述的各种通信***。并且LDPC编码方法在很多其他通信领域具有应用潜力，例如深空通信、光纤通信、卫星数字视频、数字水印、磁/光/全息存储、移动和固定无线通信、电缆调制/解调器和数字用户线等领域。The LDPC encoding method can apply the various communication systems described above. And LDPC coding methods have potential applications in many other communication fields, such as deep space communications, fiber optic communications, satellite digital video, digital watermarking, magnetic/optical/holographic storage, mobile and fixed wireless communications, cable modems and digital users. Fields such as lines.
本申请实施例提供了一种编码方法，其在LDPC编码方案的基础上，对校验部分矩阵M(x)进行改进，从而降低了编码的复杂度，并能够扩展缩放因子的范围，提高了编码的灵活度。The embodiment of the present application provides an encoding method, which improves the parity part matrix M(x) on the basis of the LDPC encoding scheme, thereby reducing the complexity of the encoding, and expanding the range of the scaling factor, thereby improving the range. The flexibility of coding.
图2是本申请实施例的LDPC校验矩阵的示意图。结合图2，下面简单介绍LDPC的校验矩阵。LDPC是通过校验矩阵定义的一种线性分组码。线性分组码可由校验矩阵唯一确定。其中校验矩阵表示信息比特与校验比特的对应关系。LDPC校验矩阵包括两部分矩 阵。一部分矩阵为***部分矩阵N(x)，其对应于***比特；另一部分为校验部分矩阵M(x)，其对应于校验比特。I(x)与M(x)满足以下条件：D(x)＝{N(x)I(x)}mod2＝{M(x)C(x)}mod2，mod 2表示进行伽罗华域GF(2)转换。其中，I表示单位矩阵。图2中M(x)为双对角线矩阵。且图2中的A、B、C表示M(x)的第一列向量中的非零元素互不相同。2 is a schematic diagram of an LDPC check matrix according to an embodiment of the present application. Referring to Figure 2, the check matrix of the LDPC is briefly introduced below. LDPC is a linear block code defined by a check matrix. The linear block code can be uniquely determined by the check matrix. The check matrix represents the correspondence between the information bits and the check bits. The LDPC check matrix consists of a two-part matrix. A part of the matrix is the system partial matrix N(x), which corresponds to the systematic bits; the other part is the check partial matrix M(x), which corresponds to the check bits. I(x) and M(x) satisfy the following condition: D(x)={N(x)I(x)}mod2={M(x)C(x)} mod2, mod 2 indicates that the Galois field is performed GF(2) conversion. Where I represents the identity matrix. In Figure 2, M(x) is a double diagonal matrix. And A, B, and C in FIG. 2 indicate that the non-zero elements in the first column vector of M(x) are different from each other.
校验矩阵中的每个元素代表一个循环右移Z×Z的单位阵。其中，Z为缩放因子，代表单位阵的大小。校验矩阵中，每一个元素的值代表相应单位阵循环右移位数。Each element in the check matrix represents a unit matrix that is rotated right by Z × Z. Where Z is the scaling factor and represents the size of the unit matrix. In the check matrix, the value of each element represents the right shift number of the corresponding unit array loop.
LDPC校验矩阵是一个稀疏矩阵。相对于行与列的长度，LDPC校验矩阵每行、列中非零元素的数目(或者称作行重、列重)非常小，这也是LDPC码之所以称为低密度码的原因。The LDPC check matrix is a sparse matrix. Relative to the length of the row and column, the number of non-zero elements (or row weight, column weight) in each row and column of the LDPC check matrix is very small, which is why the LDPC code is called a low density code.
图3示出了本申请又一实施例的LDPC校验矩阵的示意图。在一些场景中，例如NR场景中，为了适应可变码率编码需求，可以在图2的LDPC校验矩阵的基础上作进一步扩充，增加扩充校验(additional parity)矩阵，根据扩充校验矩阵，可以计算出扩充检验比特，并在编码码字中添加该扩充校验比特。FIG. 3 is a schematic diagram of an LDPC check matrix of still another embodiment of the present application. In some scenarios, such as the NR scenario, in order to adapt to the variable rate encoding requirement, the LDPC check matrix of FIG. 2 may be further extended to add an additional parity matrix according to the extended parity check matrix. The extended check bit can be calculated and added to the coded codeword.
图4示出了本申请实施例的编码方法400的流程示意图。下面结合图4，介绍本申请实施例的编码方法。在S401部分，根据待发送通信信号的信息比特，获取(N-M)×1信息比特向量I(x)，其中I(x)中的每个元素包括Z个信息比特。其中，N、M、Z分别为正整数，N＞M。Z为缩放因子。可选地，所述待发送通信信号可以是上述各种通信***中的待编码的待发送通信信号。上述待发送通信信号可以属于视频领域、音频领域、图像领域或其他任何需要编解码领域中的待编码的通信信号。FIG. 4 is a schematic flowchart diagram of an encoding method 400 according to an embodiment of the present application. The coding method of the embodiment of the present application is introduced below with reference to FIG. 4. In part S401, an (N-M) x 1 information bit vector I(x) is acquired according to the information bits of the communication signal to be transmitted, wherein each element in I(x) includes Z information bits. Where N, M, and Z are positive integers, respectively, N>M. Z is the scaling factor. Optionally, the to-be-transmitted communication signal may be a to-be-transmitted communication signal to be encoded in the foregoing various communication systems. The above-mentioned communication signal to be transmitted may belong to a video field, an audio field, an image field or any other communication signal to be encoded in the field of codec.
上述待发送通信信号包括多个信息比特，在编码时，可以依序将上述多个信息比特划分为规格为N-M行1列的信息比特向量I(x)，其中I(x)中的每个元素包括Z个信息比特。或者说，上述信息比特为包括N-M个元素的向量I(x)，且向量I(x)中的每个元素包括Z个信息比特。或者，也可以理解为，将上述信息比特划分为(N-M)×Z×1的向量。The communication signal to be transmitted includes a plurality of information bits. When encoding, the plurality of information bits may be sequentially divided into information bit vectors I(x) of 1 column of NM rows, wherein each of I(x) The element includes Z information bits. Or, the above information bits are vectors I(x) including N-M elements, and each element in the vector I(x) includes Z information bits. Alternatively, it can be understood that the above information bits are divided into (N-M) × Z × 1 vectors.
在S402部分，根据I(x)和M×(N-M)***部分矩阵N(x)，获取校验集合向量D(x)。其中，LDPC校验矩阵为M×N矩阵，其包括I(x)和M(x)。其中I(x)为M×(N-M)矩阵，M(x)为M×M矩阵。D(x)满足以下条件：D(x)＝{N(x)I(x)}mod2，其中C(x)表示I(x)对应的校验比特向量，C(x)中的每个元素表示由Z个校验比特组成的一个向量。In part S402, a check set vector D(x) is obtained from the I(x) and Mx(N-M) system partial matrices N(x). Wherein, the LDPC check matrix is an M×N matrix including I(x) and M(x). Where I(x) is an M×(N-M) matrix and M(x) is an M×M matrix. D(x) satisfies the following condition: D(x)={N(x)I(x)} mod2, where C(x) represents the parity bit vector corresponding to I(x), each of C(x) The element represents a vector consisting of Z check bits.
在S403部分，确定M×M校验部分矩阵M(x)。其中，M(x)为双对角线矩阵，M(x)的第一列向量对应的多项式矩阵Q(x)表示为Q(x)＝I+x ah+x bh，且Q -1(x)＝x -2×β×hQ(x)，a、b为互不相同的常数，h＝2 j-1，β为正整数，j为正整数。M(x)的第一列向量中的任一两个非零元素均不相同。h表示缩放因子指数。例如，M(x)可以表示为： In the S403 portion, the M x M check partial matrix M(x) is determined. Where M(x) is a double diagonal matrix, and the polynomial matrix Q(x) corresponding to the first column vector of M(x) is represented as Q(x)=I+x ah +x bh , and Q -1 ( x)=x -2×β×h Q(x), a and b are constants different from each other, h=2 j-1 , β is a positive integer, and j is a positive integer. Any two non-zero elements in the first column vector of M(x) are different. h represents the scaling factor index. For example, M(x) can be expressed as:
Figure PCTCN2018120556-appb-000005
其中，I(x)表示Z×Z的单位矩阵。
Figure PCTCN2018120556-appb-000005
Where I(x) represents an identity matrix of Z×Z.
可以通过设置Q(x)的系数a和b，使得Q -1(x)＝x -2×β×2jQ(x)＝x -2×β×hQ(x)。换句话说， 对Q(x)求逆矩阵Q -1(x)能够通过对Q(x)进行线性循环移位获取，而无需对Q(x)求平方。因此降低了编码的复杂度。 The coefficients a and b of Q(x) can be set such that Q -1 (x) = x - 2 × β × 2j Q(x) = x - 2 × β × h Q(x). In other words, the inverse matrix Q -1 (x) for Q(x) can be obtained by linearly cyclically shifting Q(x) without squaring Q(x). This reduces the complexity of the encoding.
在S404部分，根据D(x)和M(x)，确定I(x)对应的校验比特向量C(x)。C(x)表示I(x)对应的校验比特向量，C(x)中的每个元素表示由Z个校验比特组成的一个向量。具体地，可以先确定C(x)中的第一个元素C 0(x)，然后利用M(x)的双对角线结构，通过公式D(x)＝{M(x)C(x)}mod2，迭代计算出C(x)的其他元素。 In part S404, the check bit vector C(x) corresponding to I(x) is determined according to D(x) and M(x). C(x) denotes a parity bit vector corresponding to I(x), and each element in C(x) represents a vector composed of Z parity bits. Specifically, the first element C 0 (x) in C(x) can be determined first, and then the double diagonal structure of M(x) is used, by the formula D(x)={M(x)C(x) )} mod2, iteratively calculates other elements of C(x).
C(x)满足以下条件：D(x)＝{M(x)C(x)}mod2，其中，C 0(x)是通过分别对
Figure PCTCN2018120556-appb-000006
进行多次线性循环移位之后再进行伽罗华域GF(2)累和获取的，C 0(x)为C(x)的第一个元素，D i(x)表示D(x)中的第i+1个元素。具体地，
Figure PCTCN2018120556-appb-000007
由于Q -1(x)＝x -2×β×2jQ(x)＝x -2×β×hQ(x)，即Q -1(x)能够通过对Q(x)进行线性循环移位获取。因此，根据将Q -1(x)代入
Figure PCTCN2018120556-appb-000008
后得到的结果，也可以通过对
Figure PCTCN2018120556-appb-000009
进行多次线性循环移位，并对多次线性循环移位的结果再进行伽罗华域GF(2)累和获取C 0(x)。下文中将进一步描述获取C 0(x)的具体过程。 C(x) satisfies the following condition: D(x)={M(x)C(x)} mod2, where C 0 (x) is passed separately
Figure PCTCN2018120556-appb-000006
After performing multiple linear cyclic shifts and then acquiring the Galois field GF(2), C 0 (x) is the first element of C(x), and D i (x) is represented by D(x). The i+1th element. specifically,
Figure PCTCN2018120556-appb-000007
Since Q -1 (x) = x - 2 × β × 2j Q(x) = x - 2 × β × h Q(x), that is, Q -1 (x) can be linearly shifted by Q(x) Bit acquisition. Therefore, according to the substitution of Q -1 (x)
Figure PCTCN2018120556-appb-000008
After the results obtained, you can also pass the
Figure PCTCN2018120556-appb-000009
Multiple linear cyclic shifts are performed, and the results of multiple linear cyclic shifts are further subjected to Galois field GF(2) accumulation to obtain C 0 (x). The specific process of obtaining C 0 (x) will be further described below.
S405，根据I(x)和C(x)，生成所述待发送通信信号对应的编码码字。例如，在确定C(x)中的每个元素的值之后，即确定了待发送通信信号的信息比特对应的校验比特之后，将校验比特加在信息比特之后，以生成编码码字。S405. Generate an encoded codeword corresponding to the to-be-transmitted communication signal according to I(x) and C(x). For example, after determining the value of each element in C(x), that is, after determining the parity bit corresponding to the information bit of the communication signal to be transmitted, the parity bit is added after the information bit to generate an encoded codeword.
在本申请实施例中，在LDPC编码方案的基础上，对校验部分矩阵M(x)的第一列向量Q(x)进行设置，使得在编码过程中能够通过对向量D(x)进行多次线性循环移位并求和以获取校验比特，避免了对Q(x)的求平方运算，从而降低了编码的复杂度。In the embodiment of the present application, on the basis of the LDPC coding scheme, the first column vector Q(x) of the check partial matrix M(x) is set, so that the vector D(x) can be performed in the encoding process. Multiple linear cyclic shifts and summation to obtain the check bits avoid squared operations on Q(x), thereby reducing the complexity of the encoding.
下文将进一步描述多项式矩阵Q(x)。本申请实施例提出了两种设置校验矩阵的方案，其通过构造M(x)对应的多项式Q(x)＝I+x ah+x bh的系数a和b，以实现Q -1(x)＝x -2×β×hQ(x)。 The polynomial matrix Q(x) will be further described below. The embodiment of the present application proposes two schemes for setting a check matrix, which constructs a coefficient a and b of a polynomial Q(x)=I+x ah +x bh corresponding to M(x) to implement Q -1 (x) ) = x - 2 × β × h Q(x).
在第一种方案中，a＝2，b＝lcmA×h。第一种方案中构造的多项式Q(x)可以表示为：In the first scheme, a = 2, b = lcmA × h. The polynomial Q(x) constructed in the first scheme can be expressed as:
Q(x)＝I+x 2h+x lcmA×h             (1) Q(x)=I+x 2h +x lcmA×h (1)
其中，lcmA表示集合A包括的元素的最小公倍数，所述集合A包括至少一个奇数。例如，A∈{3,5,7,9,...}。h＝2 j-1，h为缩放因子指数。可支持的缩放因子Z＝α×2 j，其中，α可以称为缩放因子系数。α可以为2或者集合A中的任意元素。例如，α∈{2,3,5,7,9,...}。 Where lcmA represents the least common multiple of the elements included in set A, and said set A includes at least one odd number. For example, A∈{3,5,7,9,...}. h=2 j-1 , h is the scaling factor index. A supportable scaling factor Z = α × 2 j , where α can be referred to as a scaling factor coefficient. α can be 2 or any element in set A. For example, α∈{2,3,5,7,9,...}.
针对伽罗华域GF(2)的校验矩阵，我们可求得该多项式矩阵Q(x)的平方为：For the check matrix of the Galois field GF(2), we can find the square of the polynomial matrix Q(x) as:
Figure PCTCN2018120556-appb-000010
Figure PCTCN2018120556-appb-000010
若α＝2，并且由于I＝I Z，推导出x 2×2j＝x 0＝I为单位阵，因此， If α=2, and since I=I Z , it is derived that x 2×2j= x 0 =I is a unit matrix, therefore,
Figure PCTCN2018120556-appb-000011
Figure PCTCN2018120556-appb-000011
若α∈{3,5,7,9,...}，由于α为集合A中的元素，由于I＝I Z＝I α×2j，因此
Figure PCTCN2018120556-appb-000012
因此， If α∈{3,5,7,9,...}, since α is an element in set A, since I=I Z =I α×2j ,
Figure PCTCN2018120556-appb-000012
therefore,
Figure PCTCN2018120556-appb-000013
Figure PCTCN2018120556-appb-000013
在第二种方案中，a＝C a×lcmA 1×h，b＝C b×lcmA 2×h，lcmA 1。第二种方案中构造的多项式Q(x)可以表示为： In the second scheme, a = C a × lcmA 1 × h, b = C b × lcmA 2 × h, lcmA 1 . The polynomial Q(x) constructed in the second scheme can be expressed as:
Figure PCTCN2018120556-appb-000014
Figure PCTCN2018120556-appb-000014
其中，lcmA 1表示集合A 1包括的元素的最小公倍数，lcmA 2表示集合A 2包括的元素的最小公倍数，所述集合A 1和所述集合A2分别包括至少一个奇数，且所述集合A 1和所述集合A 2的交集为空集。h＝2 j-1，h为缩放因子指数。可支持的缩放因子Z＝α×2 j，其中，α可以为2或者集合A 1和集合A 2中的任意元素。例如，α∈{2,3,5,7,9,...}。 Wherein lcmA 1 represents the least common multiple of the elements included in the set A 1 , lcmA 2 represents the least common multiple of the elements included in the set A 2 , the set A 1 and the set A 2 respectively comprise at least one odd number, and the set A 1 The intersection with the set A 2 is an empty set. h=2 j-1 , h is the scaling factor index. A supportable scaling factor Z = α × 2 j , where α can be 2 or any of the set A 1 and the set A 2 . For example, α∈{2,3,5,7,9,...}.
另外，为了保证多项式矩阵Q(x)能简单求逆，Q(x)符合以下条件中的至少一项或全部项：a与b为奇数，且a与b互质；c＝a-b为偶数且不为4或4的倍数；c与a、b均互质；lcmA 1与lcmA 2互质。 In addition, in order to ensure that the polynomial matrix Q(x) can be simply inverted, Q(x) meets at least one or all of the following conditions: a and b are odd, and a and b are mutually prime; c=ab is even and Not a multiple of 4 or 4; c and a, b are both homogeneous; lcmA 1 and lcmA 2 are relatively prime.
可选地，可以通过对C a和C b进行配置，以使得Q(x)能够达到上述条件。 Alternatively, it is possible to configure C a and C b such that Q(x) can achieve the above conditions.
同样的，针对伽罗华域GF(2)的校验矩阵，我们可求得该多项式矩阵Q(x)的平方为：Similarly, for the check matrix of the Galois field GF(2), we can find the square of the polynomial matrix Q(x) as:
Figure PCTCN2018120556-appb-000015
Figure PCTCN2018120556-appb-000015
若α＝2，由于c＝a-b为偶数，因此，If α=2, since c=a-b is even, therefore,
Figure PCTCN2018120556-appb-000016
Figure PCTCN2018120556-appb-000016
若α∈{3,5,7,9,...}，由于α为集合A 1或集合A 2中的元素，因而
Figure PCTCN2018120556-appb-000017
或
Figure PCTCN2018120556-appb-000018
中的其中一个为单位阵I。 If α∈{3,5,7,9,...}, since α is an element in the set A 1 or the set A 2 ,
Figure PCTCN2018120556-appb-000017
or
Figure PCTCN2018120556-appb-000018
One of them is the unit array I.
例如，若α∈A 1，由于I＝I Z＝I α×2j， For example, if α ∈ A 1 , since I = I Z = I α × 2j ,
则
Figure PCTCN2018120556-appb-000019
then
Figure PCTCN2018120556-appb-000019
又例如，若α∈A 2，由于I＝I Z＝I α×2j， For another example, if α ∈ A 2 , since I=I Z =I α×2j ,
则
Figure PCTCN2018120556-appb-000020
then
Figure PCTCN2018120556-appb-000020
由上述分析可以见，第一种方案和第二种方案中，Q(x)均满足条件：As can be seen from the above analysis, in the first scheme and the second scheme, Q(x) satisfies the conditions:
Figure PCTCN2018120556-appb-000021
Figure PCTCN2018120556-appb-000021
针对上式(3)继续进行推导，可以获取Q -1(x)： To continue the derivation of the above equation (3), you can get Q -1 (x):
Figure PCTCN2018120556-appb-000022
Figure PCTCN2018120556-appb-000022
由公式(4)可知，对Q(x)求逆可通过对Q(x)循环右移-2×β×h位得到。As can be seen from equation (4), the inversion of Q(x) can be obtained by shifting the Q(x) cycle to the right by -2 × β × h bits.
接下来进一步描述上述两种方案中的C 0(x)的获取方法。 Next, the acquisition method of C 0 (x) in the above two schemes will be further described.
在第一种方案中，逆矩阵Q -1(x)可以进一步分解为： In the first scheme, the inverse matrix Q -1 (x) can be further decomposed into:
Figure PCTCN2018120556-appb-000023
Figure PCTCN2018120556-appb-000023
根据M(x)的双对角线特性，C 0(x)可以通过下式获取： According to the double diagonal property of M(x), C 0 (x) can be obtained by:
Figure PCTCN2018120556-appb-000024
Figure PCTCN2018120556-appb-000024
将公式(5)代入公式(6)，可获得：Substituting equation (5) into equation (6), you can get:
Figure PCTCN2018120556-appb-000025
Figure PCTCN2018120556-appb-000025
即由公式(7)可知，在具体实施例中，可以分别对
Figure PCTCN2018120556-appb-000026
进行循环右移Z-2×β×h、2×(1-β)×h以及(lcmA-2×β)×h之后，再对上述循环右移的结果进行GF(2)累和获取C 0(x)。 That is, as can be seen from the formula (7), in a specific embodiment, it can be separately
Figure PCTCN2018120556-appb-000026
After performing the right shift Z-2×β×h, 2×(1-β)×h, and (lcmA-2×β)×h, the result of the above-mentioned cyclic right shift is subjected to GF(2) accumulation acquisition C. 0 (x).
可选地，在具体实施例中，可预先计算出不同缩放因子Z对应的循环右移的值并存储，编码时无需实时计算Z-2×β×h、(C a×lcmA 1-2×β)×h以及(C b×lcmA 2-2×β)×h这三个值。 Alternatively, in particular embodiments, can be calculated in advance Rotate Right value Z corresponds to a different scaling factor and store, in real time without having to calculate Z-2 × β × h coding, (C a × lcmA 1 -2 × β) × h and (C b × lcmA 2 - 2 × β) × h three values.
在第二种方案中，逆矩阵Q -1(x)可以进一步分解为： In the second scheme, the inverse matrix Q -1 (x) can be further decomposed into:
Figure PCTCN2018120556-appb-000027
Figure PCTCN2018120556-appb-000027
根据M(x)的双对角线特性，C 0(x)可以通过下式获取： According to the double diagonal property of M(x), C 0 (x) can be obtained by:
Figure PCTCN2018120556-appb-000028
Figure PCTCN2018120556-appb-000028
将公式(5)代入公式(6)，可获得：Substituting equation (5) into equation (6), you can get:
Figure PCTCN2018120556-appb-000029
Figure PCTCN2018120556-appb-000029
即由公式(9)可知，在具体实施例中，可以分别对
Figure PCTCN2018120556-appb-000030
进行循环右移Z-2×β×h、(C a×lcmA 1-2×β)×h以及(C b×lcmA 2-2×β)×h之后，再对上述循环右移的结果进行GF(2)累和获取C 0(x)。 That is, as shown by the formula (9), in the specific embodiment, it can be separately
Figure PCTCN2018120556-appb-000030
After the right shift Z-2×β×h, (C a ×lcmA 1 -2×β)×h, and (C b ×lcmA 2 -2×β)×h, the result of the right shift of the above cycle is performed. GF(2) accumulates to obtain C 0 (x).
可选地，在具体实施例中，可预先计算出不同缩放因子Z对应的循环右移的值并存储，编码时无需实时计算Z-2×β×h、(C a×lcmA 1-2×β)×h以及(C b×lcmA 2-2×β)×h这三个值。 Alternatively, in particular embodiments, can be calculated in advance Rotate Right value Z corresponds to a different scaling factor and store, in real time without having to calculate Z-2 × β × h coding, (C a × lcmA 1 -2 × β) × h and (C b × lcmA 2 - 2 × β) × h three values.
相关技术中的LDCP编码过程中，需要求出多项式矩阵Q(x)的平方矩阵，然后再做两次矩阵乘法才能得到C 0(x)，其运算量较大。受编码复杂度的限制，相关技术中的LDCP编码方案能够支持的缩放因子Z有限。而本申请实施例提供的编码方法中，只需将计算得的向量
Figure PCTCN2018120556-appb-000031
分别进行线性循环移位并对线性循环移位的结果进行GF(2)累和即可得到C 0(x)。 In the LDCP encoding process in the related art, it is necessary to find the square matrix of the polynomial matrix Q(x), and then perform the matrix multiplication twice to obtain C 0 (x), which has a large amount of computation. Due to the limitation of coding complexity, the scaling factor Z that the LDCP coding scheme in the related art can support is limited. In the coding method provided by the embodiment of the present application, only the calculated vector is needed.
Figure PCTCN2018120556-appb-000031
The linear cyclic shift is performed separately and the result of the linear cyclic shift is subjected to GF(2) accumulation to obtain C 0 (x).
本申请实施例提供的编码方法和现有技术相比，减少了矩阵乘法的计算时延，同时由于编码复杂度的减少，扩展了可支持的缩放因子Z的范围。换句话说，由于编码复杂度的减少，对于相同的计算资源，本申请实施例能够提供更大的缩放因子Z的范围。Compared with the prior art, the coding method provided by the embodiment of the present application reduces the calculation delay of the matrix multiplication, and at the same time expands the range of the supportable scaling factor Z due to the reduction of the coding complexity. In other words, embodiments of the present application are able to provide a larger range of scaling factors Z for the same computing resources due to the reduced coding complexity.
上文介绍了本申请实施例的编码方法以及其原理。下文将进一步描述本申请的编码方法的具体实施例。针对第一种方案中多项式矩阵Q(x)的构造方法，在一个具体示例中，首先可以确定集合A的范围为A∈{3,5,7,9,11,13,15}，从而缩放因子系数的取值范围为α∈{2,3,5,7,9,11,13,15}。或者，也可以先确定缩放因子系数α的范围，再根据α确定集合A的范围。其中，上述取值仅作为示例，集合A的范围可以为任意奇数的组合，α可以是 2或集合A中的任意元素。The encoding method of the embodiment of the present application and the principle thereof are described above. Specific embodiments of the encoding method of the present application are further described below. For the construction method of the polynomial matrix Q(x) in the first scheme, in a specific example, it is first determined that the range of the set A is A∈{3, 5, 7, 9, 11, 13, 15}, thereby scaling The factor coefficients range from α∈{2,3,5,7,9,11,13,15}. Alternatively, the range of the scaling factor coefficient α may be determined first, and then the range of the set A may be determined according to α. Wherein, the above value is only an example, the range of the set A may be a combination of any odd number, and α may be 2 or any element in the set A.
根据集合A，可以得到如下多项式矩阵Q(x)：According to the set A, the following polynomial matrix Q(x) can be obtained:
Q(x)＝I+x 2h+x 5×7×9×11×13×h Q(x)=I+x 2h +x 5×7×9×11×13×h
若α＝3，j＝1，则缩放因子Z＝α×2 j＝3×2 1＝6,Q(x 2)＝Q(x 2)＝x 2×2j，且有Q -1(x)＝x -β×2jQ -1(x)＝x Zx -4Q(x)＝x 2Q(x)。 If α=3, j=1, the scaling factor Z=α×2 j =3×2 1 =6, Q(x 2 )=Q(x 2 )=x 2×2j , and there is Q −1 (x ) = x - β × 2j Q -1 (x) = x Z x - 4 Q(x) = x 2 Q(x).
上述多项式矩阵Q(x)以及x 2可以分别采用Z×Z矩阵表示为： The above polynomial matrix Q(x) and x 2 can be represented by a Z×Z matrix, respectively:
Figure PCTCN2018120556-appb-000032
Figure PCTCN2018120556-appb-000032
由上式推导，Q -1(x)可由Q(x)循环右移2列得到，即Q -1(x)可以采用Z×Z矩阵表示为： Derived from the above formula, Q -1 (x) can be obtained by shifting the Q(x) cycle to the right by 2 columns, that is, Q -1 (x) can be expressed by the Z × Z matrix as:
Figure PCTCN2018120556-appb-000033
Figure PCTCN2018120556-appb-000033
根据前面的推导C 0(x)可由下式获取： According to the previous derivation C 0 (x) can be obtained by:
C
Figure PCTCN2018120556-appb-000034
C
Figure PCTCN2018120556-appb-000034
即可以将向量
Figure PCTCN2018120556-appb-000035
分别进行循环右移2，4，5位并对线性循环移位的结果进行GF(2)累和即可得到C 0(x)。 Vector
Figure PCTCN2018120556-appb-000035
C 0 (x) can be obtained by performing GF(2) accumulation on the result of linear shifting by 2, 4, and 5 bits respectively.
针对第二种方案中多项式矩阵Q(x)的构造方法，在一个具体示例中，首先可以确定集合A 1和A 2的范围分别为A 1∈{3,5,7,9,15}，A 2∈{11,13}。从而缩放因子系数的取值范围为α∈{2,3,5,7,9,11,13,15}。或者，也可以先确定缩放因子系数α的范围，再根据α确定集合A 1和A 2的范围。其中，上述取值仅作为示例，集合A 1和A 2的范围可以为任意奇数的组合，α可以是2或集合A 1和A 2中的任意元素。 For a construction method of the polynomial matrix Q(x) in the second scheme, in a specific example, first, it can be determined that the ranges of the sets A 1 and A 2 are A 1 ∈{3, 5, 7, 9, 15}, respectively. A 2 ∈{11,13}. Therefore, the scaling factor coefficient ranges from α∈{2,3,5,7,9,11,13,15}. Alternatively, the range of the scaling factor coefficient α may be determined first, and the range of the sets A 1 and A 2 may be determined according to α. Wherein, the above values are only an example, and the range of the sets A 1 and A 2 may be a combination of any odd number, and α may be 2 or any of the elements A 1 and A 2 .
根据集合A 1和A 2，可以得到如下多项式矩阵Q(x)： According to the set A 1 and A 2 , the following polynomial matrix Q(x) can be obtained:
其中，C a＝3,C b＝1。 Where C a = 3 and C b =1.
Q(x)＝I+x 3×5×7×9×h+x 11×13×h Q(x)=I+x 3×5×7×9×h +x 11×13×h
若α＝2，j＝1，则缩放因子Z＝α×2 j＝2×2 1＝4,Q(x 2)＝Q(x 2)＝I，且有Q -1(x)＝Q(x)。 If α=2, j=1, the scaling factor Z=α×2 j =2×2 1 =4, Q(x 2 )=Q(x 2 )=I, and there is Q −1 (x)=Q (x).
上述多项式矩阵，Q -1(x)可以采用Z×Z矩阵表示为： The above polynomial matrix, Q -1 (x) can be represented by a Z × Z matrix:
Figure PCTCN2018120556-appb-000036
Figure PCTCN2018120556-appb-000036
根据前面的推导C 0(x)可由下式获取： According to the previous derivation C 0 (x) can be obtained by:
Figure PCTCN2018120556-appb-000037
Figure PCTCN2018120556-appb-000037
即可以将向量
Figure PCTCN2018120556-appb-000038
分别进行循环右移0，1，3位并对线性循环移位的结果进行GF(2)累和即可得到C 0(x)。 Vector
Figure PCTCN2018120556-appb-000038
C 0 (x) can be obtained by performing GF(2) accumulation by shifting the 0 , 1, and 3 bits to the right and cyclically shifting the result of the linear cyclic shift.
本申请实施例提供的编码方法和现有技术相比，减少了矩阵乘法的计算时延，同时由于编码复杂度的减少，扩展了可支持的缩放因子Z的范围。换句话说，由于编码复杂度的减少，对于相同的计算资源，本申请实施例能够提供更大的缩放因子Z的范围。Compared with the prior art, the coding method provided by the embodiment of the present application reduces the calculation delay of the matrix multiplication, and at the same time expands the range of the supportable scaling factor Z due to the reduction of the coding complexity. In other words, embodiments of the present application are able to provide a larger range of scaling factors Z for the same computing resources due to the reduced coding complexity.
上文结合图1-图4介绍了本申请实施例的编码方法，下文将结合图5-图6描述本申请实施例的通信装置。The coding method of the embodiment of the present application is described above with reference to FIG. 1 to FIG. 4. The communication device of the embodiment of the present application will be described below with reference to FIG. 5 to FIG.
图5是本申请实施例的通信装置500的示意性框图。应理解，装置500能够执行图1至图4的方法的各个步骤，为了避免重复，此处不再详述。装置500包括：FIG. 5 is a schematic block diagram of a communication device 500 in accordance with an embodiment of the present application. It should be understood that the apparatus 500 is capable of performing the various steps of the method of FIGS. 1 through 4, and to avoid repetition, it will not be described in detail herein. Apparatus 500 includes:
获取模块510，用于根据待发送通信信号的信息比特，获取(N-M)×1信息比特向量I(x)，其中I(x)中的每个元素包括Z个信息比特，N、M、Z分别为正整数，N＞M；所述获取模块510还用于根据I(x)和M×(N-M)***部分矩阵N(x)，获取校验集合向量D(x)，D(x)满足以下条件：D(x)＝{N(x)I(x)}mod2。The obtaining module 510 is configured to acquire (NM)×1 information bit vector I(x) according to information bits of the communication signal to be sent, where each element in I(x) includes Z information bits, N, M, and Z. A positive integer, N>M, respectively; the obtaining module 510 is further configured to obtain a check set vector D(x), D(x) according to the I(x) and M×(NM) system partial matrix N(x). The following condition is satisfied: D(x)={N(x)I(x)} mod2.
确定模块520，用于确定M×M校验部分矩阵M(x)，M(x)为双对角线矩阵，M(x)的第一列向量对应的多项式矩阵Q(x)表示为Q(x)＝I+x ah+x bh，且Q -1(x)＝x -2×β×hQ(x)，a、b为互不相同的常数，h＝2 j-1，β为正整数，j为正整数；所述确定模块520还用于根据D(x)和M(x)，确定I(x)对应的校验比特向量C(x)，C(x)表示I(x)对应的校验比特向量，C(x)中的每个元素表示由Z个校验比特组成的一个向量，C(x)满足以下条件： The determining module 520 is configured to determine the M×M check partial matrix M(x), where M(x) is a double diagonal matrix, and the polynomial matrix Q(x) corresponding to the first column vector of M(x) is represented as Q (x)=I+x ah +x bh , and Q -1 (x)=x -2×β×h Q(x), a and b are constants different from each other, h=2 j-1 , β a positive integer, j is a positive integer; the determining module 520 is further configured to determine, according to D(x) and M(x), a parity bit vector C(x) corresponding to I(x), where C(x) represents I (x) Corresponding check bit vector, each element in C(x) represents a vector consisting of Z check bits, and C(x) satisfies the following conditions:
D(x)＝{M(x)C(x)}mod2，其中，C 0(x)是通过分别对
Figure PCTCN2018120556-appb-000039
进行多次线性循环移位之后再进行伽罗华域GF(2)累和获取的，C 0(x)为C(x)的第一个元素，D i(x)表示D(x)中的第i+1个元素。 D(x)={M(x)C(x)} mod2, where C 0 (x) is passed separately
Figure PCTCN2018120556-appb-000039
After performing multiple linear cyclic shifts and then acquiring the Galois field GF(2), C 0 (x) is the first element of C(x), and D i (x) is represented by D(x). The i+1th element.
生成模块530，用于根据I(x)和C(x)，生成所述待发送通信信号对应的编码码字。The generating module 530 is configured to generate, according to I(x) and C(x), an encoded codeword corresponding to the to-be-transmitted communication signal.
图6是本申请实施例提供的通信装置600的示意性结构图。如图6所示，装置600包括：一个或多个处理器620，一个或多个存储器610。该存储器610用于存储计算机程序， 该处理器620用于从存储器610中调用并运行该计算机程序，使得该装置执行本申请的编码方法中的相应流程和/或操作。为了简洁，此处不再赘述。任一处理器620可以是中央处理器(Central Processing Unit，CPU)，卷积神经网络(Convolutional Neural Network,CNN)处理器，通用处理器，数字信号处理器(Digital Signal Processor，DSP)，微处理器或者其他可执行软件程序或代码的部件或者其任意组合。FIG. 6 is a schematic structural diagram of a communication device 600 according to an embodiment of the present application. As shown in FIG. 6, device 600 includes one or more processors 620, one or more memories 610. The memory 610 is for storing a computer program for calling and running the computer program from the memory 610 such that the apparatus performs the respective processes and/or operations in the encoding method of the present application. For the sake of brevity, it will not be repeated here. Any processor 620 can be a central processing unit (CPU), a Convolutional Neural Network (CNN) processor, a general purpose processor, a digital signal processor (DSP), and a micro processing unit. Or any other component of an executable software program or code, or any combination thereof.
可选地，装置600还包括通信接口630，所述通信接口630用于与其他设备，如解码器或接收器进行通信。所述通信接口630可以是收发器或收发电路、例如，装置600可以通过所述通信接口630发送上述待发送通信信号。具体地，在本实施例中，所述通信接口630用于发送所述待发送通信信号对应的编码码字。所述处理器620通过执行计算机程序确定需要发送所述编码码字，并且控制或驱动所述通信接口630执行所述发送。因此，通信接口630是发送动作的执行者，而处理器620是动作的触发者或决定者。Optionally, apparatus 600 also includes a communication interface 630 for communicating with other devices, such as a decoder or receiver. The communication interface 630 can be a transceiver or a transceiver circuit. For example, the device 600 can transmit the communication signal to be sent through the communication interface 630. Specifically, in this embodiment, the communication interface 630 is configured to send an encoded codeword corresponding to the to-be-transmitted communication signal. The processor 620 determines that the encoded codeword needs to be transmitted by executing a computer program and controls or drives the communication interface 630 to perform the transmitting. Thus, communication interface 630 is the executor of the transmission action and processor 620 is the trigger or determinator of the action.
需要说明的是，图5中所示的装置500可以通过图6中所示的装置600实现。例如，获取模块510、确定模块520和生成模块530均可以是由图6中的处理器620执行的软件模块。It should be noted that the apparatus 500 shown in FIG. 5 can be implemented by the apparatus 600 shown in FIG. 6. For example, the acquisition module 510, the determination module 520, and the generation module 530 can each be a software module executed by the processor 620 in FIG.
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the various examples described in connection with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the solution. A person skilled in the art can use different methods to implement the described functions for each particular application, but such implementation should not be considered to be beyond the scope of the present application.
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的***、装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。A person skilled in the art can clearly understand that for the convenience and brevity of the description, the specific working process of the system, the device and the unit described above can refer to the corresponding process in the foregoing method embodiment, and details are not described herein again.
在本申请所提供的几个实施例中，应该理解到，所揭露的***、装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个***，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of the unit is only a logical function division. In actual implementation, there may be another division manner, for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
所述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。The functions may be stored in a computer readable storage medium if implemented in the form of a software functional unit and sold or used as a standalone product. Based on such understanding, the technical solution of the present application, which is essential or contributes to the prior art, or a part of the technical solution, may be embodied in the form of a software product, which is stored in a storage medium, including The instructions are used to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like, which can store program codes. .
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖 在本申请的保护范围之内。因此，本申请的保护范围应以所述权利要求的保护范围为准。The foregoing is only a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto, and any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present application. It should be covered by the scope of protection of this application. Therefore, the scope of protection of the present application should be determined by the scope of the claims.

Claims (12)

  1. 一种通信信号的低密度奇偶校验LDPC编码方法，其特征在于，包括：A low density parity check LDPC encoding method for communication signals, comprising:
    根据待发送通信信号的信息比特，获取(N-M)×1信息比特向量I(x)，其中I(x)中的每个元素包括Z个信息比特，N、M、Z分别为正整数，N＞M；Obtaining (NM)×1 information bit vector I(x) according to information bits of the communication signal to be transmitted, wherein each element in I(x) includes Z information bits, and N, M, and Z are positive integers, respectively, N >M;
    根据I(x)和LDPC的M×(N-M)***部分矩阵N(x)，获取校验集合向量D(x)，D(x)满足以下条件：D(x)＝{N(x)I(x)}mod 2；According to the M×(NM) system partial matrix N(x) of I(x) and LDPC, the check set vector D(x) is obtained, and D(x) satisfies the following condition: D(x)={N(x)I (x)}mod 2;
    确定LDPC的M×M校验部分矩阵M(x)，M(x)为双对角线矩阵，M(x)的第一列向量对应的多项式矩阵Q(x)表示为Q(x)＝I+x ah+x bh，且Q -1(x)＝x -2×β×hQ(x)，a、b为互不相同的常数，h＝2 j-1，β为正整数，j为正整数； Determining the M×M check partial matrix M(x) of LDPC, M(x) is a double diagonal matrix, and the polynomial matrix Q(x) corresponding to the first column vector of M(x) is represented as Q(x)= I+x ah +x bh , and Q -1 (x)=x -2×β×h Q(x), a and b are constants different from each other, h=2 j-1 , β is a positive integer, j is a positive integer;
    根据D(x)和M(x)，确定I(x)对应的校验比特向量C(x)，C(x)中的每个元素表示由Z个校验比特组成的一个向量，C(x)满足以下条件：D(x)＝{M(x)C(x)}mod 2，其中，C 0(x)是通过分别对
    Figure PCTCN2018120556-appb-100001
    进行多次线性循环移位之后再进行伽罗华域GF(2)累和获取的，C 0(x)为C(x)的第一个元素，D i(x)表示D(x)中的第i+1个元素；     According to D(x) and M(x), a check bit vector C(x) corresponding to I(x) is determined, and each element in C(x) represents a vector consisting of Z check bits, C ( x) satisfies the following condition: D(x)={M(x)C(x)} mod 2, where C 0 (x) is passed separately
    Figure PCTCN2018120556-appb-100001
    After performing multiple linear cyclic shifts and then acquiring the Galois field GF(2), C 0 (x) is the first element of C(x), and D i (x) is represented by D(x). The i+1th element;
    根据I(x)和C(x)，生成所述待发送通信信号对应的编码码字。And generating an encoded codeword corresponding to the to-be-transmitted communication signal according to I(x) and C(x).
  2. 如权利要求1所述的方法，其特征在于，a＝2，b＝lcmA×h，lcmA表示集合A包括的元素的最小公倍数，所述集合A包括至少一个奇数，Z＝α×2 j，α为2或集合A中的任一元素，所述C 0(x)是通过分别对
    Figure PCTCN2018120556-appb-100002
    进行循环右移Z-2×β×h、2×(1-β)×h以及(lcmA-2×β)×h之后再进行GF(2)累和获取的，Z＝α×2 j，α∈{2 A}，β∈{2 lcmA}。     The method according to claim 1, wherein, a = 2, b = lcmA × h, lcmA represents the least common multiple of the elements comprising the set of A, the set A comprising at least an odd number, Z = α × 2 j, α is 2 or any element in set A, and the C 0 (x) is passed separately
    Figure PCTCN2018120556-appb-100002
    Performing GG(2) accumulation acquisition after cyclically shifting Z-2×β×h, 2×(1-β)×h, and (lcmA-2×β)×h, Z=α×2 j , Α∈{2 A}, β∈{2 lcmA}.
  3. 如权利要求1所述的方法，其特征在于，a＝C a×lcmA 1×h，b＝C b×lcmA 2×h，lcmA 1表示集合A 1包括的元素的最小公倍数，lcmA 2表示集合A 2包括的元素的最小公倍数，所述集合A 1和所述集合A2分别包括至少一个奇数，且所述集合A 1和所述集合A 2的交集为空集，Z＝α×2 j，α为2或集合A 1和集合A 2中的任一元素，C a和C b均为常数，所述C 0(x)是通过分别对
    Figure PCTCN2018120556-appb-100003
    进行循环右移Z-2*β*h、(C a×lcmA 1-2×β)×h以及(C b×lcmA 2-2×β)×h之后再进行GF(2)累和获取的，Z＝α×2 j，α∈{2 A 1 A 2}，β∈{0 C a×lcmA 1 C b×lcmA 2}。     The method according to claim 1, wherein a = C a × lcmA 1 × h, b = C b × lcmA 2 × h, lcmA 1 represents a least common multiple of elements included in the set A 1 , and lcmA 2 represents a set A least common multiple of the elements included in A 2 , the set A 1 and the set A 2 respectively comprise at least one odd number, and the intersection of the set A 1 and the set A 2 is an empty set, Z=α×2 j , α is 2 or any of the set A 1 and the set A 2 , and both C a and C b are constants, and the C 0 (x) is passed separately
    Figure PCTCN2018120556-appb-100003
    Performing GF(2) accumulation acquisition after cyclically shifting Z-2*β*h, (C a ×lcmA 1 -2×β)×h, and (C b ×lcmA 2 -2×β)×h , Z = α × 2 j , α ∈ {2 A 1 A 2 }, β ∈ {0 C a × lcmA 1 C b × lcmA 2 }.
  4. 如权利要求3所述的方法，其特征在于，Q(x)符合以下条件中的至少一项：The method of claim 3 wherein Q(x) meets at least one of the following conditions:
    a与b为奇数，且a与b互质；a and b are odd numbers, and a and b are relatively prime;
    c＝a-b为偶数且不为4或4的倍数；c=a-b is an even number and is not a multiple of 4 or 4;
    c与a、b均互质；c and a, b are mutually homogeneous;
    lcmA 1与lcmA 2互质。 lcmA 1 is relatively prime to lcmA 2 .
  5. 权利要求2-4中任一项所述的方法，其特征在于，
    Figure PCTCN2018120556-appb-100004
    The method of any of claims 2-4, wherein
    Figure PCTCN2018120556-appb-100004
  6. 一种通信装置，其特征在于，包括：A communication device, comprising:
    获取模块，用于根据待发送通信信号的信息比特，获取(N-M)×1信息比特向量I(x)，其中I(x)中的每个元素包括Z个信息比特，N、M、Z分别为正整数，N＞M；And an obtaining module, configured to acquire (NM)×1 information bit vector I(x) according to information bits of the communication signal to be sent, where each element in I(x) includes Z information bits, and N, M, and Z respectively Is a positive integer, N>M;
    所述获取模块还用于根据I(x)和M×(N-M)***部分矩阵N(x)，获取校验集合向量D(x)，D(x)满足以下条件：D(x)＝{N(x)I(x)}mod 2；The obtaining module is further configured to obtain a check set vector D(x) according to the I(x) and M×(NM) system partial matrix N(x), where D(x) satisfies the following condition: D(x)={ N(x)I(x)}mod 2;
    确定模块，用于确定M×M校验部分矩阵M(x)，M(x)为双对角线矩阵，M(x)的第一列向量对应的多项式矩阵Q(x)表示为Q(x)＝I+x ah+x bh，且Q -1(x)＝x -2×β×hQ(x)，a、b为互不相同的常数，h＝2 j-1，β为正整数，j为正整数； a determining module for determining an M×M check partial matrix M(x), M(x) is a double diagonal matrix, and a polynomial matrix Q(x) corresponding to the first column vector of M(x) is represented as Q ( x)=I+x ah +x bh , and Q -1 (x)=x -2×β×h Q(x), a and b are constants different from each other, h=2 j-1 , β is a positive integer, j is a positive integer;
    所述确定模块还用于根据D(x)和M(x)，确定I(x)对应的校验比特向量C(x)，C(x)表示I(x)对应的校验比特向量，C(x)中的每个元素表示由Z个校验比特组成的一个向量，C(x)满足以下条件：D(x)＝{M(x)C(x)}mod 2，其中，C 0(x)是通过分别对
    Figure PCTCN2018120556-appb-100005
    进行多次线性循环移位之后再进行伽罗华域GF(2)累和获取的，C 0(x)为C(x)的第一个元素，D i(x)表示D(x)中的第i+1个元素；     The determining module is further configured to determine, according to D(x) and M(x), a parity bit vector C(x) corresponding to I(x), where C(x) represents a parity bit vector corresponding to I(x), Each element in C(x) represents a vector consisting of Z parity bits, and C(x) satisfies the following condition: D(x)={M(x)C(x)} mod 2, where C 0 (x) is passed separately
    Figure PCTCN2018120556-appb-100005
    After performing multiple linear cyclic shifts and then acquiring the Galois field GF(2), C 0 (x) is the first element of C(x), and D i (x) is represented by D(x). The i+1th element;
    生成模块，用于根据I(x)和C(x)，生成所述待发送通信信号对应的编码码字。And a generating module, configured to generate, according to I(x) and C(x), an encoded codeword corresponding to the to-be-transmitted communication signal.
  7. 如权利要求6所述的装置，其特征在于，a＝2，b＝lcmA×h，lcmA表示集合A包括的元素的最小公倍数，所述集合A包括至少一个奇数，Z＝α×2 j，α为2或集合A中的任一元素，所述C 0(x)是通过分别对
    Figure PCTCN2018120556-appb-100006
    进行循环右移Z-2×β×h、2×(1-β)×h以及(lcmA-2×β)×h之后再进行GF(2)累和获取的，Z＝α×2 j，α∈{2 A}，β∈{2 lcmA}。     The apparatus according to claim 6, wherein a = 2, b = lcmA × h, lcmA represents a least common multiple of elements included in set A, said set A includes at least one odd number, Z = α × 2 j , α is 2 or any element in set A, and the C 0 (x) is passed separately
    Figure PCTCN2018120556-appb-100006
    Performing GG(2) accumulation acquisition after cyclically shifting Z-2×β×h, 2×(1-β)×h, and (lcmA-2×β)×h, Z=α×2 j , Α∈{2 A}, β∈{2 lcmA}.
  8. 如权利要求6所述的装置，其特征在于，a＝C a×lcmA 1×h，b＝C b×lcmA 2×h，lcmA 1表示集合A 1包括的元素的最小公倍数，lcmA 2表示集合A 2包括的元素的最小公倍数，所述集合A 1和所述集合A2分别包括至少一个奇数，且所述集合A 1和所述集合A 2的交集为空集，Z＝α×2 j，α为2或集合A 1和集合A 2中的任一元素，C a和C b均为常数，所述C 0(x)是通过分别对
    Figure PCTCN2018120556-appb-100007
    进行循环右移Z-2*β*h、(C a×lcmA 1-2×β)×h以及(C b×lcmA 2-2×β)×h之后再进行GF(2)累和获取的，Z＝α×2 j，α∈{2 A 1 A 2}，β∈{0 C a×lcmA 1 C b×lcmA 2}。     The apparatus according to claim 6, wherein a = C a × lcmA 1 × h, b = C b × lcmA 2 × h, lcmA 1 represents a least common multiple of elements included in the set A 1 , and lcmA 2 represents a set A least common multiple of the elements included in A 2 , the set A 1 and the set A 2 respectively comprise at least one odd number, and the intersection of the set A 1 and the set A 2 is an empty set, Z=α×2 j , α is 2 or any of the set A 1 and the set A 2 , and both C a and C b are constants, and the C 0 (x) is passed separately
    Figure PCTCN2018120556-appb-100007
    Performing GF(2) accumulation acquisition after cyclically shifting Z-2*β*h, (C a ×lcmA 1 -2×β)×h, and (C b ×lcmA 2 -2×β)×h , Z = α × 2 j , α ∈ {2 A 1 A 2 }, β ∈ {0 C a × lcmA 1 C b × lcmA 2 }.
  9. 如权利要求8所述的装置，其特征在于，Q(x)符合以下条件中的至少一项：The apparatus of claim 8 wherein Q(x) meets at least one of the following conditions:
    a与b为奇数，且a与b互质；a and b are odd numbers, and a and b are relatively prime;
    c＝a-b为偶数且不为4或4的倍数；c=a-b is an even number and is not a multiple of 4 or 4;
    c与a、b均互质；c and a, b are mutually homogeneous;
    lcmA 1与lcmA 2互质。 lcmA 1 is relatively prime to lcmA 2 .
  10. 权利要求6-9中任一项所述的装置，其特征在于，
    Figure PCTCN2018120556-appb-100008
    The device of any of claims 6-9, wherein
    Figure PCTCN2018120556-appb-100008
  11. 一种通信装置，其特征在于，包括：A communication device, comprising:
    存储器，用于存储计算机指令；a memory for storing computer instructions;
    处理器，用于执行所述存储器中存储的计算机指令，当所述计算机指令被执行时，所述处理器用于执行如权利要求1-5中任一项所述的方法。A processor for executing computer instructions stored in the memory, the processor for performing the method of any of claims 1-5 when the computer instructions are executed.
  12. 一种可读存储介质，其特征在于，包括指令，当所述指令在通信装置上运行时，使得所述通信装置执行如权利要求1-5中任一项所述的方法。A readable storage medium, comprising instructions that, when executed on a communication device, cause the communication device to perform the method of any of claims 1-5.
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