CN111490797B - Encoding method, device and equipment - Google Patents

Abstract

Embodiments of the present application provide an encoding method, apparatus, and device. The method includes: acquiring N bits to be encoded, where the N bits to be encoded include K information bits and N-K fixed bits, where N is a positive integer , the K is a positive integer, and the K is less than or equal to the N; obtain the generator matrix of the N bits to be coded; according to the linear independence metric between the row vectors in the generator matrix, determine the position; encode the to-be-coded bit according to the position of the information bit. Improved reliability of encoding.

Description

Coding method, device and equipment

technical field

The present application relates to the field of communication technologies, and in particular, to an encoding method, apparatus, and device.

Background technique

In the field of communication technology, communication devices (such as terminal devices, base stations, etc.) can perform channel coding and decoding by means of polar codes (Polar codes).

In the prior art, a method based on sub-channel reliability is generally used to construct polar codes, and the construction methods based on sub-channel reliability include a Gaussian Approximation (GA) method, a Polarization Weight (Polarization Weight, PW) method, and the like. However, the above-mentioned way of constructing polar codes can make the performance of the serial cancellation (Successive Cancellation, SC) decoding optimal, but cannot make the serial cancellation list (Successive Cancellation List, SCL) decoding and the ordered statistical decoding (Ordered Statistical decoding) Statistics Decoding, OSD) decoding performance is the best, resulting in poor performance of the existing encoding methods.

SUMMARY OF THE INVENTION

The present application provides an encoding method, apparatus and device, which improve the reliability of encoding.

In a first aspect, an embodiment of the present application provides an encoding method, the method includes: obtaining N bits to be encoded, where the N bits to be encoded include K information bits and N-K fixed bits, N is a positive integer, and K is a positive Integer, K is less than or equal to N; obtain the generator matrix of N bits to be coded; determine the position of the information bit according to the linear independence measure between the row vectors in the generator matrix; according to the position of the information bit, encode the bit to be coded.

In the above process, the position of the information bit is determined according to the linear independence measure between the row vectors in the generator matrix, so that the possibility of linear independence between the row vectors in the generator matrix corresponding to the position of the information bit is high, thereby making The probability of SCL decoding error and the probability of OSD decoding error are small, thereby improving the reliability of encoding.

In one possible implementation, the linearly independent measure is the likelihood of being linearly independent.

In a possible implementation manner, the position of the information bit can be determined according to the linear independence metric between the row vectors in the generator matrix in the following feasible implementation manner: initialize a first position set, and the initialized first position set includes the generator matrix The row sequence number of the row vector with the largest row weight in the middle row; initialize the second position set, and the initialized second position set includes at least one row sequence number; according to the row vector corresponding to each row sequence number in the second position set in the generator matrix, and the generator matrix The linear independence metric between the row vectors corresponding to the row sequence numbers in the first position set in , determines the position of the information bit.

In the above process, the initialized first position set includes the row sequence number of the row vector with the largest row weight in the generator matrix, and the linear relationship between the row vectors corresponding to the row sequence numbers in the first position set in the second position set and the row sequence number in the first position set is sequentially calculated. The row number corresponding to the row vector with the greatest possibility of being irrelevant is moved to the first position set, so that the code weight of the row vector in the generator matrix corresponding to the row number in the first position set can be made larger, and the first position can be made larger. The possibility of linear independence between the row vectors in the generator matrix corresponding to the row numbers in the set is the largest, that is, the possibility of linear independence between the row vectors corresponding to the information bits in the generator matrix is the largest, so that the The SCL decoding error probability is small and the OSD decoding error probability is small, thereby improving the reliability of encoding.

In a possible implementation manner, the initialized second location set includes row numbers corresponding to the K+L sub-channels with the highest reliability; wherein, L is the number of reserved paths for serial cancellation list SCL decoding, and the number of reserved paths Maximum number of paths reserved for each decoding step in SCL decoding.

In the above process, since the second location set includes the row numbers corresponding to the K+L sub-channels with the highest reliability, and the row numbers in the first location set are selected in the initialized second location set, therefore, it is possible to The reliability of the sub-channels corresponding to the row sequence numbers in the first position set is made high, and the reliability of the sub-channels corresponding to the information bits is made high, so that the reliability of coding is high.

In a possible implementation manner, the K+L subchannels are the K+L subchannels with the highest reliability among the N subchannels.

In a possible implementation, the K+L sub-channels are the K+L sub-channels with the highest reliability among the N-X sub-channels, X is the number of row sequence numbers included in the initialized first position set, and the N-X sub-channels are Subchannels in the N subchannels other than the subchannels corresponding to the row numbers in the first location set. In this way, the row sequence numbers included in the initialized first position set and the initialized second position set may not be repeated, thereby avoiding unnecessary operations.

In a possible implementation manner, the generator matrix is a polar code matrix of bits to be coded, and the polar code matrix includes N rows and N columns; the initialized first position set includes the generator matrix whose row weight is greater than the first Hamming distance. The serial number of the row; wherein, the first Hamming distance is the maximum value of the minimum Hamming distances when the information bits and the fixed bits are arranged in different ways, and the information bits and the fixed bits are arranged in one way corresponding to a minimum Hamming distance, and the information The minimum Hamming distance when the bits and the fixed bits are arranged in one way is the minimum row weight of the row corresponding to the information bits in the generated matrix when the information bits and the fixed bits are arranged in this way.

In the above process, the row weight of the row corresponding to the row sequence number included in the initialized first position set can be made larger, thereby making the encoding performance higher.

In a possible implementation manner, the initialized second position set includes the serial number of the row in the generator matrix whose row weight is equal to the first Hamming distance. In this way, the row weight of the row corresponding to the row sequence number included in the initialized second position set can be made larger, so that the row weight of the row corresponding to the row sequence number selected in the first position set is also higher, thereby making the coding performance better. high.

In a possible implementation manner, the initialized second position set includes all row numbers in the generator matrix; or, the initialized second position set includes all row numbers in the generator matrix except for the row numbers in the initialized first position set line number.

In a possible implementation manner, according to the linear independence measure between the row vector corresponding to each row number in the second position set in the generator matrix and the row vector corresponding to the row number in the first position set in the generator matrix, Determine the location of information bits, including:

Perform a first operation, the first operation includes: according to the row vector corresponding to each row sequence number in the current second position set in the generator matrix, and the row vector corresponding to the row sequence number in the current first position set in the generator matrix. Irrelevant metric, the target row number is determined in the current second position set; in the current second position set, the target row number corresponds to the row vector in the generator matrix and the row vector corresponding to the row number in the current first position set in the generator matrix The linearly independent measure between is the largest;

Performing a second operation, the second operation includes: adding the target row sequence number to the current first position set to obtain a new first position set, and deleting the target row sequence number in the current second position set to obtain a new second position set ;

The first operation and the second operation are repeatedly performed until the new first position set includes K row numbers, and the row number in the current first position set is determined as the position of the information bit.

In the above process, it can be ensured that the row sequence number with the largest linear independence metric of the row vector corresponding to the row sequence number in the first position set in the second position set is added to the first position set, so that the row sequence number in the first position set is The linear independence measure of the corresponding row vector is the largest, which makes the coding reliability higher.

In a possible implementation manner, adding the target row sequence number to the current first position set, and deleting the target row sequence number from the current second position set, includes: when Y is greater than Z, determining among the Y target row sequence numbers Z target row numbers, Y is the number of target row numbers, Z=K-T, T is the number of row numbers included in the current first position set, Y is an integer greater than 1, Z is a positive value less than or equal to K Integer; add Z target row numbers to the current first position set, and delete Z target row numbers from the current second position set.

In the above process, the maximum number of row sequence numbers included in the first location set can be K, so as to prevent the number of row sequence numbers included in the first location set from being larger than K.

In a possible implementation manner, the Z target row numbers are the row numbers corresponding to the Z sub-channels with the highest reliability among the Y target row numbers; or, the Z target row numbers are the row numbers with the largest row number among the Y target row numbers. Z line numbers; or, the Z target line numbers are the Z line numbers with the smallest line numbers among the Y target line numbers.

In a possible implementation, the information bits include cyclic redundancy check CRC bits and/or parity check PC bits.

In a second aspect, an embodiment of the present application provides an encoding device, including:

The first acquisition module is used to acquire N bits to be encoded, the N bits to be encoded include K information bits and N-K fixed bits, N is a positive integer, the K is a positive integer, and the K is less than or is equal to said N;

A second acquisition module, configured to acquire the generator matrix of the N bits to be encoded;

a determining module, configured to determine the position of the information bit according to the linearly independent metric between the row vectors in the generator matrix;

An encoding module, configured to encode the bits to be encoded according to the positions of the information bits.

In a possible implementation, the linearly independent metric is the likelihood of being linearly independent.

In a possible implementation manner, the determining module is specifically used for:

Initializing the first position set, the initialized first position set includes the row sequence number of the row vector with the largest row weight in the generator matrix;

initializing a second location set, where the initialized second location set includes at least one row sequence number;

According to the linear independence measure between the row vector corresponding to each row number in the second position set in the generator matrix and the row vector corresponding to the row number in the first position set in the generator matrix, determine the location of the information bits.

In a possible implementation manner, the initialized second location set includes row sequence numbers corresponding to the K+L sub-channels with the highest reliability;

Wherein, the L is the number of reserved paths for serial cancellation list SCL decoding, and the reserved path number is the maximum number of paths reserved for each step of decoding in the SCL decoding.

In a possible implementation manner, the K+L subchannels are the K+L subchannels with the highest reliability among the N subchannels; or,

The K+L sub-channels are the K+L sub-channels with the highest reliability among the N-X sub-channels, the X is the number of row sequence numbers included in the initialized first position set, and the N-X sub-channels are all the sub-channels. Subchannels in the N subchannels except the subchannels corresponding to the row numbers in the first location set.

In a possible implementation manner, the generator matrix is a polar code matrix of the to-be-coded bits, and the polar code matrix includes N rows and N columns;

The initialized first position set includes the serial number of the row whose row weight is greater than the first Hamming distance in the generator matrix; wherein, the first Hamming distance is when the information bits and the fixed bits are arranged in different ways. The maximum value of the minimum Hamming distances of The distance is the minimum row weight of the row corresponding to the information bit in the generator matrix when the information bits and the fixed bits are arranged in this manner.

In a possible implementation manner, the initialized second position set includes a sequence number of a row in the generator matrix whose row weight is equal to the first Hamming distance.

In a possible implementation manner, the initialized second position set includes all row numbers in the generator matrix; or,

The initialized second set of positions includes row numbers in the generator matrix other than row numbers in the initialized first set of positions.

In a possible implementation manner, the determining module is used for:

Performing a first operation, the first operation includes: according to the row vector corresponding to each row sequence number in the current second position set in the generator matrix, and the row sequence number corresponding to the row sequence number in the current first position set in the generator matrix The linear independence measure between row vectors, the target row number is determined in the current second position set; in the current second position set, the target row number corresponds to the row vector in the generator matrix and the current row vector in the generator matrix. The linear independence metric between the row vectors corresponding to the row numbers in the first position set is the largest;

Performing a second operation, the second operation includes: adding the target row sequence number to the current first position set to obtain a new first position set, and deleting the target row sequence number in the current second position set to obtain a new set of second positions;

The first operation and the second operation are repeatedly performed until the new first position set includes K row numbers, and the row number in the current first position set is determined as the position of the information bit.

In a possible implementation manner, the determining module is used for:

When Y is greater than Z, Z target row numbers are determined among the Y target row numbers, where Y is the number of target row numbers, Z=K-T, and T is the current first position set The number of row numbers included in the Y, the Y is an integer greater than 1, and the Z is a positive integer less than or equal to the K;

The Z target row sequence numbers are added to the current first position set, and the Z target row sequence numbers are deleted from the current second position set.

In a possible implementation manner, the Z target row numbers are row numbers corresponding to the Z sub-channels with the highest reliability among the Y target row numbers; or,

The Z target row sequence numbers are the Z row sequence numbers with the largest row sequence numbers in the Y target row sequence numbers; or,

The Z target row sequence numbers are the Z row sequence numbers with the smallest row sequence numbers among the Y target row sequence numbers.

In a possible implementation, the information bits include cyclic redundancy check CRC bits and/or parity check PC bits.

In a third aspect, an embodiment of the present application provides an encoding apparatus, including: a memory, a processor, and a computer program, where the computer program is stored in the memory, and the processor runs the computer program to execute any of the methods described in the first aspect. one of the methods described.

In a fourth aspect, an embodiment of the present application provides a storage medium, wherein the storage medium includes a computer program, and the computer program is used to implement the method according to any one of the first aspect.

In the encoding method, device and device provided by the present application, N bits to be encoded are obtained first. The N bits to be encoded include K information bits and N-K fixed bits, where N is a positive integer, K is a positive integer, and K is less than or equal to N; obtain a generator matrix of N bits to be encoded; determine the position of the information bit according to the linear independence measure between row vectors in the generator matrix; encode the bit to be encoded according to the position of the information bit. In the above process, the position of the information bit is determined according to the linear independence measure between the row vectors in the generator matrix, so that the possibility of linear independence between the row vectors in the generator matrix corresponding to the position of the information bit is high, thereby making The probability of SCL decoding error and the probability of OSD decoding error are small, thereby improving the reliability of encoding.

Description of drawings

FIG. 1 is an architectural diagram of a communication system provided by an embodiment of the present application;

2 is a flow chart of channel transmission provided by an embodiment of the present application;

Fig. 3 is the schematic flowchart of the encoding method provided by the application;

4 is a schematic flowchart of determining the position of an information bit provided by the present application;

Fig. 5 is a kind of simulation schematic diagram that this application provides;

Fig. 6 is a kind of simulation schematic diagram that this application provides;

Fig. 7 is a kind of simulation schematic diagram that this application provides;

8 is a schematic structural diagram of an encoding device provided by an embodiment of the present application;

FIG. 9 is a schematic diagram of a hardware structure of an encoding apparatus provided by an embodiment of the present application.

Detailed ways

The embodiments of the present application can be applied to various fields using Polar coding, for example, the field of data storage, the field of optical network communication, the field of wireless communication, and the like. The wireless communication systems mentioned in the embodiments of this application include, but are not limited to: Narrow Band-Internet of Things (NB-IoT), Global System for Mobile Communications (GSM), enhanced data Rate GSM Evolution (Enhanced Datarate for GSM Evolution, EDGE), Wideband Code Division Multiple Access (WCDMA), Code Division Multiple Access (Code Division Multiple Access, CDMA2000), Time Division Synchronous Code Division Multiple Access System (Time Division-Synchronization Code Division Multiple Access, TD-SCDMA), Long Term Evolution (Long Term Evolution, LTE) and three major application scenarios of the next generation 5G mobile communication system Enhanced Mobile Broad Band (eMBB) , Ultra Reliable Low Latency Communication (URLLC) and Massive Machine-Type Communications (mMTC). Of course, other fields may be used for Polar coding, which is not specifically limited in this application.

The communication device involved in this application mainly includes network equipment or terminal equipment. The sending device in this application may be a network device, and the receiving device is a terminal device. The sending device in this application is a terminal device, and the receiving device is a network device.

In the embodiments of the present application, terminal devices (terminal devices) include, but are not limited to, a mobile station (MobileStation, MS), a mobile terminal (Mobile Terminal, MT), a mobile phone (Mobile Telephone, MT), a mobile phone (handset), and a portable device (portable equipment), etc., the terminal equipment can communicate with one or more core networks via a radio access network (Radio Access Network, RAN). For example, the terminal device may be a mobile phone (or "cellular" phone), a computer with wireless communication function, etc. The terminal device may also be a portable, pocket-sized, hand-held, computer-built or vehicle-mounted mobile device or device.

In this embodiment of the present application, the network device may be an evolved base station (Evolutional NodeB, eNB or eNodeB) in an LTE system, or the network device may be a gNB or a transmission reception point (TRP) in a 5G communication system ), micro base station, etc., or the network equipment can be a relay station, an access point, a vehicle-mounted device, a wearable device, and a network device in the public land mobile network (Public Land Mobile Network, PLMN) evolved in the future, or in a variety of other technologies In a converged network, or a base station in other various evolved networks, etc.

For example, the network equipment may be a base station (Base Station, BS), the base station may provide communication services to multiple mobile stations (MobileStation, MS), and the base station may also be connected to core network equipment. The base station includes a baseband unit (Baseband Unit, BBU) and a remote radio unit (English: Remote Radio Unit, RRU). The BBU and RRU can be placed in different places, for example, the RRU is far away and placed in an area with high traffic volume, and the BBU is placed in the central computer room. BBU and RRU can also be placed in the same computer room. The BBU and RRU can also be different components under one rack.

FIG. 1 is an architectural diagram of a communication system provided by an embodiment of the present application. Please refer to FIG. 1 , including a sending device 101 and a receiving device 102 .

Optionally, when the sending device 101 is a terminal device, the receiving device 102 is a network device. When the sending device 101 is a network device, the receiving device is a terminal device.

Referring to FIG. 1 , the sending device 101 includes an encoder, and the sending device 101 can perform encoding through the encoder, and transmit the encoded sequence to the receiving device 102 through a channel. The receiving device 102 includes a decoder, and the receiving device can decode the received sequence through the decoder.

It should be noted that, FIG. 1 merely illustrates an architecture diagram of a communication system in the form of an example, and is not intended to limit the architecture diagram of the communication system.

FIG. 2 is a flow chart of channel transmission provided by an embodiment of the present application. Referring to FIG. 2 , the sending device performs source coding and channel coding on the data to be sent, and the coded sequence is transmitted to the receiving device on the channel after mapping and modulation. The receiving device can perform demapping and demodulation processing, channel decoding processing, and source decoding processing on the received sequence to recover the data sent by the sending device.

Since the current encoding method cannot optimize the performance of SCL decoding and OSD decoding, this application proposes an encoding method, which can improve the performance of SCL decoding and OSD decoding. In order to facilitate the understanding of the present application, the OSD decoding method, the OSD decoding error probability, the SCL decoding method and the SCL decoding error probability are first described.

The OSD decoding process may include the following steps:

Step 1: Acquire the received sequence, sort the received sequence in descending order according to the reliability of the hard judgment value of each bit to be decoded in the received sequence, obtain the first sequence y ₁ , and determine the first conversion from the received sequence to the first sequence Operation matrix (or transformation operation vector) λ ₁ .

Optionally, the received sequence may be a set of log-likelihood ratios (Likelihood Rate, LLR), and one bit to be decoded may be one LLR.

Optionally, the hard decision value of the bit to be decoded is 0 or 1. For example, if the bit to be decoded (LLR) is greater than 0, the hard decision value of the bit to be decoded may be 0; if the bit to be decoded (LLR) is less than 0, the hard decision value of the bit to be decoded is 1.

Optionally, the reliability of the hard decision value of the bit to be decoded may be the absolute value of the bit to be decoded (LLR).

即，

第一转换操作矩阵还可以为(4,1,2,3)，通过该第一转换操作矩阵中的元素指示对接收序列中的排序方式，由上述第一转换操作矩阵可知，将接收序列中的第4个元素排到了第1位，将接收序列中的第1个元素排到了第2位，将接收序列中的第2个元素排到了第3位，将接收序列中的第2个元素排到了第4位。For example, assuming that the received sequence is L1 (LLR1, LLR2, LLR3, LLR4) and the first sequence is L2 (LLR4, LLR1, LLR2, LLR3), the first conversion operation matrix can be:

which is,

The first conversion operation matrix can also be (4, 1, 2, 3). The elements in the first conversion operation matrix indicate the sorting method in the received sequence. It can be known from the above-mentioned first conversion operation matrix that the received sequence is sorted. The fourth element of the received sequence is ranked first, the first element in the received sequence is ranked second, the second element in the received sequence is ranked third, and the second element in the received sequence is ranked ranked 4th.

Step 2: Perform column conversion on the generator matrix corresponding to the received sequence according to the first conversion operation matrix to obtain a first matrix G1.

In OSD decoding, the number of rows included in the generator matrix is the same as the number of information bits, and the rows corresponding to the positions of the row information bits in the generator matrix are generated.

For example, assuming that the bits to be encoded include K information bits and N-K fixed bits, the generator matrix in OSD decoding includes the rows corresponding to the positions of the information bits in the N*N matrix (including N rows and N columns), That is, the generator matrix in OSD decoding is a K*N matrix (including K rows and N columns).

假设第一转换操作矩阵为(4,1,2,3)，则将生成矩阵的第4列调换到第1列，将第1列调换到第2列，将第2列调换到第3列，将第3列调换到第4列，得到的第一矩阵为

For example, assuming that the bits to be encoded include 2 information bits and 2 frozen bits, the generating matrix is

Assuming that the first transformation operation matrix is (4,1,2,3), then the 4th column of the generator matrix is transposed to the 1st column, the 1st column is transposed to the 2nd column, and the 2nd column is transposed to the 3rd column , swap the 3rd column to the 4th column, and the resulting first matrix is

Step 3. Perform Gaussian elimination on the first matrix G1 from left to right, wherein the mutually independent columns will be pre-generated to generate a new second matrix G2, and determine the second matrix G2 from the first matrix G1 to the second matrix G2. The transformation operation matrix (or transformation operation vector) λ ₂ .

Through this step, since the first K columns of the first matrix G1 are not necessarily mutually independent (irrelevant), the second matrix G2 is obtained after fine-tuning the column order of the first matrix G1 through the second transformation operation matrix λ ₂ . The top K columns of G2 are independent of each other (uncorrelated).

It should be noted that the process of determining the second conversion operation matrix may participate in the process of determining the first conversion operation matrix, which will not be repeated here.

Step 4: Perform a conversion operation on the first sequence y ₁ through the second conversion operation matrix λ ₂ to obtain a converted second sequence y ₂ .

For example, y ₂ =λ ₂ *y ₁ .

Step 5: For a given 0≤l≤K, invert all bit hard decisions of the second sequence y ₂ at positions less than or equal to 1 in K.

Step 6: For each error mode, re-encode the K bits based on the second matrix G2, and calculate the corresponding decoding metric.

Step 7: Select the codeword with the best decoding metric among all error modes and determine it as the decoding result.

Based on the above OSD decoding, the following describes the OSD decoding error probability.

满足公式一所示的关系：In the above OSD decoding, the OSD decoding error probability includes the Maximum Likelihood (ML) decoding error probability and the first-order decoding error probability, and the OSD decoding error probability

Satisfy the relationship shown in Equation 1:

为ML译码错误概率，P_e(I)为I阶译码错误概率。in,

is the ML decoding error probability, and P _e (I) is the I-order decoding error probability.

可以如公式二所示：The ML decoding error probability is related to the weight spectrum of the codeword, where the weight spectrum is related to the probability of being linearly independent between the row vectors used to transmit information bits in the generator matrix, e.g. The greater the likelihood of linear independence between row vectors, the better the weight spectrum,

It can be shown as formula 2:

为与码字x₁间的汉明距离为d_h的码字的个数，f(d_h)为将码字x₁错译码成与码字x₁的汉明距离为d_h的其它码字的概率。码字x₁与码字x₂之间汉明距离越大，将码字x₁错译码成码字x₂的概率越小，即d_h越大，f(d_h)越小。Polar码的一个特性为，码字的最小汉明距离等于生成矩阵中信息位对应行的最小行重，行重为一行中包括的非0元素的个数。由此可知，码字的重量谱越好，码字的最小码重越大、具有较低码重的码字越少，可以使得ML译码性能最优(ML译码错误概率最小)。Among them, P(x ₁ →x ₂ ) is the probability of wrongly decoding the codeword x ₁ into the code word x ₂ , d _h is the Hamming distance between the code words,

is the number _of codewords whose Hamming distance from the codeword x1 is dh, and _f (dh ₎ is the _{misdecoding of} the codeword x1 into other codewords whose Hamming distance is _dh from the codeword x1 Probability of codewords. _The larger the Hamming distance between the codeword x1 and the codeword _x2 , the smaller the probability _of incorrectly decoding the codeword x1 into the codeword _x2 , that is, the larger the d _h , the smaller the f(d _h ). One characteristic of the Polar code is that the minimum Hamming distance of the codeword is equal to the minimum row weight of the row corresponding to the information bit in the generator matrix, and the row weight is the number of non-zero elements included in a row. It can be seen that the better the weight spectrum of the codeword, the greater the minimum code weight of the codeword, and the fewer codewords with lower code weights, which can make the ML decoding performance optimal (ML decoding error probability is the smallest).

The first-order decoding error probability is related to the distribution of d, where d is the number of linearly correlated columns before the Kth linearly independent column is obtained, that is, the number of additional columns required to form K uncorrelated columns. For example, assuming that the K-1 column is linearly independent and the K-th column is linearly related to the first K-1 column, it is necessary to exchange the K-th column with the K+3-th column to make the first K columns linearly independent, then d is 3.

It can be seen from the above OSD decoding process that the OSD decoding is decoded according to the K elements that are not related. However, in the actual application process, it cannot be guaranteed that the first K columns are linearly independent. Therefore, when estimating P _e (I ), the error conditions at the first K+d positions need to be considered, and P _e (I) satisfies the relationship shown in the following formula 3:

表示为了得到K个线性不相关的列，需要额外考虑的列的最大个数，

为该码字的最小汉明距离，P₁为前K+d个元素中存在大于I个错误的概率。显然，当可靠度最高的比特(Most Reliable Bits，MRB)的可靠性越高，出现错误的可能性越低，即，前K+d个元素中出现多于I个错误的概率P₁随着d的增大而增加，因此，在d越小时令P(d)越大，从而得到较小的P_e(I)。where P(d) is the distribution of d,

Indicates the maximum number of additional columns that need to be considered in order to obtain K linearly uncorrelated columns,

is the minimum Hamming distance of the codeword, and P ₁ is the probability that there are more than 1 errors in the first K+d elements. Obviously, when the reliability of the most reliable bit (Most Reliable Bits, MRB) is higher, the probability of error occurrence is lower, that is, the probability of occurrence of more than 1 error in the first K+d elements P ₁ As d increases, P(d) is made larger when d is smaller, so as to obtain smaller P _e (I).

P(d) is consistent with the distribution of the weight spectrum, ie, the better the weight spectrum, the greater the P(d) when d is smaller. P(d) usually satisfies the characteristics shown in Equation 4 below:

且

表示在码字中任取K位为全0的码字平均数目，N(d_x)表示汉明重量为d_x的码字数量，可以看出，d_x越小，N(d_x)前的系数越大，因此

的大小主要由重量小的码字数量决定，重量小的码字数量越少，

越小，而p越大d的分布越靠左(更优)。由上可知，因此I阶译码性能最优(I阶译码错误最小)和ML译码性能最优(ML译码性能最小)是一致的。in,

and

Represents the average number of code words with K bits as all 0s in the code word, N(d _x ) represents the number of code words whose Hamming weight is d _x , it can be seen that the smaller d _{x is} , the more The larger the coefficient is, so

The size of the code is mainly determined by the number of code words with a small weight, and the smaller the number of code words with a small weight,

The smaller the value, and the larger p is, the more the distribution of d is to the left (better). From the above, it can be seen that the optimal performance of the I-order decoding (the smallest decoding error of the I-order) and the optimal ML decoding performance (the smallest ML decoding performance) are consistent.

The greater the possibility of linear independence of any K columns in the generator matrix, the better the distribution of d. Since the linear independence between the rows in the generator matrix is positively correlated with the linear independence of any K columns, therefore, try to select the position corresponding to the linearly independent rows in the generator matrix as the information bits, which can make the linear independence of any K columns selected. The possibility of irrelevance is the largest, so that the OSD decoding performance is optimal (the OSD decoding error probability is the smallest).

The SCL decoding process may include the following steps:

Step 1: Obtain a received sequence, where the received sequence includes a plurality of bits to be decoded.

Optionally, the received sequence may be a group of LLRs, and one bit to be decoded is one LLR.

Step 2: Divide the bits to be decoded in the received sequence into P groups of bits to be decoded.

For example, assuming that the received sequence includes 2 ^a bits to be decoded, each group of bits to be decoded includes m bits, 2 ^a =P×m, P is a positive integer greater than 1, and m is a positive integer greater than or equal to 1 .

Step 3: Perform P-step decoding with P groups of bits to be decoded as decoding objects, until a decoding result is obtained.

Wherein, for any i-th step of decoding, the m+1-level LLR of each to-be-decoded information bit in the i-th group of to-be-decoded bits can be calculated according to the received sequence (a group of LLRs). According to the m+1-level LLR of each information bit in the i-th group of bits to be decoded, the path metrics of all possible decoding paths decoded in the i-th step are calculated in parallel. According to the path metrics of all possible decoding paths, at least one reserved decoding path is selected.

Based on the above-mentioned SCL decoding, the following describes the SCL decoding error probability.

In the above SCL decoding process, SCL decoding errors include two types of errors. The first type of error is path selection error, that is, there is no correct decoding path in the selected at least one reserved decoding path; the second type of error is ML errors, ie, Path Metric (PM) values for correctly decoded paths are not minimal. The first type of error is mainly related to the reliability of the information bit sub-channel. The higher the reliability of the information bit sub-channel, the lower the probability of wrong path selection. The second type of error is related to the weight spectrum of the codeword. The better the weight spectrum of the codeword, the lower the probability of ML errors.

It can be seen from the above that the higher the reliability of the subchannel corresponding to the information bit, and the better the weight spectrum (the greater the possibility of linear independence between the row vectors used to transmit the information bit in the generator matrix), the SCL decoding can be made. The lower the probability of error.

Hereinafter, the technical solutions shown in the present application will be described in detail through specific embodiments. It should be noted that the following embodiments may be combined with each other, and the same or similar content will not be repeated in different embodiments.

FIG. 3 is a schematic flowchart of the encoding method provided by the present application. Referring to Figure 3, the method can include:

S301. Obtain N bits to be encoded.

The N bits to be encoded include K information bits and N-K fixed bits, N is a positive integer, K is a positive integer, and K is less than or equal to N.

Optionally, the information bits are bits used to carry information.

Optionally, the information bits may include cyclic redundancy check (Cyclic Redundancy Check, CRC) bits and/or parity check (Parity Check, PC) bits.

Optionally, the fixed bits may also be referred to as padding bits, frozen bits, or the like. Fixed bits can be 0.

Optionally, N can be a positive integer power of 2.

S302. Obtain a generator matrix of N bits to be encoded.

Optionally, the generator matrix may be an N*N matrix, that is, the generator matrix includes N rows and N columns.

为n次克罗内克(Kronecker)幂，即，生成矩阵可以为n个矩阵F连续做克罗内克积，n＝log₂N。For example, the generator matrix can be

It is a Kronecker power of n times, that is, the generator matrix can be continuously Kronecker product for n matrices F, n=log ₂ N.

For example, when N is equal to 4, the generator matrix can be:

When N is equal to 8, the generator matrix can be:

S303. Determine the position of the information bit according to the linear independence metric between the row vectors in the generator matrix.

Optionally, the linearly independent metric may be linearly independent likelihood, or the linearly independent metric may also be referred to as linearly independent, or the linearly independent metric may also be referred to as independent likelihood.

Optionally, the positions of the information bits are K.

Optionally, the position of the information bit may be the row sequence number of the row vector with a higher possibility (eg, the largest) of linear independence in the generator matrix.

It should be noted that, in this application, a row vector may also be referred to as a row, a row sequence number of a row vector may also be referred to as a row sequence number of a row, and a row weight of a row vector may also be referred to as a row weight of a row.

For example, assuming that N is 8 and K is 4, and assuming that the linear independence metric between the 1st, 2nd, 5th, and 8th rows in the generator matrix is the largest, the position of the information bit can be determined to be {1, 2, 5, 8}.

Optionally, for a row vector x of length N, the linear independence measure of the row vector x and the previous K ₁ row vectors can be as shown in formula 5:

Among them, i is the column number of the column where the element 1 in the vector x is located. For example, if the element in the 1st, 3rd, 4th, and 5th columns of the vector x is 1, then i takes 1, 3, 4, and 5 in turn. q _i is the proportion of 1s included in the i-th column of the matrix formed by the first K ₁ rows and the dimension is K ₁ ×N. For example, if the i-th column includes m 1s, then q _i =m/K ₁ .

S304: Encode the bits to be encoded according to the positions of the information bits.

Optionally, the information bits and the fixed bits may be sorted according to the positions of the information bits, and the sorted information bits and the fixed bits are encoded according to the generator matrix.

可以将序列

乘以生成矩阵、以及比特反序重排等处理，以实现对待编码比特进行编码。For example, suppose that N is 8, K is 4, the information bits are i ₁ , i ₂ , i ₃ and i ₄ , the positions of the information bits are {4, 6, 7, 8}, and the fixed bits are 0. Therefore, according to the information Bit position After sorting the information bits and fixed bits, the sequence is obtained

sequence can be

Multiply by the generator matrix, and rearrange the bits in reverse order to realize the encoding of the to-be-coded bits.

The coding method provided by the present application determines the position of the information bits according to the linear independence metric between the row vectors in the generator matrix, so that the possibility of linear independence between the row vectors in the generator matrix corresponding to the position of the information bits is high, Further, the probability of SCL decoding error and the probability of OSD decoding error are smaller, thereby improving the reliability of encoding.

On the basis of any one of the foregoing embodiments, optionally, the position of the information bit may be determined through the following feasible implementation manners. Specifically, please refer to the embodiment shown in FIG. 4 .

FIG. 4 is a schematic flowchart of determining the position of an information bit according to the present application. Referring to Figure 4, the method can include:

S401. Initialize a first location set.

The initialized first position set includes the row sequence number of the row vector with the largest row weight in the generated matrix.

Optionally, the row weight of the row vector refers to the number of non-zero elements included in the row vector. For example, the row weight of a row vector in a generator matrix refers to the number of 1's included in the row vector.

The elements in the last row of the spanning matrix are usually all 1s, so the last row vector in the spanning matrix has the largest row weight.

Optionally, the initialized first location set may include at least the following two situations:

A possible situation:

The initialized first position set includes only the row number of the last row in the generator matrix.

In this possible situation, the number of row sequence numbers included in the initialized first location set is 1.

For example, assuming that the generator matrix includes 8 rows, only row number 8 is included in the first position set.

Optionally, when the decoding algorithm is the SCL decoding algorithm, the initialized first location set may be this possible situation.

Another possible situation:

When the generator matrix is a polar code matrix of bits to be encoded, and the polar code matrix includes N rows and N columns, the initialized first position set includes the serial numbers of the rows in the generator matrix whose row weight is greater than the first Hamming distance.

Among them, the first Hamming distance is the maximum value of the minimum Hamming distances when the information bits and the fixed bits are arranged in different ways, and the information bits and the fixed bits are arranged in one way corresponding to a minimum Hamming distance, and the information bits and the fixed bits are arranged in one way. The minimum Hamming distance when arranged in one manner is the minimum row weight of the row corresponding to the information bits in the generation matrix when the information bits and the fixed bits are arranged in this manner.

In this possible situation, the number of row sequence numbers included in the initialized first location set is one or more.

Optionally, the minimum Hamming distance when the information bits and the fixed bits are arranged in one way can be determined in the following manner: when the information bits and the fixed bits are arranged in one way, the information bits (information bits) can be determined according to the arrangement. bit position), and the minimum row weight of the row corresponding to the information bit in the generator matrix is determined as the minimum Hamming distance in this arrangement.

For example, assuming the information bits are i ₁ , I ₂ , I ₃ and i ₄ , the information bits and the fixed bit (0) are arranged as follows: (0,0,0, _i1,0 , _i2 , _i3 ,i ₄ ), it can be determined that the information bits (positions of the information bits) are 4, 6, 7, and 8, and the information bits correspond to the 4th, 6th, 7th, and 8th rows in the generator matrix. The row weight of the 4th row, the row weight of the 6th row, the row weight of the 7th row, and the row weight of the 8th row is determined as the minimum Hamming distance in this arrangement.

Optionally, the information bits and the fixed bits can be arranged in multiple ways, and one arrangement can correspond to a minimum Hamming distance, and the maximum value of the minimum Hamming distances corresponding to all the arrangements of the information bits and the fixed bits is determined. is the first Hamming distance.

For example, assuming that the information bits and the fixed bits can be arranged in Q ways, then Q minimum Hamming distances can be determined, and the maximum value among the Q minimum Hamming distances is determined as the first Hamming distance.

Optionally, when the decoding algorithm is the OSD decoding algorithm, the initialized first location set may be this possible situation.

It should be noted that the initialized first location set may be pre-configured.

S402. Initialize the second location set.

Wherein, the initialized second location set includes at least one row sequence number.

Optionally, the initialized second location set may include at least the following three situations:

A possible situation:

The initialized second position set includes the row numbers corresponding to the K+L sub-channels with the highest reliability; wherein, L is the number of reserved paths in the SCL decoding of the serial cancellation list, and the number of reserved paths is the decoding of each step in the SCL decoding. Maximum number of paths to keep.

Optionally, the K+L subchannels are the K+L subchannels with the highest reliability among the N subchannels.

Optionally, the K+L sub-channels are the K+L sub-channels with the highest reliability among the N-X sub-channels, X is the number of row sequence numbers included in the initialized first position set, and the N-X sub-channels are divided by the N sub-channels. Subchannels other than the subchannels corresponding to the row numbers in the first location set. which is. The row number in the initialized first position set is not included in the initialized second position set.

Optionally, L can be 4, 8, 16, etc. In the actual application process, the size of L can be set according to actual needs.

Optionally, the row sequence number corresponding to the subchannel may be an identifier of the subchannel. For example, assuming that the K+L subchannels with the highest reliability are the 1st, 4th, 6th, and 7th subchannels, the row numbers corresponding to the K+L subchannels with the highest reliability are 1, 4, 6, and 7.

Optionally, when the decoding algorithm is the SCL decoding algorithm, the initialized second location set may be this possible situation.

This possible initialized second location set is very suitable for short code scenarios (scenarios where N is small and/or K is small), therefore, a threshold NT of N (or a threshold of K can also be set, the principle is the same, (No more details), when less than or equal to NT, use the construction method as described in the above embodiment to determine the information bit position, when greater than or equal to NT, use the traditional method for selecting the information bit position according to the reliability principle or other existing principles , note that when N is equal to the threshold value NT, both methods can be used.

Another possible situation:

The initialized second position set includes the serial number of the row in the generator matrix whose row weight is equal to the first Hamming distance.

It should be noted that, for the first Hamming distance, reference may be made to S401, which will not be repeated here.

Optionally, when the decoding algorithm is the OSD decoding algorithm, the initialized second position set may be this possible situation.

Another possible situation:

The initialized second position set includes all row numbers in the generator matrix; or, the initialized second position set includes row numbers in the generator matrix except the row numbers in the initialized first position set.

It should be noted that the initialized second location set may be pre-configured.

S403. According to the possibility of linear independence between the row vector corresponding to each row sequence number in the current second position set in the generator matrix and the row vector corresponding to the row sequence number in the current first position set in the generator matrix, in the current first position set The sequence number of the target row is determined in the two-position set.

Wherein, in the current second position set, the possibility of linear independence between the row vector in the generator matrix corresponding to the target row number and the row vector corresponding to the row number in the current first position set in the generator matrix is the greatest.

It should be noted that, in this application, by executing S404, the row sequence numbers included in the first location set can be changed, and by executing S405, the row sequence numbers included in the second location set can be changed. That is, the first position set and the second position set in this application are constantly changing, the row sequence numbers included in the first position set at different times may be different, and the row sequence numbers included in the second position set at different times may be different. different.

The current first position set shown in this application refers to the first position set at the current moment, wherein, if S404 has not been executed, the current first position set is the initialized first position set, and if S404 has been executed, the current first position set The location set is the new first location set obtained after S404 is executed for the last time.

The current second position set shown in this application refers to the second position set at the current moment, wherein, if S405 has not been executed, the current second position set is the initialized second position set, and if S405 has been executed, the current second position set The location set is a new second location set obtained after the last execution of S405.

Optionally, the possibility of linear independence between the first row vector corresponding to a row number in the current second position set in the generator matrix and the second row vector corresponding to the row number in the current first position set in the generator matrix Can be: the sum of the likelihoods of linear independence between the first row vector and each of the second row vectors, or the average of the likelihoods of linear independence between the first row vector and all second row vectors.

It should be noted that the above formula 5 can be used to determine the row vector corresponding to each row number in the current second position set in the generator matrix and the row vector corresponding to the row number in the current first position set in the generator matrix. Linearly independent possibilities.

Optionally, for the row sequence numbers in the current second position set, the possibility of linear independence between the row vector corresponding to each row sequence number and the row vector corresponding to the row sequence number in the current first position set in the generator matrix may be calculated separately. and determine the row sequence number with the greatest possibility of being linearly independent between the row vectors corresponding to the row sequence numbers in the current first position set in the current second position set as the target row sequence number.

For example, assuming that the second set of positions includes row numbers 2, 3, and 4, and the first set of positions includes row numbers 1, 8, the linearity between row 2 and row 1 and row 8 in the generator matrix can be calculated. Irrelevant possibility (denoted as possibility 1), calculate the linearly independent possibility (denoted as possibility 2) between the 3rd row and the 1st row and the 8th row in the generator matrix, calculate the 4th row in the generator matrix The possibility that is independent of the linearity between the first row and the eighth row (denoted as possibility 3), if the value of possibility 2 is the largest among possibility 1, possibility 2 and possibility 3, the row Sequence number 3 is determined as the target row sequence number.

S404. Add the sequence number of the target row to the current first location set to obtain a new first location set.

Optionally, if the number of target row serial numbers is 1, the target row serial number can be directly added to the current first position set.

Optionally, if the number of target row serial numbers is greater than 1, the target row serial number is added to the current first position set according to the number of target row serial numbers and the number of row serial numbers included in the current first position set.

Optionally, it is assumed that the number of target row numbers is Y, the number of row numbers included in the current first position set is T, and K-T=Z; when Y is greater than Z, determine Z among the Y target row numbers. target row sequence numbers, and add the Z target row sequence numbers to the current first position set. Y is an integer greater than 1, and Z is a positive integer less than or equal to K. In this way, the first location set can include at most K row numbers, so as to avoid that the number of row numbers included in the first location is greater than K.

When Y is greater than Z, Z target row numbers can be selected from the Y target row numbers through a rule, and the rules may include but are not limited to any of the following rules: The Z target row numbers are the most reliable among the Y target row numbers. Line numbers corresponding to the Z sub-channels; or, the Z target line numbers are the Z line numbers with the largest line number among the Y target line numbers; or the Z target line numbers are the Z line numbers with the smallest line number among the Y target line numbers serial number.

Of course, in the actual application process, a rule for selecting Z target row serial numbers among the Y target row serial numbers may be set according to actual needs, which is not specifically limited in this application.

S405. Delete the sequence number of the target row in the current second position set to obtain a new second position set.

It should be noted that the sequence number of the target row added in the current first position set is the same as the sequence number of the target row deleted in the current second position set.

For example, if Z target row numbers are added to the current first location set, then Z target row numbers are deleted from the current second location set, and the Z target row numbers added to the current first location set are the same as those in the current first location set. The sequence numbers of the Z target rows deleted in the second position set are the same.

S406. Determine whether the number of row sequence numbers included in the new first location set is K.

If yes, execute S407.

If not, execute S403.

S407: Determine the row sequence number in the current first position set as the position of the information bit.

In the embodiment shown in FIG. 4 , the initialized first position set includes the row sequence number of the row vector with the largest row weight in the generator matrix, and the rows corresponding to the row sequence numbers in the first position set in the second position set are sequentially The row sequence number corresponding to the row vector with the greatest possibility of being linearly independent between vectors is moved to the first position set, so that the code weight of the row vector in the generator matrix corresponding to the row sequence number in the first position set can be made larger, And make the possibility of linear independence between the row vectors in the generator matrix corresponding to the row numbers in the first position set maximum, that is, make the possibility of linear independence between the row vectors corresponding to the information bits in the generator matrix maximum , thereby making the SCL decoding error probability smaller and the OSD decoding error probability smaller, thereby improving the reliability of encoding.

Next, the method shown in the embodiment of FIG. 4 will be described with specific examples.

Example 1, assuming that the decoding algorithm is the SCL decoding algorithm, N is 16, K is 4, and L is 4.

Initialize the first position set: It is determined that the initialized first position set includes the row number (16) of the last row of the generator matrix, that is, the initialized first position set is {16}.

Initialize the second location set: determine that the initialized second location set includes the row numbers corresponding to the K+L(8) sub-channels with the highest sub-channel reliability among the 16 channels, assuming that the initialized second location set is {1,3 ,4,5,8,9,12,15}.

Obtain the probability that each row in the 1, 3, 4, 5, 8, 9, 12, and 15 rows in the generator matrix is linearly independent of the 16th row, assuming that the 3rd row in the generator matrix is linearly independent from the 16th row. is most likely, then add row number 3 to the current first position set to obtain a new first position set, and delete row number 3 from the current second position set to obtain a new second position set. The new first position set is {16,3}, and the new second position set is {1,4,5,8,9,12,15}.

Obtain the probability that each of rows 1, 4, 5, 8, 9, 12, and 15 in the generator matrix is linearly independent of rows 16 and 3, assuming that rows 9 and 16 and 3 in the generator matrix are The possibility of linear independence is the greatest, then the row number 9 is added to the current first position set to obtain a new first position set, and the row number 9 is deleted from the second position set to obtain a new second position set. The new set of first positions is {16,3,9}, and the new set of second positions is {1,4,5,8,12,15}.

The above process is repeated until the current first location set includes K=4 row numbers. Assuming that the current first position set is {16, 3, 9, 8}, the positions of the information bits are determined to be 3, 8, 9, and 16.

Example 2, it is assumed that the decoding algorithm is an OSD decoding algorithm, N is 16, and K is 8.

First, the first Hamming distance is calculated. For the calculation process of the first Hamming distance, reference may be made to S401, which will not be repeated here.

Initializing the first position set: It is determined that the initialized first position set includes the row number of the row whose row weight is greater than the first Hamming distance. Suppose the initial set of first positions is {2, 3, 8, 10, 16}.

Initialize the second position set: determine the row number of the row whose row weight is equal to the first Hamming distance in the initialized second position set. Assume that the initialized second position set is {4, 7, 9, 13, 15}.

Obtain the probability that each row in the 4th, 7th, 9th, 13th, and 15th rows in the generator matrix is linearly independent of all rows (2, 3, 8, 10, 16) in the first position set, assuming that the th row in the generator matrix is 7 rows are most likely to be linearly independent of all rows (2, 3, 8, 10, 16) in the first position set, then add row number 7 to the current first position set to obtain a new first position set, Delete row number 7 in the current second position set to obtain a new second position set. The new first position set is {2, 3, 8, 10, 16, 7}, and the new second position set is {4, 9, 13, 15}.

The above process is repeated until the current first location set includes K=8 row numbers. Assuming that the current first position set is {2, 3, 8, 10, 16, 7, 4, 9}, the positions of the information bits are determined to be 2, 3, 4, 7, 8, 9, 10, 16.

On the basis of any one of the above embodiments, the decoding efficiency based on the encoding method shown in the present application will be described below with reference to the simulation data shown in FIG. 5 to FIG. 6 .

When the simulation parameters corresponding to the coding of the present application and the simulation parameters corresponding to the existing coding are shown in Table 1, the simulation results using the coding method shown in the present application and the existing coding method may be as shown in FIG. 5 .

Table 1

/ The simulation parameters corresponding to the coding in this application Simulation parameters corresponding to existing codes channel AWGN AWGN Modulation BPSK BPSK Construction method New Code GA concatenated code NO CRC NO CRC Decoding algorithm SCL(L=8) SCL(L=8) Information bit length K 64 64 Codeword length N 128 128

Please refer to Table 1. Among the simulation parameters corresponding to the coding of the present application and the existing coding, the channels are all additive white Gaussian Noise (AWGN) channels, and the modulation methods are all binary phase shift keying (Binary Phase Shift Keying, BPSK), the codeword construction method of the present application becomes the New Code method, and the existing codeword construction method is Gaussian Approximation (GA), does not use CRC code, and the decoding algorithm is the SCL decoding algorithm (reserved decoding). The code paths L are all 8), the information bit lengths K are all 64, and the codeword lengths N are all 128.

FIG. 5 is a schematic diagram of a simulation provided by the present application. Referring to FIG. 5 , the horizontal axis represents a signal tonoise ratio (SNR), and the vertical axis represents a block error rate (Block Error Rate, BLER).

Referring to FIG. 5 , the dotted line represents the corresponding decoding block error rate when using the existing encoding method for encoding, and the solid line represents the corresponding decoding block error rate when using the encoding method of the present application for encoding. It can be seen from FIG. 5 that when CRC is not used, the coding method of the present application can significantly reduce the block error rate in the decoding process, so that the decoding performance is higher.

When the simulation parameters corresponding to the coding of the present application and the simulation parameters corresponding to the existing coding are shown in Table 2, the simulation results using the coding method shown in the present application and the existing coding method may be as shown in FIG. 6 .

Table 2

/ The simulation parameters corresponding to the coding in this application Simulation parameters corresponding to existing codes channel AWGN AWGN Modulation BPSK BPSK Construction method New Code GA concatenated code NO CRC CRC-4 Decoding algorithm SCL(L=8) SCL(L=8) Information bit length K 64 64 Codeword length N 128 128

Please refer to Table 2. In the simulation parameters corresponding to the coding of the present application and the existing coding, the channels are all AWGN channels, and the modulation methods are all BPSK. The codeword construction method of the present application is the New Code method, and the existing codeword construction method is GA, this application does not use CRC code, the existing code adopts 4 as CRC code, the decoding algorithm is SCL decoding algorithm (the reserved decoding path L is 8), the information bit length K is 64, and the code word length N is Both are 128.

FIG. 6 is a schematic diagram of simulation provided by the present application. Referring to Figure 6, the horizontal axis represents SNR and the vertical axis represents BLER.

Referring to FIG. 6 , the dotted line represents the corresponding decoding block error rate when using the existing encoding method for encoding, and the solid line represents the corresponding decoding block error rate when using the encoding method of the present application for encoding. It can be seen from FIG. 6 that when the present application does not use CRC, and the existing encoding adopts a 4-bit CRC code, the encoding method of the present application can significantly reduce the block error rate in the decoding process, so that the decoding performance is higher, and The complexity brought by the CRC check can be reduced.

When the simulation parameters corresponding to the coding of the present application and the simulation parameters corresponding to the existing coding are shown in Table 3, the simulation results of the coding methods shown in the present application and the existing coding methods can be as shown in FIG. 7 .

table 3

/ The simulation parameters corresponding to the coding in this application Simulation parameters corresponding to existing codes channel AWGN AWGN Modulation BPSK BPSK Construction method New Code GA concatenated code NO CRC NO CRC Decoding algorithm OSD-3 OSD-3 Information bit length K 32 32 Codeword length N 64 64

Please refer to Table 3. In the simulation parameters corresponding to the coding of the present application and the existing coding, the channels are all AWGN channels, and the modulation methods are all BPSK. The codeword construction method of the present application is the New Code method, and the existing codeword construction method is GA does not use CRC code, the decoding algorithm is OSD decoding algorithm, the information bit length K is 32, and the code word length N is 64.

FIG. 7 is a schematic diagram of a simulation provided by the present application. Referring to FIG. 7 , the horizontal axis represents the SNR, and the vertical axis represents the Block Error Rate (BLER).

Referring to FIG. 7 , the dotted line represents the corresponding decoding block error rate when using the existing encoding method for encoding, and the solid line represents the corresponding decoding block error rate when using the encoding method of the present application for encoding. It can be seen from FIG. 7 that, when CRC is not used, the coding method of the present application can significantly reduce the block error rate in the decoding process, so that the decoding performance is higher.

FIG. 8 is a schematic structural diagram of an encoding apparatus provided by an embodiment of the present application. Referring to FIG. 8, the encoding device 10 may include:

The first acquisition module 11 is used to acquire N bits to be encoded, the N bits to be encoded include K information bits and N-K fixed bits, N is a positive integer, the K is a positive integer, and the K is less than or equal to said N;

The second obtaining module 12 is used to obtain the generator matrix of the N bits to be encoded;

A determination module 13, configured to determine the position of the information bit according to the linearly independent metric between the row vectors in the generator matrix;

The encoding module 14 is configured to encode the bits to be encoded according to the positions of the information bits.

Optionally, the first obtaining module 11 may execute S301 in the embodiment of FIG. 3 .

Optionally, the second obtaining module 12 may execute S302 in the embodiment of FIG. 3 .

Optionally, the determining module 13 may execute S303 in the embodiment of FIG. 3 and the embodiment shown in FIG. 4 .

Optionally, the encoding module 14 may perform S304 in the embodiment of FIG. 3 .

Optionally, the encoding apparatus 10 may further include a sending module for sending the encoded information.

It should be noted that the encoding apparatus shown in the embodiments of the present application can implement the technical solutions shown in the foregoing method embodiments, and the implementation principles and beneficial effects thereof are similar, which will not be repeated here.

In a possible implementation, the linearly independent metric is the likelihood of being linearly independent.

In a possible implementation manner, the determining module 13 is specifically configured to:

Initializing the first position set, the initialized first position set includes the row sequence number of the row vector with the largest row weight in the generator matrix;

initializing a second location set, where the initialized second location set includes at least one row sequence number;

According to the linear independence measure between the row vector corresponding to each row number in the second position set in the generator matrix and the row vector corresponding to the row number in the first position set in the generator matrix, determine the location of the information bits.

In a possible implementation manner, the initialized second location set includes row sequence numbers corresponding to the K+L sub-channels with the highest reliability;

Wherein, the L is the number of reserved paths for serial cancellation list SCL decoding, and the reserved path number is the maximum number of paths reserved for each step of decoding in the SCL decoding.

In a possible implementation manner, the K+L subchannels are the K+L subchannels with the highest reliability among the N subchannels; or,

The K+L sub-channels are the K+L sub-channels with the highest reliability among the N-X sub-channels, the X is the number of row sequence numbers included in the initialized first position set, and the N-X sub-channels are all the sub-channels. Subchannels in the N subchannels except the subchannels corresponding to the row numbers in the first location set.

In a possible implementation manner, the generator matrix is a polar code matrix of the to-be-coded bits, and the polar code matrix includes N rows and N columns;

The initialized first position set includes the serial number of the row whose row weight is greater than the first Hamming distance in the generator matrix; wherein, the first Hamming distance is when the information bits and the fixed bits are arranged in different ways. The maximum value of the minimum Hamming distances of The distance is the minimum row weight of the row corresponding to the information bit in the generator matrix when the information bits and the fixed bits are arranged in this manner.

In a possible implementation manner, the initialized second position set includes a sequence number of a row in the generator matrix whose row weight is equal to the first Hamming distance.

In a possible implementation manner, the initialized second position set includes all row numbers in the generator matrix; or,

The initialized second set of positions includes row numbers in the generator matrix other than row numbers in the initialized first set of positions.

In a possible implementation manner, the determining module 13 is used for:

Performing a first operation, the first operation includes: according to the row vector corresponding to each row sequence number in the current second position set in the generator matrix, and the row sequence number corresponding to the row sequence number in the current first position set in the generator matrix The linear independence measure between row vectors, the target row number is determined in the current second position set; in the current second position set, the target row number corresponds to the row vector in the generator matrix and the current row vector in the generator matrix. The linear independence metric between the row vectors corresponding to the row numbers in the first position set is the largest;

Performing a second operation, the second operation includes: adding the target row sequence number to the current first position set to obtain a new first position set, and deleting the target row sequence number in the current second position set to obtain a new set of second positions;

The first operation and the second operation are repeatedly performed until the new first position set includes K row numbers, and the row number in the current first position set is determined as the position of the information bit.

In a possible implementation manner, the determining module 13 is used for:

When Y is greater than Z, Z target row numbers are determined among the Y target row numbers, where Y is the number of target row numbers, Z=K-T, and T is the current first position set The number of row numbers included in the Y, the Y is an integer greater than 1, and the Z is a positive integer less than or equal to the K;

The Z target row sequence numbers are added to the current first position set, and the Z target row sequence numbers are deleted from the current second position set.

In a possible implementation manner, the Z target row numbers are row numbers corresponding to the Z sub-channels with the highest reliability among the Y target row numbers; or,

The Z target row sequence numbers are the Z row sequence numbers with the largest row sequence numbers in the Y target row sequence numbers; or,

The Z target row sequence numbers are the Z row sequence numbers with the smallest row sequence numbers among the Y target row sequence numbers.

In a possible implementation, the information bits include cyclic redundancy check CRC bits and/or parity check PC bits.

FIG. 9 is a schematic diagram of a hardware structure of an encoding apparatus provided by an embodiment of the present application. Referring to FIG. 9, the encoding apparatus 20 may include: a processor 21 and a memory 22; wherein,

memory 22, for storing computer programs, and sometimes for storing intermediate data;

The processor 21 is configured to execute the computer program stored in the memory, so as to realize each step in the above encoding method. For details, refer to the relevant descriptions in the foregoing method embodiments.

Optionally, the memory 22 may be independent or integrated with the processor 21 . In some embodiments, the memory may even be located outside the device.

When the memory 22 is a device independent of the processor 21 , the receiving device 20 may further include a bus 23 for connecting the memory 22 and the processor 21 .

The encoding apparatus of FIG. 9 may further include a transmitter for transmitting the encoded information.

The encoding device provided in this embodiment may be a terminal device, or may also be a network device, and may be used to execute the foregoing encoding method. The implementation manner and technical effect thereof are similar, and details are not described herein again in this embodiment.

An embodiment of the present application further provides a storage medium, where the storage medium includes a computer program, and the computer program is used to implement the encoding method as described above.

Embodiments of the present application further provide a chip or integrated circuit, including: a memory and a processor;

The memory is used to store program instructions and sometimes intermediate data;

The processor is configured to invoke the program instructions stored in the memory to implement the encoding method described above.

Optionally, the memory can be independent or integrated with the processor. In some embodiments, the memory may also be located outside the chip or integrated circuit.

An embodiment of the present application further provides a program product, where the program product includes a computer program, and the computer program is stored in a storage medium, and the computer program is used to implement the above encoding method.

The steps of the method or algorithm described in conjunction with the disclosure of the embodiments of the present invention may be implemented in a hardware manner, or may be implemented in a manner in which a processor executes software instructions. Software instructions can be composed of corresponding software modules, and software modules can be stored in random access memory (Random Access Memory, RAM), flash memory, read only memory (Read Only Memory, ROM), erasable programmable read only memory ( Erasable Programmable ROM, EPROM), Electrically Erasable Programmable Read-Only Memory (Electrically EPROM, EEPROM), registers, hard disks, removable hard disks, compact disks (CD-ROMs) or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor, such that the processor can read information from, and write information to, the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and storage medium may reside in an ASIC. Alternatively, the ASIC may be located in the base station or in the terminal. Of course, the processor and storage medium may also exist in the receiving device as discrete components.

It should be understood that the above-mentioned processor may be a central processing unit (English: Central Processing Unit, referred to as: CPU), and may also be other general-purpose processors, digital signal processors (English: Digital Signal Processor, referred to as: DSP), application-specific integrated circuits (English: Application Specific Integrated Circuit, referred to as: ASIC) and so on. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in conjunction with the invention can be directly embodied as executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.

The memory may include high-speed RAM memory, and may also include non-volatile storage NVM, such as at least one magnetic disk memory, and may also be a U disk, a removable hard disk, a read-only memory, a magnetic disk or an optical disk, and the like.

The bus may be an Industry Standard Architecture (Industry Standard Architecture, ISA) bus, a Peripheral Component (Peripheral Component, PCI) bus, or an Extended Industry Standard Architecture (Extended Industry Standard Architecture, EISA) bus, or the like. The bus can be divided into address bus, data bus, control bus and so on. For convenience of representation, the buses in the drawings of the present application are not limited to only one bus or one type of bus.

The above-mentioned storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read only memory (EEPROM), erasable Except programmable read only memory (EPROM), programmable read only memory (PROM), read only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. A storage medium can be any available medium that can be accessed by a general purpose or special purpose computer.

In this application, "at least one" means one or more, and "plurality" means two or more. "And/or", which describes the relationship of the associated objects, indicates that there can be three kinds of relationships, for example, A and/or B, it can indicate that A exists alone, A and B exist at the same time, and B exists alone, where A, B can be singular or plural. The character "/" generally indicates that the associated objects are an "or" relationship. "At least one item(s) below" or similar expressions thereof refer to any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one item (a) of a, b, or c can represent: a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, c may be single or multiple .

Those skilled in the art should realize that, in one or more of the above examples, the functions described in the embodiments of the present invention may be implemented by hardware, software, firmware, or any combination thereof. When implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage medium can be any available medium that can be accessed by a general purpose or special purpose computer.

In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the device embodiments described above are only illustrative. For example, the division of the modules is only a logical function division. In actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated. to another system, or some features can be ignored, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or modules, and may be in electrical, mechanical or other forms.

The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, or each module may exist physically alone, or two or more modules may be integrated into one unit. The units formed by the above modules can be implemented in the form of hardware, or can be implemented in the form of hardware plus software functional units.

Claims (26)

1. A method of encoding, comprising:

acquiring N bits to be coded, wherein the N bits to be coded comprise K information bits and N-K fixed bits, N is a positive integer, K is a positive integer, and K is less than or equal to N;

acquiring a generating matrix of the N bits to be coded;

determining the position of the information bit according to the linear irrelevance measurement between the row vectors in the generating matrix;

and coding the bit to be coded according to the position of the information bit.

2. The method of claim 1, wherein the linearly independent metric is a linearly independent likelihood.

3. The method of claim 1 or 2, wherein determining the position of the information bit according to a linear independence metric between row vectors in the generator matrix comprises:

initializing a first position set, wherein the initialized first position set comprises a row sequence number of a row vector with the maximum row weight in the generating matrix;

initializing a second position set, wherein the initialized second position set comprises at least one row sequence number;

and determining the position of the information bit according to the linear independence measurement between the row vector corresponding to each row sequence number in the second position set in the generating matrix and the row vector corresponding to the row sequence number in the first position set in the generating matrix.

4. The method according to claim 3, wherein the initialized second location set comprises a row sequence number corresponding to the K + L subchannels with the highest reliability;

and L is the reserved path number of the serial cancellation list SCL decoding, and the reserved path number is the maximum path number reserved for each step of decoding in the SCL decoding.

5. The method of claim 4,

the K + L sub-channels are K + L sub-channels with the highest reliability in the N sub-channels; or,

the K + L sub-channels are K + L sub-channels with the highest reliability in N-X sub-channels, where X is the number of row sequence numbers included in the initialized first location set, and the N-X sub-channels are sub-channels of the N sub-channels except sub-channels corresponding to the row sequence numbers in the first location set.

6. The method of claim 3, wherein the generator matrix is a polar code matrix of the bits to be encoded, and the polar code matrix comprises N rows and N columns;

the initialized first position set comprises sequence numbers of rows with row weights larger than a first Hamming distance in the generator matrix; the first hamming distance is a maximum value of minimum hamming distances when the information bits and the fixed bits are arranged in different manners, the information bits and the fixed bits are arranged in a manner corresponding to one minimum hamming distance, the minimum hamming distance when the information bits and the fixed bits are arranged in a manner is a minimum line repetition of a line corresponding to an information bit in the generator matrix when the information bits and the fixed bits are arranged in the manner.

7. The method of claim 6, wherein the initialized second set of locations comprises sequence numbers of rows in the generator matrix with row weights equal to the first Hamming distance.

8. The method of claim 3,

the initialized second location set comprises all row sequence numbers in the generator matrix; or,

the initialized second set of locations comprises a row sequence number in the generator matrix except for a row sequence number in the initialized first set of locations.

9. The method according to any of claims 4-8, wherein said determining the position of the information bit according to a linear independence metric between the row vector corresponding to each row sequence number in the second set of positions in the generator matrix and the row vector corresponding to the row sequence number in the first set of positions in the generator matrix comprises:

performing a first operation, the first operation comprising: determining a target row sequence number in the current second position set according to a linear independence measure between a row vector corresponding to each row sequence number in the current second position set in the generated matrix and a row vector corresponding to a row sequence number in the current first position set in the generated matrix; in the current second position set, the linear independence metric between the row vector corresponding to the target row sequence number in the generating matrix and the row vector corresponding to the row sequence number in the current first position set in the generating matrix is the largest;

performing a second operation, the second operation comprising: adding the target row sequence number to the current first position set to obtain a new first position set, and deleting the target row sequence number in the current second position set to obtain a new second position set;

and repeatedly executing the first operation and the second operation until the new first position set comprises K row serial numbers, and determining the row serial number in the current first position set as the position of the information bit.

10. The method of claim 9, wherein adding the target row sequence number to a current first location set and deleting the target row sequence number from a current second location set comprises:

when Y is larger than Z, Z target row sequence numbers are determined in the Y target row sequence numbers, Y is the number of the target row sequence numbers, Z is K-T, T is the number of the row sequence numbers included in the current first position set, Y is an integer larger than 1, and Z is a positive integer smaller than or equal to K;

and adding the Z target row serial numbers to the current first position set, and deleting the Z target row serial numbers in the current second position set.

11. The method of claim 10,

the Z target row serial numbers are row serial numbers corresponding to Z sub-channels with highest reliability in the Y target row serial numbers; or,

the Z target row serial numbers are the Z row serial numbers with the largest row serial number in the Y target row serial numbers; or,

and the Z target row serial numbers are the Z row serial numbers with the minimum row serial number in the Y target row serial numbers.

12. The method according to any of claims 1-2, 4-8, 10-11, characterized in that the information bits comprise cyclic redundancy check, CRC, bits and/or parity check, PC, bits.

13. An encoding apparatus, comprising:

a first obtaining module, configured to obtain N bits to be encoded, where the N bits to be encoded include K information bits and N-K fixed bits, N is a positive integer, K is a positive integer, and K is less than or equal to N;

a second obtaining module, configured to obtain a generator matrix of the N bits to be encoded;

a determining module, configured to determine a position of the information bit according to a linear independence metric between row vectors in the generator matrix;

and the coding module is used for coding the bits to be coded according to the positions of the information bits.

14. The apparatus of claim 13, wherein the linearly independent metric is a linearly independent likelihood.

15. The apparatus according to claim 13 or 14, wherein the determining module is specifically configured to:

initializing a first position set, wherein the initialized first position set comprises a row sequence number of a row vector with the maximum row weight in the generating matrix;

initializing a second position set, wherein the initialized second position set comprises at least one row sequence number;

and determining the position of the information bit according to a linear independence measure between a row vector corresponding to each row sequence number in the second position set in the generated matrix and a row vector corresponding to a row sequence number in the first position set in the generated matrix.

16. The apparatus according to claim 15, wherein the initialized second location set includes a row sequence number corresponding to K + L subchannels with highest reliability;

and L is the reserved path number of the serial cancellation list SCL decoding, wherein the reserved path number is the maximum path number reserved in each step of decoding in the SCL decoding.

17. The apparatus of claim 16,

the K + L sub-channels are K + L sub-channels with the highest reliability in the N sub-channels; or,

the K + L sub-channels are K + L sub-channels with the highest reliability in N-X sub-channels, where X is the number of row sequence numbers included in the initialized first location set, and the N-X sub-channels are sub-channels of the N sub-channels except sub-channels corresponding to the row sequence numbers in the first location set.

18. The apparatus of claim 15, wherein the generator matrix is a polar code matrix of the bits to be encoded, and wherein the polar code matrix comprises N rows and N columns;

the initialized first position set comprises sequence numbers of rows with row weights larger than a first Hamming distance in the generator matrix; the first hamming distance is the maximum value of the minimum hamming distances when the information bits and the fixed bits are arranged in different ways, the information bits and the fixed bits are arranged in a way corresponding to one minimum hamming distance, the minimum hamming distance when the information bits and the fixed bits are arranged in a way is the minimum line weight of the lines corresponding to the information bits in the generating matrix when the information bits and the fixed bits are arranged in the way.

19. The apparatus of claim 18, wherein the initialized second set of locations comprises sequence numbers of rows in the generator matrix with row weights equal to the first hamming distance.

20. The apparatus of claim 15,

the initialized second location set comprises all row sequence numbers in the generator matrix; or,

the initialized second set of locations comprises a row sequence number in the generator matrix except for a row sequence number in the initialized first set of locations.

21. The apparatus according to any of claims 16-20, wherein the determining module is configured to:

performing a first operation, the first operation comprising: determining a target row sequence number in the current second position set according to a linear independence measure between a row vector corresponding to each row sequence number in the current second position set in the generated matrix and a row vector corresponding to a row sequence number in the current first position set in the generated matrix; in the current second position set, the linear independence metric between the row vector corresponding to the target row sequence number in the generating matrix and the row vector corresponding to the row sequence number in the current first position set in the generating matrix is the largest;

performing a second operation, the second operation comprising: adding the target row sequence number to the current first position set to obtain a new first position set, and deleting the target row sequence number in the current second position set to obtain a new second position set;

and repeatedly executing the first operation and the second operation until the new first position set comprises K line sequence numbers, and determining the line sequence number in the current first position set as the position of the information bit.

22. The apparatus of claim 21, wherein the determining module is configured to:

when Y is larger than Z, Z target row sequence numbers are determined in the Y target row sequence numbers, Y is the number of the target row sequence numbers, Z is K-T, T is the number of the row sequence numbers included in the current first position set, Y is an integer larger than 1, and Z is a positive integer smaller than or equal to K;

and adding the Z target row sequence numbers to the current first position set, and deleting the Z target row sequence numbers in the current second position set.

23. The apparatus of claim 22,

the Z target row serial numbers are row serial numbers corresponding to Z sub-channels with highest reliability in the Y target row serial numbers; or,

the Z target row serial numbers are the Z row serial numbers with the largest row serial number in the Y target row serial numbers; or,

and the Z target row serial numbers are the Z row serial numbers with the minimum row serial number in the Y target row serial numbers.

24. The apparatus according to any of claims 13-14, 16-20, 22-23, wherein the information bits comprise cyclic redundancy check, CRC, bits and/or parity check, PC, bits.

25. An encoding apparatus, comprising: memory, a processor and a computer program, the computer program being stored in the memory, the processor running the computer program to perform the method of any of claims 1 to 12.

26. A storage medium, characterized in that the storage medium comprises a computer program for implementing the method according to any one of claims 1 to 12.

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