Decoding path determination method, apparatus, computer equipment, and storage medium

Abstract

This application relates to a decoding path determination method, apparatus, computer device, and storage medium. The method includes: constructing a symbol-based equivalent directed graph based on a polar code generator matrix; obtaining at least two initial symbol synchronization sets based on the equivalent directed graph; optimizing each initial symbol synchronization set based on frozen symbols in each initial symbol synchronization set and information symbols in a preset set to obtain an optimized symbol synchronization set; and determining the target decoding path based on the optimized symbol synchronization set. This method optimizes the symbol enumeration order, improves path evaluation at each decoding level, and further optimizes the enumeration order of symbols in the optimized symbol synchronization set, resulting in a more accurate final target decoding path.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a decoding path determination method, apparatus, computer device, and storage medium. Background Technology

[0002] With the development of communication technology, signal detection and channel decoding have become important research directions in baseband signal processing. For example, at the transmitting end, the information bits are first channel-coded, and then the encoded signal is modulated into symbols. At the receiving end, the detector first estimates the symbols from the received signal, converts the estimated symbols into the log-likelihood ratio of the bits, and sends it as soft information to the decoder. The decoder then recovers the information bits through a decoding algorithm.

[0003] In 5G, the channel polarization method using polar codes is very common. For example, in a polar code-coded multiple-input multiple-output (MIMO) communication system, the commonly used detection and decoding method is the MIMO fusion detection and decoding algorithm, which is generally implemented using spherical decoding or the K-best algorithm. Through bit enumeration, the final output is the decoding path with the smallest Euclidean distance to the received information.

[0004] However, current MIMO fusion detection decoding algorithms suffer from low accuracy in the decoding path. Summary of the Invention

[0005] Therefore, it is necessary to provide a decoding path determination method, apparatus, computer equipment, and storage medium that can improve the decoding path accuracy in response to the above-mentioned technical problems.

[0006] Firstly, this application provides a method for determining a decoding path. The method includes:

[0007] Construct symbol-based equivalent directed graphs based on polar code generation matrices;

[0008] Based on the equivalence directed graph, obtain at least two initial symbol synchronization sets;

[0009] Based on the frozen symbols in each initial symbol synchronization set and the information symbols in the preset set, each initial symbol synchronization set is optimized to obtain the optimized symbol synchronization set.

[0010] The target decoding path is determined based on the optimized symbol synchronization set.

[0011] In one embodiment, at least two initial symbol synchronization sets are obtained based on the equivalence directed graph, including:

[0012] Based on the enumeration order of each symbol in the equivalent directed graph, the target edges of each information symbol are deleted, and the initial symbol synchronization set is determined according to the in-degree of the frozen symbols; the target edge is the edge that originates from the signal symbol.

[0013] In one embodiment, after deleting the target edges of each information symbol according to the enumeration order of the symbols in the equivalent directed graph, the initial symbol synchronization set is determined based on the in-degree of the frozen symbols, including:

[0014] Perform a classification operation; wherein, the classification operation includes: according to the enumeration order of each symbol in the equivalent directed graph, after deleting the target edge of the current information symbol, obtaining the in-degree of the target frozen symbol connected to the current information symbol after deleting the target edge; if the in-degree of the target frozen symbol is zero, then classify the current information symbol and the target frozen symbol into the same set.

[0015] According to the enumeration order, the next information symbol adjacent to the current information symbol is determined as the new current information symbol, and the classification operation is performed until all symbols are classified into the set, thus obtaining the initial symbol synchronization set.

[0016] In one embodiment, each initial symbol synchronization set is optimized based on the frozen symbols in each initial symbol synchronization set and the information symbols in a preset set to obtain an optimized symbol synchronization set, including:

[0017] Get the first sequence number of the frozen symbol in the current symbol synchronization set and the second sequence number of the information symbol in the preset set; the current symbol synchronization set is any one of at least two initial symbol synchronization sets;

[0018] Based on the first sequence number, the second sequence number, and the upper triangular matrix corresponding to the channel matrix, the current symbol synchronization set is optimized to obtain the optimized symbol synchronization set.

[0019] In one embodiment, the initial symbol synchronization sets are optimized based on the first sequence number, the second sequence number, and the upper triangular matrix corresponding to the channel matrix to obtain optimized symbol synchronization sets, including:

[0020] Determine the value of the target element from the upper triangular matrix, using the first index as the row and the second index as the column;

[0021] If the second sequence number is greater than the first sequence number, and the value of the target element is not zero, then the frozen symbol is removed from the current symbol synchronization set and added to the target symbol synchronization set; the third sequence number of the information symbol in the target symbol synchronization set is less than the first sequence number, and the values ​​of the elements in the upper triangular matrix corresponding to the first and third sequence numbers are not zero; or, the target symbol synchronization set is a preset set.

[0022] In one embodiment, determining the target decoding path based on the optimized symbol synchronization set includes:

[0023] Based on the enumeration order of each optimized symbol synchronization set, obtain the Euclidean distance of each information symbol in each optimized symbol synchronization set;

[0024] The target decoding path is determined based on the Euclidean distance between each information symbol in each optimized symbol synchronization set.

[0025] In one embodiment, the target decoding path is determined based on the Euclidean distance between each information symbol in each optimized symbol synchronization set, including:

[0026] Based on the Euclidean distance between each information symbol in each optimized symbol synchronization set, a preset number of candidate decoding paths are determined for each optimized symbol synchronization set.

[0027] The target decoding path is determined based on the candidate decoding paths corresponding to each optimized symbol synchronization set.

[0028] Secondly, this application also provides a decoding path determination apparatus, the apparatus comprising:

[0029] A building module is used to construct symbol-based equivalent directed graphs from polar code generation matrices;

[0030] The module obtains at least two initial symbol synchronization sets based on the equivalence directed graph.

[0031] The optimization module is used to optimize each initial symbol synchronization set based on the frozen symbols in each initial symbol synchronization set and the information symbols in the preset set, so as to obtain the optimized symbol synchronization set.

[0032] The determination module is used to determine the target decoding path based on the optimized symbol synchronization set.

[0033] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the decoding path determination method as described in any embodiment of the first aspect.

[0034] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the decoding path determination method as described in any embodiment of the first aspect.

[0035] The decoding path determination method, apparatus, computer device, and storage medium provided in this application construct an equivalent directed graph based on symbols according to the polar code generation matrix. Based on the equivalent directed graph, at least two initial symbol synchronization sets are obtained. Each initial symbol synchronization set is optimized based on frozen symbols in each set and information symbols in a preset set, resulting in an optimized symbol synchronization set. The target decoding path is then determined based on the optimized symbol synchronization set. In this application, symbols are categorized into sets based on the equivalent directed graph, and the decoding path is determined based on these sets. This optimizes the symbol enumeration order, making path evaluation at each decoding level more accurate. Furthermore, optimizing the initial symbol synchronization sets further optimizes the enumeration order of symbols in the optimized symbol synchronization sets, resulting in a more accurate final target decoding path. Attached Figure Description

[0036] Figure 1 This is an application environment diagram of the decoding path determination method in one embodiment;

[0037] Figure 2 This is a flowchart illustrating a decoding path determination method in one embodiment;

[0038] Figure 3 This is an equivalent directed graph based on bit synchronization nodes in one embodiment;

[0039] Figure 4 This is a flowchart illustrating the process of determining the initial symbol synchronization set in another embodiment;

[0040] Figure 5 This is a preliminary symbolic equivalent directed graph and an improved symbolic equivalent directed graph in one embodiment;

[0041] Figure 6 This is a flowchart illustrating the process of determining the optimized symbol synchronization set in one embodiment;

[0042] Figure 7 This is a flowchart illustrating the process of determining the optimized symbol synchronization set in one embodiment;

[0043] Figure 8 This is a flowchart illustrating the process of determining the target decoding path in another embodiment;

[0044] Figure 9 This is a flowchart illustrating the process of determining the target decoding path in another embodiment;

[0045] Figure 10 This is a flowchart illustrating the process of determining the target decoding path in one embodiment;

[0046] Figure 11 A comparison chart of FER performance obtained from tests in a simulation environment;

[0047] Figure 12 This is a block diagram of a decoding path determination device in one embodiment;

[0048] Figure 13 This is a block diagram of a decoding path determination device in one embodiment;

[0049] Figure 14 This is a block diagram of a decoding path determination device in one embodiment;

[0050] Figure 15 This is a block diagram of a decoding path determination device in one embodiment;

[0051] Figure 16 This is an internal structural diagram of a computer device in one embodiment;

[0052] Figure 17 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0054] With the development of communication technology and the increase in user demand, users have increasingly higher requirements for communication quality. MIMO communication systems use multiple antennas at the transmitting end to independently transmit signals, while multiple antennas at the receiving end receive and recover the original information, greatly improving channel capacity and reliability. However, due to the large number of antennas at the receiving end, signal detection and decoding become more difficult.

[0055] Signal detection and channel decoding are important research areas in baseband signal processing. At the transmitter, information bits are first channel-coded and modulated into symbols. At the receiver, detection and decoding are usually considered as two independent processing modules: the MIMO detector first estimates the symbols from the received signal, then converts them into the log-likelihood ratio of the bits as soft information and sends it to the decoder; the decoding algorithm finally recovers the information bits.

[0056] 5G employs polar codes for channel polarization as a crucial approach to constructively approximate channel capacity, establishing polar codes as the standard for the eMBB control channel. Facing the application scenarios of next-generation mobile communication systems, baseband signal processing technology faces significant challenges. Joint optimization of MIMO signal detection and channel decoding has demonstrated the potential to bring substantial system gains. For the polar codes selected as the standard for the 5G eMBB control channel, traditional separate and joint iterative methods are no longer sufficient to meet the requirements of high reliability and low latency communication. Therefore, proposing a synchronization set-assisted width-first spherical decoding method suitable for polar code-coded MIMO systems is of great significance.

[0057] In MIMO communication systems encoded with polar codes, the operating modes of the MIMO detection and polar code decoding modules can be divided into three types. The first type is the separate type, which treats detection and decoding as two independent processing modules, essentially a simple cascade of the MIMO detection and polar code decoding modules. Information is processed serially to obtain the final decoding result. Because the separate type fails to maximize the utilization of known polar code coding characteristics in the detection module, its error correction performance still falls far short of the Shannon limit, leaving significant room for improvement. To improve the error correction performance of the separate type, researchers proposed a second type: joint iterative detection-decoding. This involves using technical means to make the polar code decoding module output soft information, which is then fed back to the detection module for repeated iterations, thereby optimizing error correction performance. However, the multiple iterations in the joint iterative type inevitably increase the system latency.

[0058] The problems with the two MIMO detection and decoding algorithms mentioned above are as follows:

[0059] The detection and decoding modules always rely on the transmission of soft information. The calculation and storage of floating-point soft information results in high space complexity and consumes a lot of hardware resources.

[0060] The independent detection module failed to make the most of the prior information of the channel coding already adopted, resulting in a certain degree of performance loss;

[0061] The multiple iterations of joint iterative detection and decoding result in high time complexity, leading to high system latency.

[0062] Therefore, a third type of fusion-based detection decoding has emerged, generally implemented using spherical decoding or the K-best algorithm. Through bit enumeration, it ultimately outputs the decoding path with the minimum Euclidean distance to the received information. For MIMO fusion-based detection decoding algorithms using polar codes, the advantages are: the decoding part is based on bit enumeration, and the decoding architecture is the same as that of polar code encoding, which helps save storage resources and eliminates latency caused by iteration; fusion-based detection decoding can fully consider prior information from polar coding, such as the distribution of information bits and frozen bits, during bit enumeration, which can improve detection performance and reduce the original detection search space.

[0063] However, since the current bit enumeration for decoding uses a serial bit-by-bit order, the decoding order is based on the total length of the codeword, and the minimum Euclidean distance of each bit is calculated bit by bit in descending order. The current bit-by-bit enumeration order used for decoding is obviously not optimal, that is, the accuracy of the current decoding path is low, and there is still a lot of room for improvement in the detection performance of the system.

[0064] The following is a brief description of the implementation environment involved in the decoding path determination method provided in the embodiments of this application. The decoding path determination method provided in the embodiments of this application can be applied to, for example... Figure 1 The application environment shown. For example... Figure 1 As shown, this application environment may include a receiver 102 and a transmitter 101. The transmitter 101 maps the data signal to be transmitted onto multiple antennas through space-time mapping and transmits it. The receiver 102 performs space-time decoding on the signals received by each antenna to recover the data signal transmitted by the transmitter. The signal is transmitted and received through the antennas of the transmitter 101 and the receiver 102.

[0065] In this system, the transmitter 101 can use multiple transmitting antennas, and the receiver 102 can use multiple receiving antennas. For example, MIMO technology utilizes multiple antennas in the transmitter 101 to independently transmit signals, while multiple antennas in the receiver 102 receive and recover the original information, thereby achieving higher user rates at a lower cost.

[0066] The receiver 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, and smart in-vehicle systems. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. The transmitter 101 can be implemented using a standalone transmitter or a transmitter cluster consisting of multiple transmitters.

[0067] Having described the application scenarios of the decoding path determination method provided in the embodiments of this application, the following section will focus on the encoding process of polar codes.

[0068] Polar codes are channel coding techniques with practical linear complexity encoding and decoding capabilities. 5G communication has designated polar codes as the standard for the control channel of Enhanced Mobile Broadband (eMBB).

[0069] The encoding process of polar code x is x = uG, where u is the bit sequence to be encoded and G is the generator matrix of the polar code. For example, using Multiple Quadrature Amplitude Modulation (M-QAM) to modulate x, the modulated symbol S = map{uG}, where map{} represents the modulation function. After transmission through the channel, symbol S becomes a complex-valued received symbol. Each symbol It is mapped from a constellation diagram with M possible values.

[0070] For having N t One transmitting antenna and N r A MIMO system with one receiving antenna represents the received information as in For N r ×N t The complex channel matrix, The noise is Gaussian white noise. The sign with the minimum Euclidean distance is estimated using the Maximum Likelihood (ML) method:

[0071] Through real-valued decomposition, the equivalent channel model is: y = Hs + n, where H is 2N. r ×2N t The real-domain channel matrix. The length of the real-valued S is 2N. t The channel matrix H is decomposed into orthogonal trigonometric (QR) decompositions: H = QR, where Q represents 2N. r ×2N t Orthogonal matrix (unitary matrix), R is 2N r ×2N t Upper triangular matrix. Let z = Q H y, using ML detection methods to estimate the sign with the minimum Euclidean distance, can be represented as: According to s = map{uG}, this notation can be further written as: Since the formula for polar code sphere decoding is The formula has the same structure as the formula obtained using the ML detection method (y replaces z, G replaces R, u replaces s, where G and R are triangular matrices). Therefore, ML detection and polar code spherical decoding, as well as K-best detection and list-based spherical decoding, share certain similarities. Specifically, K-best detection and list-based spherical decoding are obtained by ML detection and polar code spherical decoding, respectively, by retaining the K decoding paths with the minimum Euclidean distance.

[0072] After the above process, the MIMO system detection and decoding are integrated into one process. Then, an equivalent directed graph based on symbols is constructed according to the polar code generation matrix. Based on the equivalent directed graph, at least two initial symbol synchronization sets are obtained. Based on the frozen symbols in each initial symbol synchronization set and the information symbols in the preset set, each initial symbol synchronization set is optimized to obtain an optimized symbol synchronization set. Finally, the receiver can determine the target decoding path based on the above optimized symbol synchronization set.

[0073] In one embodiment, such as Figure 2 As shown, a decoding path determination method is provided, which is applied to... Figure 1 Taking the receiving end as an example, the explanation includes the following steps:

[0074] S201. Construct a symbol-based equivalent directed graph based on the polar code generation matrix.

[0075] The polar code generator matrix can be the polar code generator matrix G described in the previous scenario. The equivalent directed graph is a directed graph with symbols as nodes and the connection relationships between symbols as edges.

[0076] In this embodiment of the application, the polar code generator matrix can be analyzed based on a preset mapping rule to construct an equivalent directed graph. For example, a symbol-based equivalent directed graph can be constructed as follows: construct a mapping rule from the polar code generator matrix to the equivalent directed graph; map a bit-based equivalent directed graph according to the mapping rule; treat at least two bits as a symbol to obtain a symbol-based equivalent directed graph.

[0077] The mapping rule from the polar code generator matrix to the equivalent directed graph is as follows: N bits correspond to N nodes in the equivalent directed graph of the symbol; if the element g in the i-th row and j-th column of the polar code generator matrix G... (i,j) If node i = 1 and satisfies i > j, i ∈ A, then in an equivalent directed graph, node i has a directed edge pointing to node j.

[0078] Furthermore, we define the frozen bit as the frozen bit, and the other types of bits as information bits. Directed edges must point from information bits to frozen bits. Figure 3An equivalent directed graph is given by mapping a polar code generator matrix G with a code length of 8, 3 information bits, and an information bit set of {6,7,8}. For example, directed edges can only be emitted by information bits 6, 7, and 8 and point to frozen bits 1, 2, 3, 4, and 5, and satisfy the condition that the element g in the i-th row and j-th column of the polar code generator matrix G is the key element. (i,j) When = 1, a directed edge exists between the information bit and the frozen bit. For example... Figure 3 If information bit 6 points to frozen bit 1, then the element g in the 6th row and 1st column of the polar code generator matrix G is... (6,1) =1; if information bit 8 points to frozen bit 4, then the element g in the 8th row and 4th column of the polar code generator matrix G is... (8,4) =1.

[0079] Furthermore, for M-QAM modulation, let M = 2 m After real-valued decomposition, one symbol corresponds to m / 2 bits. For example, for 16-QAM modulation, one symbol corresponds to 2 bits. That is, two adjacent bits are treated as a whole, the start and end points of the edges are corrected to symbols, duplicate edges are deleted, and edges that create self-loops are deleted, thus obtaining the symbol-based equivalent directed graph.

[0080] S202. Based on the equivalent directed graph, obtain at least two initial symbol synchronization sets.

[0081] The initial symbol synchronization set can include information symbols and frozen symbols. Symbols containing all frozen bits are defined as frozen symbols, while other types of symbols are defined as information symbols.

[0082] In this embodiment, the equivalent directed graph can be decomposed by removing the edges between symbols and placing related symbols in the same set to generate an initial symbol synchronization set. For example, for information symbol A in the equivalent directed graph, the edges originating from information symbol A can be deleted. Then, the frozen symbol B connected to information symbol A can be checked. If the in-degree of the frozen symbol connected to information symbol A is 0, then information symbol A and information symbol B are placed in the same set. All symbols in the equivalent directed graph can be traversed using the above method, and all symbols can be categorized into different sets to ultimately obtain multiple initial symbol synchronization sets.

[0083] For example, starting from the last information bit, remove the edges originating from it and check all frozen symbols. If the in-degree of a frozen bit is 0, then that information bit and the frozen bit will be placed in the same set, called the initial bit synchronization set. The Euclidean distance between bits in the same bit synchronization set will be calculated synchronously. By traversing all information bits in sequence, all initial bit synchronization sets of the equivalent directed graph corresponding to the polar code generator matrix are obtained.

[0084] S203. Based on the frozen symbols in each initial symbol synchronization set and the information symbols in the preset set, optimize each initial symbol synchronization set to obtain the optimized symbol synchronization set.

[0085] The preset set can be any set among the initial symbol synchronization sets. For example, at least two initial symbol synchronization sets may include initial symbol synchronization set 1, initial symbol synchronization set 2, and initial symbol synchronization set 3. If initial symbol synchronization set 1 is optimized, the preset set can be initial symbol synchronization set 2 or initial symbol synchronization set 3.

[0086] In this embodiment, the initial symbol synchronization sets can be optimized based on the dependencies between frozen symbols in the initial symbol synchronization set and information symbols in the preset set. For example, if the initial symbol synchronization set precedes the preset set according to the enumeration order of the sets, and if an information symbol in the preset set affects the value of a frozen symbol in the initial symbol synchronization set, then the frozen symbol in that initial symbol synchronization set should not be in the current initial symbol synchronization set. The frozen symbol can be placed in the preset set or in an initial symbol synchronization set that follows the enumeration order of the current initial symbol synchronization set. The initial symbol synchronization sets can be optimized in this way to ensure that the position of the symbols in each symbol synchronization set is more accurate, thus obtaining an optimized symbol synchronization set.

[0087] S204. Determine the target decoding path based on the optimized symbol synchronization set.

[0088] In this embodiment, the Euclidean distance of each symbol in each optimized symbol synchronization set can be enumerated according to the set enumeration order and the enumeration order of each symbol in each optimized symbol synchronization set, thereby determining the target decoding path based on the Euclidean distance of each symbol in each optimized symbol synchronization set. For example, when optimized symbol synchronization set 1 and optimized symbol synchronization set 2 are included, the Euclidean distance of each symbol in optimized symbol synchronization set 1 can be calculated first, and then the Euclidean distance of each symbol in optimized symbol synchronization set 2 can be calculated. The target decoding path can then be determined based on all the calculated Euclidean distances. Alternatively, K1 minimum Euclidean distances can be selected from the Euclidean distances of each symbol in optimized symbol synchronization set 1, and K2 minimum Euclidean distances can be selected from the Euclidean distances of each symbol in optimized symbol synchronization set 2. The target decoding path can then be determined based on the K1 minimum Euclidean distances and the K2 minimum Euclidean distances.

[0089] The decoding path determination method provided in this application constructs an equivalent directed graph based on symbols according to the polar code generator matrix. Based on the equivalent directed graph, at least two initial symbol synchronization sets are obtained. Each initial symbol synchronization set is optimized based on the frozen symbols in each set and the information symbols in a preset set, resulting in an optimized symbol synchronization set. The target decoding path is then determined based on the optimized symbol synchronization set. In this application embodiment, symbols are categorized into sets based on the equivalent directed graph, and the decoding path is determined based on these sets. This optimizes the symbol enumeration order, making path evaluation at each decoding level more accurate. Furthermore, optimizing the initial symbol synchronization sets further optimizes the enumeration order of symbols in the optimized symbol synchronization sets, resulting in a more accurate final target decoding path.

[0090] exist Figure 2 Based on the illustrated embodiment, after deleting edges in the equivalent directed graph, the initial symbol synchronization set can be determined according to the in-degree of the frozen symbols. Step S202, "obtain at least two initial symbol synchronization sets according to the equivalent directed graph", may include the following steps: after deleting the target edges of each information symbol according to the enumeration order of each symbol in the equivalent directed graph, the initial symbol synchronization set is determined according to the in-degree of the frozen symbols; the target edge is the edge starting from the signal symbol.

[0091] The in-degree of a frozen symbol refers to the number of directed edges that enter that frozen symbol.

[0092] In this embodiment, the symbols in the equivalent directed graph have a certain enumeration order. Based on the enumeration order, the edges originating from each information symbol can be deleted. Then, the in-degree of the frozen symbol connected to the information symbol is checked. If the in-degree of the frozen symbol is 0, the information symbol and the frozen symbol are placed in an initial symbol synchronization set. Each information symbol and frozen symbol is traversed in the enumeration order in the manner described above, and finally, each initial symbol synchronization set is obtained.

[0093] Furthermore, such as Figure 4 The process of obtaining the initial symbol synchronization set described above may include the following steps:

[0094] S401. Perform a classification operation; wherein, the classification operation includes: according to the enumeration order of each symbol in the equivalent directed graph, after deleting the target edge of the current information symbol, obtaining the in-degree of the target frozen symbol connected to the current information symbol after deleting the target edge; if the in-degree of the target frozen symbol is zero, then classify the current information symbol and the target frozen symbol into the same set.

[0095] S402. According to the enumeration order, determine the next information symbol adjacent to the current information symbol as the new current information symbol, and return to perform the classification operation until all symbols are classified into the set, and obtain the synchronization set of each initial symbol.

[0096] Please refer to Figure 5 The upper part shows a preliminary symbolic equivalent directed graph provided in an embodiment of this application. For example... Figure 5 As shown in the upper part, for 16-QAM modulation, one symbol corresponds to two bits, meaning that two adjacent bits are treated as a whole. In other words, according to the bit-by-bit sequence of bit enumeration, two adjacent bits are considered as one symbol. For example, bits 1 and 2 can be considered as symbol b1, and bits 3 and 4 can be considered as symbol b2. It should be noted that bits 8 and 1 cannot be considered as one symbol because they do not conform to the bit-by-bit sequence of bit enumeration.

[0097] Furthermore, starting from the last information symbol b4, the frozen symbols connected to b4 are b1 and b2. The edges originating from symbol b4 are deleted. Then, the in-degrees of frozen symbols b1 and b2 are checked. Since the in-degree of frozen symbol b2 is zero, information symbol b4 and frozen symbol b2 are placed in the same initial synchronization set. Next, the other information symbols are checked using the same method to obtain the initial synchronization set. Figure 5 As shown in the upper part, the last information symbol b4 and the frozen symbol b2 are in the same initial synchronization set T1' = {b4, b2}. The information symbol b3 and the frozen symbol b1 are in the same initial synchronization set T2' = {b3, b1}.

[0098] Furthermore, based on each initial symbol synchronization set, the enumeration order of the initial symbol synchronization sets is determined. For example, as... Figure 5 As shown in the upper part, the enumeration order of the initial symbol synchronization set is T1'>>T2'.

[0099] The initial symbol synchronization sets provided in this application are determined by deleting the target edges of each information symbol according to the enumeration order of each symbol in the equivalent directed graph, and then determining the initial symbol synchronization set based on the in-degree of the frozen symbols. In this application embodiment, the initial symbol synchronization set is determined based on the in-degree of the frozen symbols, converting the serial bit-by-bit enumeration sequence into an initial symbol synchronization set. Since the Euclidean distance of all symbols in the same initial symbol synchronization set can be calculated simultaneously, it is not necessary to calculate the Euclidean distance of each symbol in each initial synchronization set one by one according to the enumeration order, which optimizes the symbol enumeration order and further speeds up the decoding efficiency.

[0100] In some scenarios, to further improve the accuracy of the decoding path, the symbols in the initial symbol synchronization set can be optimized, such as... Figure 6 Step S203 may include the following steps:

[0101] S601. Obtain the first sequence number of the frozen symbols in the current symbol synchronization set and the second sequence number of the information symbols in the preset set; the current symbol synchronization set is any one of at least two initial symbol synchronization sets.

[0102] In this embodiment, each symbol in the current symbol synchronization set has a serial number. For example, the current symbol synchronization set is as described above. Figure 5 The initial synchronization set T1' = {b4, b2} is used, where b2 is a frozen symbol, and the first index of the frozen symbol b2 is 2. The preset set can be any set other than the current symbol synchronization set. For example, in this application, the preset set can be... Figure 5 In the initial synchronization set T2' = {b3, b1}, if the information symbol is b3, then the second sequence number of this information symbol is 3. This embodiment is merely an example and is not intended to limit the scope of the solution.

[0103] S602. Based on the first sequence number, the second sequence number, and the upper triangular matrix corresponding to the channel matrix, optimize the current symbol synchronization set to obtain the optimized symbol synchronization set.

[0104] In this embodiment, the upper triangular matrix can be the matrix R described above. The first and second indices can be regarded as indices of elements in matrix R, thereby locating the value of an element in matrix R based on the first and second indices, and optimizing the current symbol synchronization set based on the value of that element to obtain an optimized symbol synchronization set.

[0105] Furthermore, such as Figure 7 As shown, step S602 may include the following steps:

[0106] S701. Determine the value of the target element from the upper triangular matrix, with the first index as the row and the second index as the column.

[0107] In this embodiment, the current symbol synchronization set is still used as described above. Figure 5 The initial synchronization set T1' = {b4, b2} is preset to be... Figure 5 Taking the initial synchronization set T2'={b3,b1} as an example, the frozen symbol in T1'={b4,b2} is b2, and the information symbol in T2'={b3,b1} is b3. Then the first index is 2 and the second symbol is 3. So, with row 2 and column 3, we search for the value of element r(2,3) in the upper triangular matrix R as the value of the target element.

[0108] S702. If the second sequence number is greater than the first sequence number and the value of the target element is not zero, then the frozen symbol is deleted from the current symbol synchronization set and added to the target symbol synchronization set; the third sequence number of the information symbol in the target symbol synchronization set is less than the first sequence number, and the value of the element in the upper triangular matrix corresponding to the first and third sequence numbers is not zero; or, the target symbol synchronization set is a preset set.

[0109] Please refer to Figure 5 The lower half illustrates the improved symbolic equivalent directed graph provided in embodiments of this application. For example... Figure 5 As shown in the second half, for the frozen symbol b2 in the first initial symbol synchronization set T1' = {b4, b2}, a preset set k is found where the information symbol bi ∈ k. If i > 2 and the element r(2, i) ≠ 0 in the 2nd row and i-th column of matrix R, then b2 cannot be before bi. That is, b2 is either in the same set as bi or in the set following bi. Since the target symbol synchronization set has only two sets, T1' and T2', b2 must be in set T2'. Continuing with the current symbol synchronization set as described above... Figure 5 The initial synchronization set T1' = {b4, b2} is preset to be... Figure 5 Taking the initial synchronization set T2' = {b3, b1} as an example, the frozen symbol in T1' = {b4, b2} is b2, and the information symbol in T2' = {b3, b1} is b3. Then the first index is 2, the second symbol is 3, the second index 3 is greater than the first index 2, and the element r(2,3) in the second row and third column of the upper triangular matrix R is not zero. The frozen symbol b2 in the current symbol synchronization set T1' = {b4, b2} is deleted from the symbol synchronization set, and the frozen symbol b2 is added to the target symbol synchronization set. Since the target symbol synchronization set has only two T1' and T2', b2 must be in the T2' set.

[0110] Furthermore, such as Figure 5 As shown, the improved symbol synchronization sets T1 = {b4} and T2 = {b3, b2, b1} are obtained. Then, based on the improved symbol synchronization sets, the enumeration order of the improved symbol synchronization sets is determined. For example, as... Figure 5 As shown in the lower half, the enumeration order of the initial symbol synchronization set is T1 >> T2.

[0111] The initial symbol synchronization sets provided in this embodiment are optimized based on the first sequence number of the frozen symbols in the current symbol synchronization set and the second sequence number of the information symbols in the preset set. The optimization is achieved by using the first sequence number, the second sequence number, and the upper triangular matrix corresponding to the channel matrix. In this embodiment, the optimization of each initial symbol synchronization set based on the frozen symbols in the initial symbol synchronization set and the information symbols in the preset set ensures that each symbol can be correctly classified into the correct symbol synchronization set. This avoids errors in symbol position affecting the calculation of Euclidean distance, making the enumeration order of symbols in each symbol synchronization set more accurate, and thus resulting in a more precise target decoding path.

[0112] Based on any of the above embodiments, an optimized symbol synchronization set is obtained, and the target decoding path can be determined based on the Euclidean distance between the symbols in the optimized symbol synchronization set. For example... Figure 8 As shown, step S204 may include the following steps:

[0113] S801. Based on the enumeration order of each optimized symbol synchronization set, obtain the Euclidean distance of each information symbol in each optimized symbol synchronization set.

[0114] In this embodiment, the Euclidean distance of each information symbol can be calculated using the formula... The calculation shows that, in this formula, u is the bit sequence corresponding to the two bits in each symbol.

[0115] S802. Determine the target decoding path based on the Euclidean distance of each information symbol in each optimized symbol synchronization set.

[0116] Since each information symbol may have multiple Euclidean distances, the Euclidean distance of the optimized symbol synchronization set is related to the Euclidean distance of each information symbol, while the Euclidean distance of the frozen symbol has no effect on the Euclidean distance of the optimized symbol synchronization set.

[0117] For example, one can first calculate the Euclidean distance of each information symbol in each optimized symbol synchronization set, and then combine these Euclidean distances to determine the target decoding path. Alternatively, one can calculate the Euclidean distance of each information symbol in each optimized symbol synchronization set in the enumeration order, determine N optimal Euclidean distances for each symbol, and determine the target decoding path based on these N optimal Euclidean distances. Another approach is to calculate the Euclidean distance of each information symbol in each optimized symbol synchronization set in the enumeration order, determine the Euclidean distance of each optimized symbol synchronization set based on the Euclidean distances of its symbols, and then determine the decoding path based on these Euclidean distances.

[0118] Furthermore, such as Figure 9 Step S802 may include the following steps:

[0119] S901. Based on the Euclidean distance of each information symbol in each optimized symbol synchronization set, determine a preset number of candidate decoding paths for each optimized symbol synchronization set.

[0120] In this embodiment, the preset number of candidate decoding paths can be all decoding paths corresponding to the Euclidean distance of each information symbol in each optimized symbol synchronization set, or it can be the K paths with the smallest Euclidean distance among each information symbol in each optimized symbol synchronization set.

[0121] S902. Determine the target decoding path based on the candidate decoding paths corresponding to each optimized symbol synchronization set.

[0122] Specifically, for example, suppose there are improved symbol synchronization sets T1 and T2. First, calculate the Euclidean distance for the improved symbol synchronization set T1 and retain the K1 best paths (i.e., the paths with the smallest Euclidean distance). Then, calculate the Euclidean distance for set T2 and retain the K2 best paths. Add the K1 best paths from set T1 and the K2 best paths from set T2, for a total of K1×K2 paths. Then, retain the K3 paths with the smallest Euclidean distance from the K1×K2 paths as the target decoding paths.

[0123] The target decoding path provided in this embodiment obtains the Euclidean distance of each information symbol in each optimized symbol synchronization set according to the enumeration order of each optimized symbol synchronization set; and determines the target decoding path based on the Euclidean distance of each information symbol in each optimized symbol synchronization set. In this embodiment, because the symbols in the symbol synchronization set are further optimized, the enumeration order of the symbols is more accurate, the path evaluation at each decoding level is more precise, and therefore the final target decoding path is also more accurate.

[0124] Figure 10 A flowchart of a decoding path determination method provided in this application embodiment is shown below. Figure 9 As shown, the method may include the following steps:

[0125] S1001. Construct mapping rules from polar code generator matrices to equivalent directed graphs.

[0126] The mapping rule includes: N bits correspond to N nodes in a directed graph;

[0127] If the element g in the i-th row and j-th column of the polar code generator matrix (i,j) If node i = 1 and satisfies i > j, i ∈ A, then in an equivalent directed graph, node i has a directed edge pointing to node j.

[0128] S1002. Construct an equivalent directed graph based on bit nodes based on mapping rules and polar code generation matrices.

[0129] S1003. Bit-based equivalent directed graph: Map consecutive bits to symbols, correct the start and end points of edges to symbols, delete duplicate edges, and delete edges that create self-loops to obtain a symbol-based equivalent directed graph.

[0130] S1004. According to the enumeration order of each symbol in the equivalent directed graph, after deleting the target edge of the current information symbol, obtain the in-degree of the target frozen symbol connected to the current information symbol after deleting the target edge. If the in-degree of the target frozen symbol is zero, then classify the current information symbol and the target frozen symbol into the same set.

[0131] S1005. According to the enumeration order, determine the next information symbol adjacent to the current information symbol as the new current information symbol, and return to execute the deletion of the target edge of the new current information symbol. After deleting the target edge, obtain the in-degree of the target frozen symbol connected to the new current information symbol. If the in-degree of the target frozen symbol is zero, then classify the new current information symbol and the target frozen symbol into the same set. Continue until all symbols are classified into the same set, and obtain the synchronization set of each initial symbol.

[0132] S1006. Obtain the first sequence number of the frozen symbols in the current symbol synchronization set and the second sequence number of the information symbols in the preset set; the current symbol synchronization set is any one of at least two initial symbol synchronization sets.

[0133] S1007. Using the first index as the row and the second index as the column, determine the value of the target element from the upper triangular matrix.

[0134] S1008. If the second sequence number is greater than the first sequence number and the value of the target element is not zero, then the frozen symbol is deleted from the current symbol synchronization set and added to the target symbol synchronization set; the third sequence number of the information symbol in the target symbol synchronization set is less than the first sequence number, and the value of the element in the upper triangular matrix corresponding to the first and third sequence numbers is not zero; or, the target symbol synchronization set is a preset set.

[0135] S1009. Based on the enumeration order of each optimized symbol synchronization set, obtain the Euclidean distance of each information symbol in each optimized symbol synchronization set.

[0136] S1010. Based on the Euclidean distance of each information symbol in each optimized symbol synchronization set, determine a preset number of candidate decoding paths for each optimized symbol synchronization set.

[0137] S1011. Determine the target decoding path based on the candidate decoding paths corresponding to each optimized symbol synchronization set.

[0138] The target decoding path provided in this embodiment obtains the Euclidean distance of each information symbol in each optimized symbol synchronization set according to the enumeration order of each optimized symbol synchronization set; and determines the target decoding path based on the Euclidean distance of each information symbol in each optimized symbol synchronization set. Taking the modulation of 4 symbols as an example, where symbols 4 and 3 are information symbols containing multiple possibilities, and symbols 2 and 1 are frozen symbols with fixed values, existing fusion-based detection decoding requires 4 enumeration levels. In this embodiment, each edge pointing from node i to node j in the symbol-meaning equivalent directed graph represents the influence of the value of symbol i on the calculation of the Euclidean distance of symbol j. The generated symbol-meaning synchronization sets are T1 and T2, requiring only 2 enumeration levels. That is, at the same enumeration level, the Euclidean distance of more symbols is considered, improving the accuracy of path evaluation.

[0139] Furthermore, such as Figure 11 As shown, in a simulation environment with N=128 and 11 information bits, the proposed width-first spherical decoding method, compared with existing width-first spherical decoding methods, achieves a frame error rate (FER) of 10 when the parameter K=4. -3The required signal-to-noise ratio (SNR) is only 9dB, which is up to 7.7dB higher than the existing width-first ball decoding method.

[0140] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps.

[0141] Based on the same inventive concept, this application also provides a detection decoding apparatus for implementing the decoding path determination method described above. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations in one or more detection decoding apparatus embodiments provided below can be found in the limitations of the decoding path determination method described above, and will not be repeated here.

[0142] In one embodiment, such as Figure 12 The diagram shown is a structural block diagram of a decoding path determination device in one embodiment. A decoding path determination device includes: a construction module 201, an acquisition module 202, an optimization module 203, and a determination module 204, wherein:

[0143] Module 201 is used to construct a symbol-based equivalent directed graph based on the polar code generation matrix;

[0144] Module 202 is used to obtain at least two initial symbol synchronization sets based on the equivalence directed graph;

[0145] Optimization module 203 is used to optimize each initial symbol synchronization set based on the frozen symbols in each initial symbol synchronization set and the information symbols in the preset set, so as to obtain the optimized symbol synchronization set;

[0146] The determination module 204 is used to determine the target decoding path based on the optimized symbol synchronization set.

[0147] Furthermore, in Figure 12Based on the embodiment shown, the acquisition module 202 is specifically used to delete the target edges of each information symbol according to the enumeration order of each symbol in the equivalent directed graph, and then determine the initial symbol synchronization set according to the in-degree of the frozen symbols; the target edge is the edge that starts from the signal symbol.

[0148] In one embodiment, such as Figure 13 As shown, the acquisition module 202 includes:

[0149] Classification unit 2021 is used to perform classification operations; wherein, the classification operations include: according to the enumeration order of each symbol in the equivalent directed graph, after deleting the target edge of the current information symbol, obtaining the in-degree of the target frozen symbol connected to the current information symbol after deleting the target edge; if the in-degree of the target frozen symbol is zero, then classify the current information symbol and the target frozen symbol into the same set.

[0150] The first determining unit 2022 is used to determine the next information symbol adjacent to the current information symbol as the new current information symbol according to the enumeration order, and return to perform the classification operation until all symbols are classified into the set, thus obtaining the initial symbol synchronization set.

[0151] In one embodiment, such as Figure 14 As shown, optimization module 203 includes:

[0152] The first acquisition unit 2031 is used to acquire the first sequence number of the frozen symbols in the current symbol synchronization set and the second sequence number of the information symbols in the preset set; the current symbol synchronization set is any one of at least two initial symbol synchronization sets.

[0153] The optimization unit 2032 is used to optimize the current symbol synchronization set according to the first sequence number, the second sequence number and the upper triangular matrix corresponding to the channel matrix, so as to obtain the optimized symbol synchronization set.

[0154] In one embodiment, the optimization unit 2032 is specifically used to determine the value of the target element from the upper triangular matrix with the first index as the row and the second index as the column; if the second index is greater than the first index and the value of the target element is not zero, then the frozen symbol is deleted from the current symbol synchronization set and the frozen symbol is added to the target symbol synchronization set; the third index of the information symbol in the target symbol synchronization set is less than the first index, and the values ​​of the elements in the upper triangular matrix corresponding to the first index and the third index are not zero; or, the target symbol synchronization set is a preset set.

[0155] In one embodiment, such as Figure 15 As shown, the determining module 204 includes:

[0156] The second acquisition unit 2041 is used to acquire the Euclidean distance of each information symbol in each optimized symbol synchronization set according to the enumeration order of each optimized symbol synchronization set; and to determine the target decoding path according to the Euclidean distance of each information symbol in each optimized symbol synchronization set.

[0157] The second determining unit 2042 is used to determine the target decoding path based on the Euclidean distance of each information symbol in each optimized symbol synchronization set.

[0158] In one embodiment, the optimization unit 2042 is specifically used to determine a preset number of candidate decoding paths for each optimized symbol synchronization set based on the Euclidean distance of each information symbol in each optimized symbol synchronization set; and to determine the target decoding path based on the candidate decoding paths corresponding to each optimized symbol synchronization set.

[0159] The implementation principle and beneficial effects of the decoding path determination device provided in the above embodiments can be referred to the embodiments of the corresponding decoding path determination methods, and will not be repeated here.

[0160] Specific limitations regarding the decoding path determination device can be found in the limitations of the decoding path determination method above, and will not be repeated here. Each module in the aforementioned decoding path determination device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in the computer device in hardware form, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0161] Each module in the aforementioned decoding path determination device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0162] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 16As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores data such as decoding paths, polar codes, and sets. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a decoding path determination method.

[0163] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 17 As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When executed by the processor, the computer program implements a decoding path determination method. The display screen can be an LCD screen or an e-ink display screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0164] Those skilled in the art will understand that Figure 16 and Figure 17 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0165] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0166] Construct symbol-based equivalent directed graphs based on polar code generation matrices;

[0167] Based on the equivalence directed graph, obtain at least two initial symbol synchronization sets;

[0168] Based on the frozen symbols in each initial symbol synchronization set and the information symbols in the preset set, each initial symbol synchronization set is optimized to obtain the optimized symbol synchronization set.

[0169] The target decoding path is determined based on the optimized symbol synchronization set.

[0170] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0171] Based on the enumeration order of each symbol in the equivalent directed graph, the target edges of each information symbol are deleted, and the initial symbol synchronization set is determined according to the in-degree of the frozen symbols; the target edge is the edge that originates from the signal symbol.

[0172] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0173] Perform a classification operation; wherein, the classification operation includes: according to the enumeration order of each symbol in the equivalent directed graph, after deleting the target edge of the current information symbol, obtaining the in-degree of the target frozen symbol connected to the current information symbol after deleting the target edge; if the in-degree of the target frozen symbol is zero, then classify the current information symbol and the target frozen symbol into the same set.

[0174] According to the enumeration order, the next information symbol adjacent to the current information symbol is determined as the new current information symbol, and the classification operation is performed until all symbols are classified into the set, thus obtaining the initial symbol synchronization set.

[0175] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0176] Get the first sequence number of the frozen symbol in the current symbol synchronization set and the second sequence number of the information symbol in the preset set; the current symbol synchronization set is any one of at least two initial symbol synchronization sets;

[0177] Based on the first sequence number, the second sequence number, and the upper triangular matrix corresponding to the channel matrix, the current symbol synchronization set is optimized to obtain the optimized symbol synchronization set.

[0178] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0179] Determine the value of the target element from the upper triangular matrix, using the first index as the row and the second index as the column;

[0180] If the second sequence number is greater than the first sequence number, and the value of the target element is not zero, then the frozen symbol is removed from the current symbol synchronization set and added to the target symbol synchronization set; the third sequence number of the information symbol in the target symbol synchronization set is less than the first sequence number, and the values ​​of the elements in the upper triangular matrix corresponding to the first and third sequence numbers are not zero; or, the target symbol synchronization set is a preset set.

[0181] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0182] Based on the enumeration order of each optimized symbol synchronization set, obtain the Euclidean distance of each information symbol in each optimized symbol synchronization set;

[0183] The target decoding path is determined based on the Euclidean distance between each information symbol in each optimized symbol synchronization set.

[0184] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0185] Based on the Euclidean distance between each information symbol in each optimized symbol synchronization set, a preset number of candidate decoding paths are determined for each optimized symbol synchronization set.

[0186] The target decoding path is determined based on the candidate decoding paths corresponding to each optimized symbol synchronization set.

[0187] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0188] Construct symbol-based equivalent directed graphs based on polar code generation matrices;

[0189] Based on the equivalence directed graph, obtain at least two initial symbol synchronization sets;

[0190] Based on the frozen symbols in each initial symbol synchronization set and the information symbols in the preset set, each initial symbol synchronization set is optimized to obtain the optimized symbol synchronization set.

[0191] The target decoding path is determined based on the optimized symbol synchronization set.

[0192] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0193] Based on the enumeration order of each symbol in the equivalent directed graph, the target edges of each information symbol are deleted, and the initial symbol synchronization set is determined according to the in-degree of the frozen symbols; the target edge is the edge that originates from the signal symbol.

[0194] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0195] Perform a classification operation; wherein, the classification operation includes: according to the enumeration order of each symbol in the equivalent directed graph, after deleting the target edge of the current information symbol, obtaining the in-degree of the target frozen symbol connected to the current information symbol after deleting the target edge; if the in-degree of the target frozen symbol is zero, then classify the current information symbol and the target frozen symbol into the same set.

[0196] According to the enumeration order, the next information symbol adjacent to the current information symbol is determined as the new current information symbol, and the classification operation is performed until all symbols are classified into the set, thus obtaining the initial symbol synchronization set.

[0197] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0198] Get the first sequence number of the frozen symbol in the current symbol synchronization set and the second sequence number of the information symbol in the preset set; the current symbol synchronization set is any one of at least two initial symbol synchronization sets;

[0199] Based on the first sequence number, the second sequence number, and the upper triangular matrix corresponding to the channel matrix, the current symbol synchronization set is optimized to obtain the optimized symbol synchronization set.

[0200] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0201] Determine the value of the target element from the upper triangular matrix, using the first index as the row and the second index as the column;

[0202] If the second sequence number is greater than the first sequence number, and the value of the target element is not zero, then the frozen symbol is removed from the current symbol synchronization set and added to the target symbol synchronization set; the third sequence number of the information symbol in the target symbol synchronization set is less than the first sequence number, and the values ​​of the elements in the upper triangular matrix corresponding to the first and third sequence numbers are not zero; or, the target symbol synchronization set is a preset set.

[0203] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0204] Based on the enumeration order of each optimized symbol synchronization set, obtain the Euclidean distance of each information symbol in each optimized symbol synchronization set;

[0205] The target decoding path is determined based on the Euclidean distance between each information symbol in each optimized symbol synchronization set.

[0206] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0207] Based on the Euclidean distance between each information symbol in each optimized symbol synchronization set, a preset number of candidate decoding paths are determined for each optimized symbol synchronization set.

[0208] The target decoding path is determined based on the candidate decoding paths corresponding to each optimized symbol synchronization set.

[0209] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0210] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0211] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method of determining a decoding path, characterized by, The method comprises: constructing a symbol-based equivalent directed graph according to a polar code generator matrix; obtaining at least two initial symbol synchronization sets according to the equivalent directed graph; obtaining a first serial number of a frozen symbol in a current symbol synchronization set and a second serial number of an information symbol in a preset set; the current symbol synchronization set is any one of the at least two initial symbol synchronization sets; optimizing the current symbol synchronization set according to the first serial number, the second serial number and an upper triangular matrix corresponding to a channel matrix to obtain an optimized symbol synchronization set; determining a target decoding path according to the optimized symbol synchronization set.

2. The method of claim 1, wherein, The obtaining at least two initial symbol synchronization sets according to the equivalent directed graph comprises: after deleting target edges of each information symbol according to an enumeration order of each symbol in the equivalent directed graph, determining the initial symbol synchronization set according to in-degrees of frozen symbols; the target edge is an edge starting from a signal symbol.

3. The method of claim 2, wherein, The obtaining at least two initial symbol synchronization sets according to the equivalent directed graph comprises: performing a classification operation; wherein the classification operation comprises: after deleting target edges of a current information symbol according to the enumeration order of each symbol in the equivalent directed graph, obtaining in-degrees of target frozen symbols connected to the current information symbol after the target edges are deleted, and if the in-degree of a target frozen signal is zero, classifying the current information symbol and the target frozen symbol into a same set; according to the enumeration order, determining a next information symbol adjacent to the current information symbol as a new current information symbol, and returning to perform the classification operation until all symbols are classified into sets to obtain each initial symbol synchronization set.

4. The method of claim 1, wherein, The optimizing each initial symbol synchronization set according to the first serial number, the second serial number and the upper triangular matrix corresponding to the channel matrix to obtain the optimized symbol synchronization set comprises: determining a value of a target element from the upper triangular matrix with the first serial number as a row and the second serial number as a column; if the second serial number is greater than the first serial number and the value of the target element is not zero, deleting the frozen symbol from the current symbol synchronization set and adding the frozen symbol to a target symbol synchronization set; a third serial number of an information symbol in the target symbol synchronization set is less than the first serial number, and a value of an element in the upper triangular matrix corresponding to the first serial number and the third serial number is not zero; or the target symbol synchronization set is the preset set.

5. The method according to any one of claims 1 to 3, characterized in that, The determining a target decoding path according to the optimized symbol synchronization set comprises: obtaining Euclidean distances of each information symbol in each optimized symbol synchronization set according to an enumeration order of each optimized symbol synchronization set; determining the target decoding path according to the Euclidean distances of each information symbol in each optimized symbol synchronization set.

6. The method of claim 5, wherein, The determining the target decoding path according to the Euclidean distances of each information symbol in each optimized symbol synchronization set comprises: A preset number of candidate decoding paths are determined for each of the optimized symbol synchronization sets according to the Euclidean distances of the information symbols in each of the optimized symbol synchronization sets; The target decoding path is determined according to the candidate decoding paths corresponding to each of the optimized symbol synchronization sets.

7. A decoding path determination apparatus characterized by comprising: The apparatus comprises: A construction module configured to construct a symbol-based equivalent directed graph according to a polar code generation matrix; An acquisition module configured to acquire at least two initial symbol synchronization sets according to the equivalent directed graph; An optimization module configured to acquire a first serial number of frozen symbols in a current symbol synchronization set and a second serial number of information symbols in a preset set; the current symbol synchronization set is any one of the at least two initial symbol synchronization sets; the current symbol synchronization set is optimized according to the first serial number, the second serial number and an upper triangular matrix corresponding to a channel matrix to obtain an optimized symbol synchronization set; A determination module configured to determine a target decoding path according to the optimized symbol synchronization set.

8. The apparatus of claim 7, wherein, The acquisition module is further configured to, after deleting target edges of each information symbol according to an enumeration order of each symbol in the equivalent directed graph, determine the initial symbol synchronization set according to the in-degree of the frozen symbols; the target edge is an edge starting from a signal symbol. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8 when the computer program is executed by the processor. The processor executes the computer program to implement the steps of the method in any one of claims 1 to 6.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method in any one of claims 1 to 6.

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