A method, system and device for signal-to-noise ratio evaluation based on polar code performance estimation

Abstract

This application discloses a signal-to-noise ratio (SNR) assessment method, system, and device based on polar code performance estimation. The method comprises obtaining a target received signal after an original signal is transmitted through a target transmission channel, the original signal comprising a signal obtained by encoding target original information using a polar code method; calculating a target decoding error rate (BER) for the target received signal; and determining a target SNR corresponding to the target decoding error rate based on a preset correspondence between the decoding error rate and the SNR. In this application, the target SNR corresponding to the target decoding error rate can be determined solely based on the preset correspondence between the decoding error rate and the SNR, enabling rapid SNR assessment based on polar codes. The method is low in complexity and easy to implement.

Description

Technical Field

[0001] The present application relates to the technical fields of channel coding and signal-to-noise ratio estimation for wireless communications, and more specifically, to a signal-to-noise ratio evaluation method, system, and device based on polar code performance estimation. Background Art

[0002] To ensure highly reliable information transmission, wireless communication systems must employ advanced error control technologies, and channel coding is fundamental to wireless communication technology. Polar codes are the first constructive coding scheme theoretically proven to achieve channel capacity. They feature a regular coding structure, low decoding complexity, and excellent error correction performance. The theoretical basis of polar codes is channel polarization. By recombining and splitting multiple independent physical channels of equal capacity, multiple virtual composite subchannels with varying capacities are generated. Based on this principle, high-reliability composite subchannels (called information bits) are used during encoding to transmit user information, while low-reliability composite subchannels (called frozen bits) carry known, fixed bits. For decoding polar codes, the list-based serial cancellation (SCL) decoding algorithm offers excellent performance and low complexity, making it a commonly used high-performance decoder for polar codes. When analyzing codeword error performance, performance estimates of other coding schemes, such as LDPC codes and Turbo codes, often rely on extensive and complex experimental simulations, rather than theoretical analysis and calculation. This makes it extremely inconvenient for evaluating channel quality and optimizing information transmission performance. However, the regular coding structure and polarization construction of polar codes facilitate error performance analysis based on the coding principle. This fact, coupled with the fact that polar codes can be theoretically estimated, lends itself to a wide range of applications, such as signal-to-noise ratio estimation for channel quality assessment.

[0003] In summary, how to perform signal-to-noise ratio evaluation based on polar codes is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0004] The present application aims to provide a method for signal-to-noise ratio (SNR) evaluation based on polar code performance estimation, which can, to a certain extent, address the technical problem of how to perform SNR evaluation based on polar codes. The present application also provides a system, device, and computer-readable storage medium for SNR evaluation based on polar code performance estimation.

[0005] In order to achieve the above objectives, this application provides the following technical solutions:

[0006] A signal-to-noise ratio evaluation method based on polar code performance estimation includes:

[0007] Obtaining a target received signal after the original signal is transmitted through the target transmission channel, wherein the original signal includes a signal obtained by encoding the target original information based on a polar code method;

[0008] Calculating a target decoding error rate of the target received signal;

[0009] Based on a preset correspondence between a decoding error rate and a signal-to-noise ratio, a target signal-to-noise ratio corresponding to the target decoding error rate is determined.

[0010] Preferably, before determining the target signal-to-noise ratio corresponding to the target decoding error rate based on the preset correspondence between the decoding error rate and the signal-to-noise ratio, the method further includes:

[0011] Obtaining a test received signal after a test signal is transmitted through a test transmission channel, the test signal including a signal obtained by encoding original test information based on the polar code method, and a signal-to-noise ratio of the test transmission channel being a preset value;

[0012] determining a target calculation mode for a decoding error rate of the test received signal;

[0013] Calculating the decoding error rate of the test received signal based on the target calculation mode;

[0014] The corresponding relationship between the decoding error rate of the test received signal and the signal-to-noise ratio of the test transmission channel is established.

[0015] Preferably, the target calculation mode for determining the decoding error rate of the test received signal includes:

[0016] If the polar code method uses a rate-compatible code with a code length of M, the test transmission channel is an additive white Gaussian noise channel, and the decoding mode of the target received signal is a serial cancellation decoding algorithm, the target calculation mode for determining the decoding error rate of the test received signal is a rate-compatible code conditional mode.

[0017] Preferably, calculating the decoding error rate of the test received signal based on the target calculation mode includes:

[0018] If the type of the rate-compatible code is a code obtained by puncturing a mother codeword, calculating the decoding error rate of the test received signal based on a first operation formula;

[0019] The first operation formula includes:

[0020]

[0021]

[0022]

[0023]

[0024]

[0025] Among them, P BLER represents the decoding error rate; N represents the mother code length of the polar code method; represents the subchannel index set carrying information bits during encoding; SNR represents the preset signal-to-noise ratio; M represents the code length of the rate-compatible code; P e represents the error probability; Indicates truncated style; represents the set of codeword bit indices to be deleted; represents the remaining codeword bit index set, σ 2 represents the noise variance; y i represents the i-th received signal in the test received signal; L(y i ) represents y i The log-likelihood ratio of ; E represents the mean; represents the log-likelihood ratio of the first channel in the test transmission channel when dimension N=2; represents the log-likelihood ratio of the second channel in the test transmission channel when dimension N=2; represents the i-th polarization subchannel.

[0026] Preferably, calculating the decoding error rate of the test received signal based on the target calculation mode includes:

[0027] If the type of the rate-compatible code is a code obtained by shortening a mother codeword, calculating the decoding error rate of the test received signal based on a second operation formula;

[0028] The second operation formula includes:

[0029]

[0030]

[0031]

[0032]

[0033]

[0034] Among them, P BLER represents the decoding error rate; N represents the mother code length of the polar code method; represents the subchannel index set carrying information bits during encoding; SNR represents the preset signal-to-noise ratio; M represents the code length of the rate-compatible code; P e represents the error probability; Indicates a shortened style; represents the set of codeword bit indices to be shortened; represents the remaining codeword bit index set, σ 2 represents the noise variance; y i represents the i-th received signal in the test received signal; L(y i ) represents y i The log-likelihood ratio of ; E represents the mean; represents the log-likelihood ratio of the first channel in the test transmission channel when dimension N=2; represents the log-likelihood ratio of the second channel in the test transmission channel when dimension N=2; represents the i-th polarization subchannel.

[0035] Preferably, the target calculation mode for determining the decoding error rate of the test received signal includes:

[0036] If the polar code method is a rate-compatible code with a code length of M, the test transmission channel is a Rayleigh fading channel, and the decoding method of the target received signal is a serial elimination decoding algorithm, the target calculation mode for determining the decoding error rate of the test received signal is a fading channel condition mode.

[0037] Preferably, calculating the decoding error rate of the test received signal based on the target calculation mode includes:

[0038] Calculating a first symmetric channel capacity of the Rayleigh fading channel based on the test received signal based on a third operation formula;

[0039] Based on a fourth operation formula, calculating a second symmetric channel capacity of an additive white Gaussian noise channel converted from the Rayleigh fading channel based on the test received signal;

[0040] Determining, based on the monotonically decreasing property of the symmetric channel capacity of the additive white Gaussian noise channel with the noise variance, a target noise variance that makes the second symmetric channel capacity equal to the first symmetric channel capacity;

[0041] Calculating an error probability of each polarimetric subchannel in the additive white Gaussian noise channel based on the target noise variance;

[0042] Calculating the decoding error rate of the test received signal based on the error probability;

[0043] The third operation formula includes:

[0044]

[0045] Among them, I Frepresents the first symmetric channel capacity; p(h)=2hexp(-h 2 ); σ 2 represents the noise variance of the Rayleigh fading channel, and the test received signal under the Rayleigh fading channel is y i =h i ·s i +n i , i∈{1,2,...,N}, N represents the mother code length of the polar code method, s i =1-2x i ,x i ∈{0,1},s i represents the modulated test signal; x i Represents the codeword after polarization coding; n i represents independent and identically distributed Gaussian noise; h i Indicates that it obeys an independent Rayleigh fading distribution;

[0046] The fourth operation formula includes:

[0047]

[0048] Among them, I G represents the second symmetric channel capacity.

[0049] Preferably, the target calculation mode for determining the decoding error rate of the test received signal includes:

[0050] If the polar code method uses a rate-compatible code with a code length of M, the test transmission channel is an additive white Gaussian noise channel, and the decoding method of the target received signal is a list-based serial cancellation decoding algorithm, then the target calculation mode for determining the decoding error rate of the test received signal is a high-performance SCL decoder conditional mode.

[0051] Preferably, calculating the decoding error rate of the test received signal based on the target calculation mode includes:

[0052] If the signal-to-noise ratio of the test transmission channel is less than a preset value, calculating the decoding error rate of the test received signal based on a fifth operation formula;

[0053] The fifth operation formula includes:

[0054]

[0055] Among them, P BLER represents the decoding error rate; N represents the mother code length of the polar code method; represents the subchannel index set carrying information bits during encoding; SNR represents the preset signal-to-noise ratio; P e TB represents the bound of the tangent bound; λ d represents the Euclidean distance between two modulated signals, E s represents the energy of each coded symbol; γ represents the correction constant; σ squared represents the noise variance; weight spectrum coefficient A d represents the number of codewords with Hamming weight d; Q represents the error function.

[0056] Preferably, calculating the decoding error rate of the test received signal based on the target calculation mode includes:

[0057] If the signal-to-noise ratio of the test transmission channel is greater than or equal to a preset value, calculating the decoding error rate of the test received signal based on the sixth operation formula or the seventh operation formula;

[0058] The sixth operation formula includes:

[0059]

[0060] The seventh operation formula includes:

[0061]

[0062] Among them, P BLER represents the decoding error rate; N represents the mother code length of the polar code method; represents the subchannel index set carrying information bits during encoding; SNR represents the preset signal-to-noise ratio; P e UB represents the bound value of the joint bound; ε d Denotes the set of codewords with Hamming weight d {c i} error event;P e IB Indicates the boundary value of the set intersection; the square of σ represents the noise variance; the weight spectrum coefficient A d represents the number of codewords with Hamming weight d; Q represents the error function; represents the pairwise error probability; Pr represents the probability.

[0063] A signal-to-noise ratio evaluation system based on polar code performance estimation, comprising:

[0064] a first acquisition module, configured to acquire a target received signal after the original signal is transmitted through the target transmission channel, wherein the original signal includes a signal obtained by encoding the target original information based on a polar code method;

[0065] A first calculation module is used to calculate a target decoding error rate of the target received signal;

[0066] The first determining module is configured to determine a target signal-to-noise ratio corresponding to the target decoding error rate based on a preset correspondence between the decoding error rate and the signal-to-noise ratio.

[0067] A signal-to-noise ratio evaluation device based on polar code performance estimation, comprising:

[0068] memory for storing computer programs;

[0069] A processor, configured to implement the steps of any of the above signal-to-noise ratio evaluation methods based on polar code performance estimation when executing the computer program.

[0070] A computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the steps of any of the above-described signal-to-noise ratio evaluation methods based on polar code performance estimation.

[0071] The present application provides a signal-to-noise ratio evaluation method based on polar code performance estimation, which obtains a target received signal after an original signal is transmitted through a target transmission channel, wherein the original signal includes a signal obtained by encoding the target original information based on a polar code method; calculates a target decoding error rate of the target received signal; and determines a target signal-to-noise ratio corresponding to the target decoding error rate based on a preset correspondence between the decoding error rate and the signal-to-noise ratio. In the present application, after obtaining a target received signal transmitted via a polar code method, the target decoding error rate of the target received signal can be calculated, and the target signal-to-noise ratio corresponding to the target decoding error rate can be determined based solely on the preset correspondence between the decoding error rate and the signal-to-noise ratio, thereby achieving rapid signal-to-noise ratio evaluation based on polar codes. The method has low complexity and is easy to implement. The present application provides a signal-to-noise ratio evaluation system, device, and computer-readable storage medium based on polar code performance estimation, which also solves corresponding technical problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without any creative work.

[0073] Figure 1 A flowchart of a signal-to-noise ratio evaluation method based on polar code performance estimation provided in an embodiment of the present application;

[0074] Figure 2Another flowchart of a signal-to-noise ratio evaluation method based on polar code performance estimation provided in an embodiment of the present application;

[0075] Figure 3 A specific schematic diagram of a signal-to-noise ratio evaluation method based on polar code performance estimation provided in an embodiment of the present application;

[0076] Figure 4 This is a flowchart for calculating the decoding error rate in the rate compatible code condition mode;

[0077] Figure 5 Flowchart for calculating decoding error rate under fading channel condition mode;

[0078] Figure 6 This is a flowchart for calculating the decoding error rate in the conditional mode of the high-performance SCL decoder;

[0079] Figure 7 A schematic diagram of the structure of a signal-to-noise ratio evaluation system based on polar code performance estimation provided in an embodiment of the present application;

[0080] Figure 8 A schematic structural diagram of a signal-to-noise ratio evaluation device based on polar code performance estimation provided in an embodiment of the present application;

[0081] Figure 9 Another structural diagram of a signal-to-noise ratio evaluation device based on polar code performance estimation provided in an embodiment of the present application. DETAILED DESCRIPTION

[0082] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0083] See also Figure 1 , Figure 1 This is a flowchart of a signal-to-noise ratio evaluation method based on polar code performance estimation provided in an embodiment of the present application.

[0084] An embodiment of the present application provides a signal-to-noise ratio evaluation method based on polar code performance estimation, which may include the following steps:

[0085] Step S101: obtaining a target received signal after an original signal is transmitted through a target transmission channel, where the original signal includes a signal obtained by encoding target original information based on a polar code method.

[0086] In practical applications, a target received signal can be first obtained after the original signal is transmitted through the target transmission channel, and the original signal includes a signal obtained by encoding the target original information based on the polar code method.

[0087] It should be noted that the corresponding information of the original signal, the target transmission channel, and the target received signal can be determined according to actual needs, and this application does not make any specific limitations here.

[0088] Step S102: Calculate a target decoding error rate of a target received signal.

[0089] In actual applications, after obtaining the target received signal after the original signal is transmitted through the target transmission channel, the target decoding error rate of the target received signal can be calculated. The specific process of calculating the target decoding error rate of the target received signal can be determined according to actual needs, and this application does not make specific limitations here.

[0090] Step S103: determining a target signal-to-noise ratio corresponding to a target decoding error rate based on a preset correspondence between a decoding error rate and a signal-to-noise ratio.

[0091] In practical applications, after calculating the target decoding error rate of the target received signal, the target signal-to-noise ratio corresponding to the target decoding error rate can be determined based on a preset correspondence between the decoding error rate and the signal-to-noise ratio.

[0092] In practical applications, after determining the target signal-to-noise ratio corresponding to the target decoding error rate based on the preset correspondence between the decoding error rate and the signal-to-noise ratio, a channel quality assessment result of the target transmission channel can also be generated based on the target signal-to-noise ratio.

[0093] The present application provides a signal-to-noise ratio assessment method based on polar code performance estimation. The method comprises the following steps: obtaining a target received signal after an original signal is transmitted through a target transmission channel, wherein the original signal includes a signal obtained by encoding the target original information based on a polar code method; calculating a target decoding error rate of the target received signal; determining a target signal-to-noise ratio corresponding to the target decoding error rate based on a preset correspondence between the decoding error rate and the signal-to-noise ratio; and generating a channel quality assessment result of the target transmission channel based on the target signal-to-noise ratio. In the present application, after obtaining a target received signal transmitted via a polar code method, the target decoding error rate of the target received signal can be calculated. Moreover, the target signal-to-noise ratio corresponding to the target decoding error rate can be determined simply based on the preset correspondence between the decoding error rate and the signal-to-noise ratio. This method achieves rapid signal-to-noise ratio assessment based on polar codes, and the method has low complexity and is easy to implement.

[0094] See also Figure 2 and Figure 3 , Figure 2 This is another flowchart of a signal-to-noise ratio evaluation method based on polar code performance estimation provided in an embodiment of the present application. Figure 3 This is a specific schematic diagram of a signal-to-noise ratio evaluation method based on polar code performance estimation provided in an embodiment of the present application.

[0095] An embodiment of the present application provides a signal-to-noise ratio evaluation method based on polar code performance estimation, which may include the following steps:

[0096] Step S201: Acquire a test received signal after a test signal is transmitted through a test transmission channel. The test signal includes a signal obtained by encoding original test information based on a polar code method, and the signal-to-noise ratio of the test transmission channel is a preset value.

[0097] In practical applications, a correspondence between a decoding error rate and a signal-to-noise ratio can be established in advance based on a test signal. In this process, a test received signal can be obtained after the test signal is transmitted through a test transmission channel. The test signal includes a signal obtained by encoding the original test information based on a polar code method, and the signal-to-noise ratio of the test transmission channel is a preset value.

[0098] Step S202: Determine a target calculation mode for testing the decoding error rate of the received signal.

[0099] In practical applications, after obtaining a test received signal after the test signal is transmitted through a test transmission channel, a target calculation mode for a decoding error rate of the test received signal may be determined.

[0100] Step S203: Calculate the decoding error rate of the test received signal based on the target calculation mode.

[0101] In practical applications, after determining the target calculation mode for the decoding error rate of the test received signal, the decoding error rate of the test received signal can be calculated based on the target calculation mode. Specifically, in the wireless communication scenario involved in the present application, the channel coding adopts a polar code scheme, the transmitting end adopts a polar code encoder, the receiving end decoder can adopt a serial cancellation (SC) decoder or a list-based serial cancellation (SCL) decoder, and the modulation method can adopt a binary phase keying BPSK (Binary Phase Shift Keying) scheme. The channel types involved in the present application may include additive white Gaussian noise channels and Rayleigh fading channels. Furthermore, the conditional mode for polar code BLER (Block error rate) estimation can be selected based on the communication requirements and the codeword settings, channel types, and decoder schemes in the communication system. The three conditional modes can be: rate compatible code conditional mode, fading channel conditional mode, and high-performance SCL decoder conditional mode.

[0102] For specific application scenarios, please refer to Figure 4In the process of determining the target calculation mode for the decoding error rate of the test received signal, if the code length of the polar code method is a rate-compatible code with an M code length, the test transmission channel is an additive white Gaussian noise channel, and the decoding method of the target received signal is a serial cancellation decoding algorithm, then the target calculation mode for the decoding error rate of the test received signal is determined to be the rate-compatible code conditional mode. In this case, the rate-compatible polar code of any code length is generally generated by puncturing or shortening the mother codeword to puncture the polar code PC. p For example, some codeword bits are deleted during transmission, and the set Represents the set of punctured codeword bit indices, which is equivalent to turning this part of the physical channel into a full-noise channel. In this case, the capacities of the N independent physical channels become inconsistent during the polarization process. Under this condition, the improved Gaussian approximation algorithm can be used to recalculate the error probability of each sub-channel after polarization based on the puncturing pattern of the codeword, and then calculate the block error rate estimate of the target rate compatible polar code. i The mean of the initialized log-likelihood ratio LLR is expressed as:

[0103]

[0104] Among them, the remaining bit set σ 2 is the channel noise variance. For the case of two AWGN channels (N=2), the LLR means of the two physical channels are E[L(y1)] and E[L(y2)] respectively. Based on the basic construction unit of the polar code with N=2, the Gaussian approximation algorithm is used to recalculate the mean log-likelihood ratio of the two sub-channels after polarization transformation.

[0105]

[0106]

[0107] Wherein, u represents the integral variable in the integral formula and has no specific practical meaning; and for punctured codewords of general length (N>2), the butterfly coding structure based on the polar code can be obtained through iterative calculation. Then each polariton channel The error probability is calculated as:

[0108]

[0109] in Indicates truncated style, It should be noted that λ represents the integral variable in the integral formula, has no specific practical meaning, and will be eliminated after the integration is completed. p The BLER estimate is calculated as:

[0110]

[0111] Indicates the subchannel index set that carries information bits during coding. s (The corresponding shortened codeword bit index set is ), the BLER estimation value can be calculated by referring to the above method, except that the signal y is received in the AWGN channel i The initial LLR expectation is expressed as

[0112] That is, in the process of calculating the decoding error rate of the test received signal based on the target calculation mode, if the type of the rate-compatible code is a code obtained by puncturing the mother codeword, the decoding error rate of the test received signal can be calculated based on the first calculation formula;

[0113] The first calculation formula includes:

[0114]

[0115]

[0116]

[0117]

[0118]

[0119] Among them, P BLER Indicates the decoding error rate, where the decoding error rate type is BLER (Block Error Rate). N indicates the mother code length of the polar code method. represents the subchannel index set that carries information bits during encoding; SNR represents the preset signal-to-noise ratio; M represents the code length of the rate-compatible code; P e represents the error probability; Indicates truncated style; represents the set of codeword bit indices to be deleted; represents the remaining codeword bit index set, σ 2 represents the noise variance; y i Indicates the i-th received signal in the test received signal; L(y i ) represents y i The log-likelihood ratio of ; E represents the mean; represents the log-likelihood ratio of the first channel in the test transmission channel when dimension N=2; represents the log-likelihood ratio of the second channel in the test transmission channel when dimension N=2; represents the i-th polarization subchannel.

[0120] Accordingly, in the process of calculating the decoding error rate of the test received signal based on the target calculation mode, if the type of the rate-compatible code is a code obtained by shortening the mother codeword, the decoding error rate of the test received signal can be calculated based on the second calculation formula;

[0121] The second calculation formula includes:

[0122]

[0123]

[0124]

[0125]

[0126]

[0127] Among them, P BLER represents the decoding error rate; N represents the mother code length of the polar code method; represents the subchannel index set that carries information bits during encoding; SNR represents the preset signal-to-noise ratio; M represents the code length of the rate-compatible code; P e represents the error probability; Indicates a shortened style; represents the set of codeword bit indices to be shortened; represents the remaining codeword bit index set, σ 2 represents the noise variance; y i Indicates the i-th received signal in the test received signal; L(y i ) represents y i The log-likelihood ratio of ; E represents the mean; represents the log-likelihood ratio of the first channel in the test transmission channel when dimension N=2; represents the log-likelihood ratio of the second channel in the test transmission channel when dimension N=2; represents the i-th polarization subchannel.

[0128] For specific application scenarios, please refer to Figure 5 In the process of determining the target calculation mode for the decoding error rate of the test received signal, if the polar code method is a rate-compatible code with a code length of M, the test transmission channel is a Rayleigh fading channel, and the decoding method of the target received signal is the serial cancellation decoding algorithm, then the target calculation mode for the decoding error rate of the test received signal can be determined to be the fading channel condition mode. In this case, in the process of calculating the decoding error rate, the noise variance can be set to 1 according to the channel capacity equality criterion. The target Rayleigh fading channel is approximately converted into an equivalent additive white Gaussian noise channel The noise variance is For the Rayleigh fading channel W F , receiving signal y i =h i ·s i +n i (i∈{1,2,...,N}), where s i =1-2x i ,x i ∈{0,1} is the modulated transmission signal, x i is the codeword after polarization coding, n i is the independent and identically distributed Gaussian noise n i ~N(0,σ 2 ); Channel coefficient h i Obeying independent Rayleigh fading distribution, the probability density function is p(h)=2hexp(-h 2 ). W F The symmetric channel capacity of each state is calculated as:

[0129]

[0130] in, With W F Equivalent AWGN channel Satisfy with W F The same symmetric channel capacity, i.e. Then, for the target fading channel W F Based on the monotonically decreasing property of the symmetrical channel capacity of the AWGN channel with the noise variance, an efficient search algorithm can be used to determine the channel that is approximately equivalent to it. The noise variance is Furthermore, an improved Gaussian approximation method is used to calculate the error probability of each polarization subchannel in the equivalent AWGN channel. Then, the BLER estimate is calculated, ultimately obtaining the block error rate (BLER) estimate of the rate-compatible polarization code under Rayleigh fading channel conditions.

[0131] That is, in the process of calculating the decoding error rate of the test received signal based on the target calculation mode, the first symmetric channel capacity of the Rayleigh fading channel can be calculated based on the test received signal based on the third calculation formula; the second symmetric channel capacity of the additive white Gaussian noise channel converted from the Rayleigh fading channel can be calculated based on the test received signal based on the fourth calculation formula; based on the monotonically decreasing property of the symmetric channel capacity of the additive white Gaussian noise channel with the noise variance, a target noise variance is determined that makes the second symmetric channel capacity equal to the first symmetric channel capacity; based on the target noise variance, the error probability of each polarization subchannel is calculated in the additive white Gaussian noise channel; and based on the error probability, the decoding error rate of the test received signal is calculated.

[0132] The third operation formula includes:

[0133]

[0134] Among them, I F represents the first symmetric channel capacity; p(h)=2hexp(-h 2 );σ 2 Represents the noise variance of the Rayleigh fading channel. The test received signal under the Rayleigh fading channel is y i =h i ·s i +n i , i∈{1,2,...,N}, N represents the mother code length of the polar code method, s i =1-2x i ,x i ∈{0,1},s i Represents the modulated test signal; x i Represents the codeword after polarization coding; n i represents independent and identically distributed Gaussian noise; h i Indicates that it obeys an independent Rayleigh fading distribution;

[0135] The fourth operation formula includes:

[0136]

[0137] Among them, I G represents the second symmetric channel capacity.

[0138] For specific application scenarios, please refer to Figure 6In the process of determining the target calculation mode of the decoding error rate of the test received signal, if the code length of the polar code method is a rate-compatible code of M, the test transmission channel is an additive white Gaussian noise channel, and the decoding method of the target received signal is a list-based serial elimination decoding algorithm, then the target calculation mode of the decoding error rate of the test received signal can be determined to be a high-performance SCL decoder conditional mode. At this time, in the process of calculating the decoding error rate, when the list size is L>8, the SCL decoding performance in the high SNR range is basically consistent with the ML decoding performance bound. In view of this, the present application first proposes to use the union bound (UB) of the polar code to estimate the BLER performance of the SCL decoding. Assuming that the noise variance is σ 2 When sending all-0 codewords in an AWGN channel, the joint upper bound of the polar code block error rate is:

[0139]

[0140] where ε d Denotes the set of codewords corresponding to Hamming weight d (d≥1) {c i} error event, weight spectrum coefficient A d is the number of codewords with Hamming weight d, Represents the pairwise error probability, Q(x) is the error function; Pr represents the probability of the corresponding event. The joint bound is used to estimate the block error rate. Because it only contains the calculation of the weight spectrum and the Q function, the complexity is low and it is consistent with the actual block error rate at high signal-to-noise ratios. However, the disadvantage is that the joint bound is the upper bound of the block error rate. Especially at low signal-to-noise ratios, the gap with the actual block error rate statistics is large, and it may even be greater than 1. Therefore, the set intersection (IB) is used to estimate the block error rate of polar codes under SCL decoding to narrow the estimation gap at low signal-to-noise ratios. The set intersection is also the upper bound of the probability of code block decoding error, with low computational complexity. The calculation form is expressed as:

[0141]

[0142] Use the set intersection to estimate the block error rate, satisfying P e IB <P e UB , closely matches the actual block error rate at high SNRs and is guaranteed to be less than 1 at low SNRs. However, at low SNRs, there is still a gap between the set boundary and the actual block error rate statistics. To further improve the performance estimation accuracy, the tangent bound (TB) is used to estimate the block error rate in the low SNR range. Based on the definition of the tangent bound and simplified calculation, the expression is:

[0143]

[0144] Among them, λ drepresents the Euclidean distance between two BPSK modulated signals and is calculated as E s is the energy per coded symbol, N is the length of the code block, and the optimized correction constant γ is obtained by calculating the partial derivative of the function on the right side of the above inequality.

[0145] Based on the above analysis and calculation, the method for estimating the polar code block error rate performance under the high-performance SCL decoder conditional mode is as follows: first, based on the input polar code codeword conditions, the polarization weight spectrum of the target codeword is analyzed and calculated. Then, based on the input signal-to-noise ratio (SNR), the joint bound, set intersection bound, and tangent bound of the polar code error probability under the maximum likelihood decoding criterion are calculated. These upper bounds on the block error rate performance are used to estimate the block error rate of the polar code under SCL decoding conditions. Under high SNR conditions, the joint bound or set intersection bound is used to estimate the block error rate value, reducing the computational complexity. Under low SNR conditions, the tangent bound is used to estimate the block error rate value, improving the performance estimation accuracy.

[0146] That is, in the process of calculating the decoding error rate of the test received signal based on the target calculation mode, if the signal-to-noise ratio of the test transmission channel is less than the preset value, the decoding error rate of the test received signal can be calculated based on the fifth operation formula;

[0147] The fifth operation formula includes:

[0148]

[0149] Among them, P BLER represents the decoding error rate; N represents the mother code length of the polar code method; represents the subchannel index set that carries information bits during encoding; SNR represents the preset signal-to-noise ratio; P e TB represents the bound of the tangent bound; λ d represents the Euclidean distance between two modulated signals, E s represents the energy of each coded symbol; γ represents the correction constant; σ squared represents the noise variance; weight spectrum coefficient A d represents the number of codewords with Hamming weight d; Q represents the error function.

[0150] Accordingly, in the process of calculating the decoding error rate of the test received signal based on the target calculation mode, if the signal-to-noise ratio of the test transmission channel is greater than or equal to the preset value, the decoding error rate of the test received signal can be calculated based on the sixth operation formula or the seventh operation formula;

[0151] The sixth operation formula includes:

[0152]

[0153] The seventh operation formula includes:

[0154]

[0155] Among them, P BLER represents the decoding error rate; N represents the mother code length of the polar code method; represents the subchannel index set that carries information bits during encoding; SNR represents the preset signal-to-noise ratio; P e UB represents the bound value of the joint bound; ε d Denotes the set of codewords with Hamming weight d {c i} error event;P e IB Indicates the boundary value of the set intersection; N represents the length of the code block; σ squared represents the noise variance; weight spectrum coefficient A d represents the number of codewords with Hamming weight d; Q represents the error function; represents the pairwise error probability; Pr represents the probability.

[0156] It should be noted that in this application, the corresponding target calculation mode is determined based on the rate-compatible code. In specific application scenarios, non-punctured or shortened conventional polar codewords can also be directly applied to determine the corresponding target calculation mode, that is, a codeword with a full code length of M=N, etc. This application does not make any specific restrictions here.

[0157] As can be seen from the foregoing description, this application leverages the inherent coding structure of polar codes to theoretically analyze and estimate the error performance of polar coding under diverse conditions, avoiding the need for statistically analyzing error performance results through numerous redundant Monte Carlo simulations. Furthermore, the estimation method is low in complexity and easy to implement. Verification has shown that the theoretical performance estimation results of this application closely match the actual statistical results of simulation experiments, particularly at high signal-to-noise ratios, demonstrating the high accuracy of the estimation method.

[0158] Step S204: establishing a corresponding relationship between the decoding error rate of the test received signal and the signal-to-noise ratio of the test transmission channel.

[0159] In practical applications, after calculating the decoding error rate of the test received signal based on the target calculation mode, a corresponding relationship between the decoding error rate of the test received signal and the signal-to-noise ratio of the test transmission channel can be established.

[0160] Step S205: Acquire a target received signal after the original signal is transmitted through the target transmission channel, where the original signal includes a signal obtained by encoding the target original information based on the polar code method.

[0161] Step S206: Counting the target decoding error rate of the target received signal.

[0162] In a specific application scenario, the target decoding error rate of the target received signal is counted at the receiving end.

[0163] Step S207: Determine a target signal-to-noise ratio corresponding to a target decoding error rate based on a preset correspondence between the decoding error rate and the signal-to-noise ratio.

[0164] See also Figure 7 , Figure 7 A schematic structural diagram of a signal-to-noise ratio evaluation system based on polar code performance estimation provided in an embodiment of the present application.

[0165] An embodiment of the present application provides a signal-to-noise ratio evaluation system based on polar code performance estimation, which may include:

[0166] A first acquisition module 101 is configured to acquire a target received signal after the original signal is transmitted through a target transmission channel, where the original signal includes a signal obtained by encoding the target original information based on a polar code method;

[0167] A first calculation module 102 is configured to calculate a target decoding error rate of a target received signal;

[0168] The first determining module 103 is configured to determine a target signal-to-noise ratio corresponding to a target decoding error rate based on a preset correspondence between the decoding error rate and the signal-to-noise ratio.

[0169] For descriptions of corresponding modules in a signal-to-noise ratio assessment system based on polar code performance estimation provided in an embodiment of the present application, reference can be made to the above embodiments and will not be repeated here.

[0170] The present application also provides a signal-to-noise ratio evaluation device based on polar code performance estimation and a computer-readable storage medium, both of which have the corresponding effects of the signal-to-noise ratio evaluation method based on polar code performance estimation provided in the embodiments of the present application. Figure 8 , Figure 8 A schematic structural diagram of a signal-to-noise ratio evaluation device based on polar code performance estimation provided in an embodiment of the present application.

[0171] An embodiment of the present application provides a signal-to-noise ratio assessment device based on polar code performance estimation, including a memory 201 and a processor 202. The memory 201 stores a computer program, and when the processor 202 executes the computer program, the steps of the signal-to-noise ratio assessment method based on polar code performance estimation described in any of the above embodiments are implemented.

[0172] See also Figure 9Another signal-to-noise ratio assessment device based on polar code performance estimation provided in an embodiment of the present application may further include: an input port 203 connected to the processor 202, for transmitting external input commands to the processor 202; a display unit 204 connected to the processor 202, for displaying the processing results of the processor 202 to the outside world; and a communication module 205 connected to the processor 202, for enabling communication between the signal-to-noise ratio assessment device based on polar code performance estimation and the outside world. The display unit 204 may be a display panel, a laser scanning display, or the like. The communication methods used by the communication module 205 include, but are not limited to, mobile high-definition link technology (HML), universal serial bus (USB), high-definition multimedia interface (HDMI), wireless connection (such as wireless fidelity technology (WiFi), Bluetooth communication technology, low-power Bluetooth communication technology, and communication technology based on IEEE802.11s.

[0173] An embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps of the signal-to-noise ratio evaluation method based on polar code performance estimation as described in any of the above embodiments are implemented.

[0174] The computer-readable storage medium involved in this application includes random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium known in the technical field.

[0175] For descriptions of the relevant portions of the signal-to-noise ratio assessment system, device, and computer-readable storage medium based on polar code performance estimation provided in the embodiments of the present application, please refer to the detailed descriptions of the corresponding portions of the signal-to-noise ratio assessment method based on polar code performance estimation provided in the embodiments of the present application, and are not repeated here. Furthermore, portions of the above-mentioned technical solutions provided in the embodiments of the present application that are consistent with the implementation principles of corresponding technical solutions in the prior art are not described in detail to avoid redundant description.

[0176] It should also be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0177] The above description of the disclosed embodiments will enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A signal-to-noise ratio evaluation method based on polar code performance estimation, characterized in that: include: Obtaining a target received signal after the original signal is transmitted through the target transmission channel, wherein the original signal includes a signal obtained by encoding the target original information based on a polar code method; Calculating a target decoding error rate of the target received signal; Determining a target signal-to-noise ratio corresponding to the target decoding error rate based on a preset correspondence between the decoding error rate and the signal-to-noise ratio; Before determining the target signal-to-noise ratio corresponding to the target decoding error rate based on the preset correspondence between the decoding error rate and the signal-to-noise ratio, the method further includes: Obtaining a test received signal after a test signal is transmitted through a test transmission channel, the test signal including a signal obtained by encoding original test information based on the polar code method, and a signal-to-noise ratio of the test transmission channel being a preset value; determining a target calculation mode for a decoding error rate of the test received signal; Calculating the decoding error rate of the test received signal based on the target calculation mode; The corresponding relationship between the decoding error rate of the test received signal and the signal-to-noise ratio of the test transmission channel is established.

2. The method according to claim 1, characterized in that The target calculation mode for determining the decoding error rate of the test received signal includes: If the code length of the polar code method is The rate-compatible code is used, the test transmission channel is an additive white Gaussian noise channel, and the decoding method of the target received signal is a serial elimination decoding algorithm, then the target calculation mode for determining the decoding error rate of the test received signal is a rate-compatible code conditional mode.

3. The method according to claim 2, characterized in that The calculating the decoding error rate of the test received signal based on the target calculation mode includes: If the type of the rate-compatible code is a code obtained by puncturing a mother codeword, calculating the decoding error rate of the test received signal based on a first operation formula; The first operation formula includes: ； ； ； ； ； ； in, represents the decoding error rate; represents the mother code length of the polar code method; Indicates the subchannel index set that carries information bits during encoding; represents the preset signal-to-noise ratio; represents the code length of the rate-compatible code; represents the error probability; Indicates truncated style; Represents the set of codeword bit indices to be deleted; represents the remaining codeword bit index set, ; represents the noise variance; Indicates the first Received signal; express The log-likelihood ratio of represents the mean; Representation Dimension The log-likelihood ratio of the first channel in the test transmission channels; Representation Dimension The log-likelihood ratio of the second channel in the test transmission channel when ; Indicates the polarization sub-channels.

4. The method according to claim 2, characterized in that The calculating the decoding error rate of the test received signal based on the target calculation mode includes: If the type of the rate-compatible code is a code obtained by shortening a mother codeword, calculating the decoding error rate of the test received signal based on a second operation formula; The second operation formula includes: ； ； ； ； ； ； in, represents the decoding error rate; represents the mother code length of the polar code method; Indicates the subchannel index set that carries information bits during encoding; represents the preset signal-to-noise ratio; represents the code length of the rate-compatible code; represents the error probability; Indicates a shortened style; represents the set of codeword bit indices to be shortened; represents the remaining codeword bit index set, ; represents the noise variance; Indicates the first Received signal; express The log-likelihood ratio of represents the mean; Representation Dimension The log-likelihood ratio of the first channel in the test transmission channels; Representation Dimension The log-likelihood ratio of the second channel in the test transmission channel when ; Indicates the polarization sub-channels.

5. The method according to claim 1, wherein The target calculation mode for determining the decoding error rate of the test received signal includes: If the code length of the polar code method is The rate compatible code is used, the test transmission channel is a Rayleigh fading channel, and the decoding method of the target received signal is a serial elimination decoding algorithm, then the target calculation mode for determining the decoding error rate of the test received signal is a fading channel condition mode.

6. The method according to claim 5, characterized in that The calculating the decoding error rate of the test received signal based on the target calculation mode includes: Calculating a first symmetric channel capacity of the Rayleigh fading channel based on the test received signal based on a third operation formula; Based on a fourth operation formula, calculating a second symmetric channel capacity of an additive white Gaussian noise channel converted from the Rayleigh fading channel based on the test received signal; Determining, based on the monotonically decreasing property of the symmetric channel capacity of the additive white Gaussian noise channel with the noise variance, a target noise variance that makes the second symmetric channel capacity equal to the first symmetric channel capacity; Calculating an error probability of each polarimetric subchannel in the additive white Gaussian noise channel based on the target noise variance; Calculating the decoding error rate of the test received signal based on the error probability; The third operation formula includes: ； in, represents the first symmetric channel capacity; ; represents the noise variance of the Rayleigh fading channel, and the test received signal under the Rayleigh fading channel is , , represents the mother code length of the polar code method, , represents the modulated test signal; represents the codeword after polar coding; represents independent and identically distributed Gaussian noise; Indicates that it obeys an independent Rayleigh fading distribution; The fourth operation formula includes: ； ； in, represents the second symmetric channel capacity.

7. The method according to claim 1, characterized in that The target calculation mode for determining the decoding error rate of the test received signal includes: If the code length of the polar code method is The test transmission channel is an additive white Gaussian noise channel, and the decoding method of the target received signal is a list-based serial elimination decoding algorithm, then the target calculation mode for determining the decoding error rate of the test received signal is a high-performance SCL decoder conditional mode.

8. The method according to claim 7, characterized in that The calculating the decoding error rate of the test received signal based on the target calculation mode includes: If the signal-to-noise ratio of the test transmission channel is less than a preset value, calculating the decoding error rate of the test received signal based on a fifth operation formula; The fifth operation formula includes: ； in, represents the decoding error rate; represents the mother code length of the polar code method; Indicates the subchannel index set that carries information bits during encoding; represents the preset signal-to-noise ratio; represents the bound of the tangent bound; represents the Euclidean distance between two modulated signals, , represents the energy of each coded symbol; represents the correction constant; The square of the noise variance; the weight spectrum coefficient The Hamming weight is The number of code words; represents the error function.

9. The method according to claim 7, characterized in that The calculating the decoding error rate of the test received signal based on the target calculation mode includes: If the signal-to-noise ratio of the test transmission channel is greater than or equal to a preset value, calculating the decoding error rate of the test received signal based on the sixth operation formula or the seventh operation formula; The sixth operation formula includes: ； The seventh operation formula includes: ； in, represents the decoding error rate; represents the mother code length of the polar code method; Indicates the subchannel index set that carries information bits during encoding; represents the preset signal-to-noise ratio; represents the bound value of the joint bound; The Hamming weight is The codeword set Error events; The boundary value representing the intersection of the sets; The square of the noise variance; the weight spectrum coefficient The Hamming weight is The number of code words; represents the error function; represents the pairwise error probability; Represents probability.

10. A signal-to-noise ratio evaluation system based on polar code performance estimation, characterized in that: include: a first acquisition module, configured to acquire a target received signal after the original signal is transmitted through the target transmission channel, wherein the original signal includes a signal obtained by encoding the target original information based on a polar code method; A first calculation module is used to calculate a target decoding error rate of the target received signal; A first determining module is configured to determine a target signal-to-noise ratio corresponding to the target decoding error rate based on a preset correspondence between the decoding error rate and the signal-to-noise ratio; The system, before determining the target signal-to-noise ratio corresponding to the target decoding error rate based on a preset correspondence between the decoding error rate and the signal-to-noise ratio, is further configured to: obtain a test received signal after the test signal is transmitted through a test transmission channel, the test signal including a signal obtained by encoding original test information based on the polar code method, and the signal-to-noise ratio of the test transmission channel being a preset value; Determine a target calculation mode for the decoding error rate of the test received signal; calculate the decoding error rate of the test received signal based on the target calculation mode; and establish the correspondence between the decoding error rate of the test received signal and the signal-to-noise ratio of the test transmission channel.

11. A signal-to-noise ratio evaluation device based on polar code performance estimation, characterized in that: include: memory for storing computer programs; A processor, configured to implement the steps of the signal-to-noise ratio evaluation method based on polar code performance estimation according to any one of claims 1 to 9 when executing the computer program.

12. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the signal-to-noise ratio evaluation method based on polar code performance estimation according to any one of claims 1 to 9.

Images