A polarization code construction method and system based on underwater acoustic channel

Abstract

The present invention provides a polarization code construction method and system based on an underwater acoustic channel, and relates to the technical field of underwater acoustic communication. The method comprises: obtaining a preset number of experiments of a Monte Carlo experiment, a code length of a polarization code, a wave number of subcarriers in the frequency domain of an underwater acoustic channel, and a block coding rate; performing a Monte Carlo experiment according to the preset number of experiments, the code length of the polarization code, and the wave number of the subcarrier to obtain the approximate Bhattacharyya parameters of all subchannels of each subcarrier, thereby obtaining the sum of the channel capacity of the subcarrier; obtaining the coding rate corresponding to the subcarrier through a coding allocation algorithm according to the block coding rate of the sum of the channel capacity; obtaining the number of information bits of the subcarrier according to the coding rate and the code length of the polarization code; obtaining the subchannel for placing information bits and the subchannel for placing frozen bits according to the approximate Bhattacharyya parameters of the subchannel and the number of information bits of the subcarrier. Independently allocating the coding rate of the subcarrier through the coding allocation algorithm improves the efficiency and quality of signal transmission.

Description

Technical Field

[0001] The present invention relates to the technical field of underwater acoustic communication, and in particular to a method and system for constructing polarization codes based on an underwater acoustic channel. Background Art

[0002] At present, the Monte Carlo construction method is usually used for the polarization code construction of underwater acoustic channels, which includes conducting a sufficient number of Monte Carlo experiments in training, and after completing a specified number of Monte Carlo experiments, counting the approximate Bhattacharyya parameters of all sub-channels, and then allocating information bits and frozen bits in combination with a preset uniform coding rate to complete the polarization code construction.

[0003] In the prior art, strong multipath time-varying underwater acoustic channels can cause severe frequency selective fading, resulting in different signal-to-noise ratios for frequency domain subcarriers. In the prior art, polarization code construction generally does not consider the attenuation difference of subcarriers. Therefore, a uniform coding rate is used for allocation when selecting information bits and frozen bits, which may cause high-capacity polarization subchannels on better subcarriers to be wasted, while low-capacity subchannels are used to transmit information bits, resulting in the inability to effectively use channels to transmit information. Summary of the invention

[0004] The problem solved by the present invention is how to improve the communication capability of polarization codes in an underwater acoustic channel.

[0005] In order to solve the above problems, the present invention provides a polarization code construction method based on an underwater acoustic channel, comprising:

[0006] Obtaining the preset number of experiments of the Monte Carlo experiment, the code length of the polarization code, the wave number of subcarriers in the frequency domain of the underwater acoustic channel, and the block coding rate;

[0007] Performing a Monte Carlo experiment according to the preset number of experiments, the code length of the polarization code, and the wave number of the subcarrier to obtain approximate Bhattacharyya parameters of all subchannels of each of the subcarriers;

[0008] Obtaining the sum of the channel capacities of the subcarriers according to the approximate Bhattacharyya parameters of all the subchannels;

[0009] According to the total channel capacity and the block coding rate, a coding rate corresponding to each of the subcarriers is obtained through a coding allocation algorithm; wherein after the coding rate corresponding to each of the subcarriers is obtained, the block coding rate remains unchanged;

[0010] Obtaining, according to the coding rate corresponding to the subcarrier and the code length of the polarization code, the number of information bits of the subcarrier;

[0011] According to the approximate Bhattacharyya parameter of the subchannel of the subcarrier and the number of information bits of the subcarrier, a subchannel for placing the information bits and a subchannel for placing frozen bits are obtained.

[0012] Optionally, the performing a Monte Carlo experiment to obtain approximate Bhattacharyya parameters of all subchannels of each of the subcarriers according to the preset number of experiments, the code length of the polarization code, and the wave number of the subcarrier includes:

[0013] generating a binary random sequence according to the code length of the polar code and the wave number of the subcarrier, wherein the number of the binary random sequences is the wave number of the subcarrier, and the length of the binary random sequence is the code length of the polar code;

[0014] Performing interleaving processing according to a binary random sequence, distributing the polarization code along the time domain and performing OFDM modulation, obtaining a receiving sequence with the same number as the wave number of the subcarrier, decoding the subcarrier to obtain a decoding result vector, and increasing the number of experiments by one time;

[0015] When the number of experiments reaches the preset number of experiments, the Monte Carlo experiment is judged to be completed, and the approximate Bhattacharyya parameters of all subchannels of each subcarrier are obtained based on the received sequence and the decoding result vector of the subcarrier obtained in each experiment.

[0016] Optionally, obtaining the approximate Bhattacharyya parameters of all subchannels of each subcarrier according to the decoding result vector of the received sequence and the subcarrier obtained in each experiment includes:

[0017] According to the received sequence obtained in each experiment and the decoding result vector of the subcarrier, the approximate Bhattacharyya parameters of all subchannels of each subcarrier are obtained by using the approximate Bhattacharyya parameter formula;

[0018] The approximate Bhattacharyya parameter formula is:

[0019]

[0020] in, is the decoding result vector of the subcarrier, U i is the i-th value of the decoding result vector, is the received sequence, is the probability of satisfying the condition in brackets in the i-th subchannel of the polar code with the code length N.

[0021] Optionally, obtaining the sum of the channel capacities of the subcarriers according to the approximate Bhattacharyya parameters of all the subchannels includes:

[0022] Obtaining a signal-to-noise ratio of the sub-channel according to the approximate Bhattacharyya parameter of the sub-channel;

[0023] Obtaining a channel capacity of the subchannel according to the signal-to-noise ratio of the subchannel;

[0024] According to the channel capacity of each of the subchannels, the sum of the channel capacities of all the subchannels of the subcarrier is obtained.

[0025] Optionally, obtaining the coding rate corresponding to each of the subcarriers by a coding allocation algorithm according to the total channel capacity and the block coding rate includes:

[0026] S41: Obtaining a total number of information bits according to a code length of the polarization code, a wave number of the subcarrier, and the block coding rate;

[0027] S42: Setting the lower limit of the capacity of the polarization subchannel;

[0028] S43: Acquire the number of polarization subchannels whose unallocated capacity is greater than the capacity lower limit among all the subcarriers;

[0029] S44: Determine the relationship between the total number of information bits and the number of polarization sub-channels;

[0030] S441: When the total number of information bits is less than or equal to the number of polarization subchannels, evenly distribute the total number of information bits to all the subcarriers to obtain coding rates corresponding to the subcarriers.

[0031] Optionally, the obtaining, according to the total channel capacity and the block coding rate, a coding rate corresponding to each subcarrier through a coding allocation algorithm, further includes:

[0032] S442: When the total number of information bits is greater than the number of polarization subchannels, allocating the total number of information bits to all polarization subchannels according to the number of polarization subchannels, and obtaining a remaining number of information bits;

[0033] S433: reducing the capacity lower limit according to a preset capacity change value, and repeating S43 to S44 until the total number of information bits is less than or equal to the number of polarization subchannels.

[0034] Optionally, obtaining the number of information bits of the subcarrier according to the coding rate corresponding to the subcarrier and the code length of the polarization code includes:

[0035] The number of information bits that need to be placed in the subcarrier is obtained according to a product of the coding rate corresponding to the subcarrier and a code length of the polarization code.

[0036] Optionally, obtaining the subchannel for placing the information bits and the subchannel for placing the frozen bits according to the approximate Bhattacharyya parameter of the subchannel of the subcarrier and the number of information bits of the subcarrier includes:

[0037] Obtaining a subchannel ordering of each of the subcarriers according to the approximate Bhattacharyya parameters of the subchannels;

[0038] Selecting the subchannel for placing the information bits from the subchannel sorting according to the number of the information bits;

[0039] The remaining sub-channels in the sub-carrier are used as the sub-channels for placing the frozen bits.

[0040] Optionally, obtaining a subchannel ordering of each of the subcarriers according to the approximate Bhattacharyya parameters of the subchannels includes:

[0041] The subchannel sorting of the subcarriers is obtained by sorting the subchannels from low to high according to the approximate Bhattacharyya parameters of the subchannels.

[0042] The present invention also provides a polarization code construction system based on an underwater acoustic channel, characterized in that it includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned polarization code construction method based on the underwater acoustic channel is implemented.

[0043] The polarization code construction method and system based on the underwater acoustic channel of the present invention obtains the approximate Bhattacharyya parameters of all subchannels of each subcarrier on the basis of Monte Carlo experiments, and combines the wave number of the subcarrier in the frequency domain of the underwater acoustic channel and the block coding rate, and independently allocates the coding rate of the subcarrier through a coding allocation algorithm to ensure that the total block coding rate remains unchanged. By optimizing the coding rate of each subcarrier, a high-capacity polarization subchannel is selected as the information bit, and the specific characteristics of the underwater acoustic channel are more accurately adapted to maximize the use of high-capacity polarization subchannels to transmit information bits. According to the coding rate of each subcarrier and the code length of the polarization code, the number of information bits of the subcarrier is determined, and then according to the approximate Bhattacharyya parameters of the subchannel and the number of information bits, a high-capacity polarization subchannel is selected as the information bit transmission channel, and the rest are used as frozen bit placement channels to ensure that the information bits are transmitted through the most reliable subchannel, greatly reducing the bit error rate, thereby improving the efficiency and quality of signal transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is one of the flow charts of the method for constructing polarization codes based on an underwater acoustic channel of the present invention;

[0045] Figure 2Graph showing simulation results of the polarization code construction method based on an underwater acoustic channel of the present invention;

[0046] Figure 3 This is the second flowchart of the method for constructing polarization codes based on an underwater acoustic channel of the present invention. DETAILED DESCRIPTION

[0047] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0048] First, combining Figure 1 As shown, the present invention provides a polarization code construction method based on an underwater acoustic channel, comprising:

[0049] Obtain the preset number of experiments of the Monte Carlo experiment, the code length of the polarization code, the wave number of subcarriers in the frequency domain of the underwater acoustic channel, and the block coding rate.

[0050] Specifically, the preset number of experiments of the Monte Carlo experiment is the total number of Monte Carlo simulations, wherein the more Monte Carlo experiments the more accurate the number theoretically is, the preset number of experiments should be greater than 100 times, and a suitable value is selected according to the application situation. The code length of the polarization code refers to the length of the codeword, which is usually represented by n, where the code length n must be an integer power of 2. The wave number of the subcarrier in the frequency domain of the underwater acoustic channel refers to the number of subcarriers divided in the frequency domain, which is usually represented by N. The block coding rate refers to the ratio of the number of information bits contained in each codeword to the total length of the codeword in the communication system. In a preferred embodiment of the present invention, the preset number of experiments is 200 times, the code length of the polarization code is 256, the block coding rate is 0.5, the OFDM system has 256 subcarriers, the OFDM symbol duration is 20ms, and the frequency band range is 8000Hz-20750Hz.

[0051] According to the preset number of experiments, the code length of the polarization code, and the wave number of the subcarrier, a Monte Carlo experiment is performed to obtain approximate Bhattacharyya parameters of all subchannels of each of the subcarriers.

[0052] Specifically, the Monte Carlo experiment is used to simulate the channel of the signal mapped to the subcarrier, which includes factors such as channel attenuation and noise. The simulated channel should be able to reflect the physical characteristics of the real communication environment. By analyzing the difference between the received signal and the transmitted signal, the Bhattacharyya parameters of the signal on the subcarrier channel are calculated. Through a large number of experiments, sufficient data is obtained for statistical analysis to calculate the approximate Bhattacharyya parameters of all subchannels on each subcarrier.

[0053] The sum of the channel capacities of the subcarriers is obtained according to the approximate Bhattacharyya parameters of all the subchannels.

[0054] Specifically, for each subchannel, the corresponding signal-to-noise ratio or error rate is estimated using its Bhattacharyya parameter, and then the channel capacity of each subchannel is calculated based on the signal-to-noise ratio or error rate. For different types of channels, different mapping relationships are used to estimate the signal-to-noise ratio, and then the channel capacities of all subchannels are accumulated to obtain the total channel capacity of the subcarriers.

[0055] According to the total channel capacity and the block coding rate, the coding rate corresponding to each subcarrier is obtained through a coding allocation algorithm; wherein, after the coding rate corresponding to each subcarrier is obtained, the block coding rate remains unchanged, and the unchanged block coding rate ensures the stability of the overall communication system performance. It ensures that although the channel conditions and coding rates of a single subcarrier may change, the overall communication quality and efficiency remain stable, which helps to simplify system design and achieve transparency in information transmission.

[0056] Specifically, the coding rate of each subcarrier is allocated through the coding allocation algorithm so that the sum of the coding rates of each subcarrier is equal to the block coding rate, and the channel capacity of each subcarrier is taken into account to optimize the data transmission efficiency. Each subcarrier is allocated a suitable coding rate according to its channel capacity, thereby optimizing the performance of the entire communication system while satisfying the total coding rate constraint.

[0057] The number of information bits of the subcarrier is obtained according to the coding rate corresponding to the subcarrier and the code length of the polarization code.

[0058] Specifically, the coding rate is the ratio of the number of information bits to the total number of bits after coding, while the code length of the polar code directly reflects the total number of bits after coding. With these two parameters, the number of information bits on each subcarrier can be directly calculated. By assigning different coding rates to different subcarriers and calculating the number of information bits accordingly, system designers can optimize resource allocation and improve the efficiency and reliability of data transmission.

[0059] According to the approximate Bhattacharyya parameter of the subchannel of the subcarrier and the number of information bits of the subcarrier, a subchannel for placing the information bits and a subchannel for placing frozen bits are obtained.

[0060] Specifically, in a preferred embodiment of the present invention, all subchannels can be sorted according to the Bhattacharyya parameter of each subchannel, wherein the purpose of sorting is to arrange the channels from high to low reliability so as to select the most reliable subchannel to place the information bit. According to the coding rate of the subcarrier and the code length of the polarization code, the number of information bits on the subcarrier is calculated to determine how many subchannels are needed to place the information bits. From the sorted list, a certain number of subchannels at the top are selected as subchannels carrying information bits, and the remaining subchannels in the list (i.e., the latter part in this embodiment) are used to place frozen bits. This effectively improves the performance of the polarization code coding system, especially in subchannels with different signal-to-noise ratios, by intelligently allocating information bits and frozen bits, which greatly improves the reliability and efficiency of communication.

[0061] For example, the present invention conducts a communication simulation experiment under the condition of a strong multipath underwater acoustic time-varying channel (a shallow sea horizontal 1000-meter channel). Figure 2 As shown in the simulation result diagram, the solid line represents the coding modulation of the present invention, and the dotted line represents the existing Monte Carlo method. Compared with the two different methods, the method proposed by the present invention achieves a gain of nearly 3dB.

[0062] The polarization code construction method and system based on the underwater acoustic channel of the present invention obtains the approximate Bhattacharyya parameters of all subchannels of each subcarrier on the basis of Monte Carlo experiments, and combines the wave number of the subcarrier in the frequency domain of the underwater acoustic channel and the block coding rate, and independently allocates the coding rate of the subcarrier through a coding allocation algorithm to ensure that the total block coding rate remains unchanged. By optimizing the coding rate of each subcarrier, a high-capacity polarization subchannel is selected as the information bit, and the specific characteristics of the underwater acoustic channel are more accurately adapted to maximize the use of high-capacity polarization subchannels to transmit information bits. According to the coding rate of each subcarrier and the code length of the polarization code, the number of information bits of the subcarrier is determined, and then according to the approximate Bhattacharyya parameters of the subchannel and the number of information bits, a high-capacity polarization subchannel is selected as the information bit transmission channel, and the rest are used as frozen bit placement channels to ensure that the information bits are transmitted through the most reliable subchannel, greatly reducing the bit error rate, thereby improving the efficiency and quality of signal transmission.

[0063] Optionally, the performing a Monte Carlo experiment to obtain approximate Bhattacharyya parameters of all subchannels of each of the subcarriers according to the preset number of experiments, the code length of the polarization code, and the wave number of the subcarrier includes:

[0064] generating a binary random sequence according to the code length of the polar code and the wave number of the subcarrier, wherein the number of the binary random sequences is the wave number of the subcarrier, and the length of the binary random sequence is the code length of the polar code;

[0065] Performing interleaving processing according to a binary random sequence, distributing the polarization code along the time domain and performing OFDM modulation, obtaining a receiving sequence with the same number as the wave number of the subcarrier, decoding the subcarrier to obtain a decoding result vector, and increasing the number of experiments by one time;

[0066] When the number of experiments reaches the preset number of experiments, the Monte Carlo experiment is judged to be completed, and the approximate Bhattacharyya parameters of all subchannels of each subcarrier are obtained based on the received sequence and the decoding result vector of the subcarrier obtained in each experiment.

[0067] Specifically, for each subcarrier, a binary random sequence is generated according to the code length of the polarization code. For example, if the wave number of the subcarrier is K, K such sequences need to be generated. The generated binary random sequence is interleaved to enhance the robustness of the system to channel fading and interference. The interleaved data is then OFDM modulated to distribute the signal in the frequency domain. The modulated data on each subcarrier will constitute a receiving sequence. The received sequence obtains a decoding result vector through a decoder. Each OFDM modulation and decoding operation is recorded as an experiment. When the number of experiments reaches a preset value, the experiment is terminated. Using the received sequence and decoding result vector obtained from each experiment, the error rate of each subchannel is calculated by comparing the original sequence and the decoded sequence, and the approximate Bhattacharyya parameters of each subchannel are further calculated. The Bhattacharyya parameters are a function of the error probability and can be used to estimate the reliability of the subchannel. In a preferred embodiment of the present invention, S binary random sequences of length N are generated, which can be expressed as: It should be emphasized that the polarization code is distributed along the time domain so that the code words of the polarization code are sent one by one in time sequence, which requires the polarization code to be distributed along the time domain.

[0068] In this embodiment, the performance of polar codes in an OFDM system can be effectively simulated, providing a theoretical basis and reference data for system design and optimization.

[0069] Optionally, obtaining the approximate Bhattacharyya parameters of all subchannels of each subcarrier according to the decoding result vector of the received sequence and the subcarrier obtained in each experiment includes:

[0070] According to the received sequence obtained in each experiment and the decoding result vector of the subcarrier, the approximate Bhattacharyya parameters of all subchannels of each subcarrier are obtained by using the approximate Bhattacharyya parameter formula;

[0071] The approximate Bhattacharyya parameter formula is:

[0072]

[0073] in, is the decoding result vector of the subcarrier, U i is the i-th value of the decoding result vector, is the received sequence, is the probability of satisfying the condition in brackets in the i-th subchannel of the polar code with the code length N.

[0074] Specifically, for each Monte Carlo experiment, the transmitted binary random sequence (decoding result vector) and the corresponding received sequence are recorded. For each subchannel, the conditional probability of receiving the sequence when a specific bit value is transmitted is calculated based on the experimental data. Using the above formula, the approximate Bhattacharyya parameter is calculated for each subchannel, where the subchannel with a smaller parameter value is considered more reliable and suitable for transmitting information bits; while the subchannel with a larger parameter value is considered unreliable and suitable for carrying frozen bits.

[0075] In this embodiment, the approximate Bhattacharyya parameters of all sub-channels are calculated, and based on the results of a large number of Monte Carlo experiments, the reliability of each polarization channel is evaluated, and the codeword construction is optimized accordingly to improve the overall reliability and efficiency of communication.

[0076] Optionally, obtaining the sum of the channel capacities of the subcarriers according to the approximate Bhattacharyya parameters of all the subchannels includes:

[0077] Obtaining a signal-to-noise ratio of the sub-channel according to the approximate Bhattacharyya parameter of the sub-channel;

[0078] Obtaining a channel capacity of the subchannel according to the signal-to-noise ratio of the subchannel;

[0079] According to the channel capacity of each of the subchannels, the sum of the channel capacities of all the subchannels of the subcarrier is obtained.

[0080] Specifically, after obtaining the signal-to-noise ratio of each subchannel, the channel capacity formula is used to calculate the channel capacity of each subchannel. For a given signal-to-noise ratio, under a certain bandwidth, the channel capacity of the subchannel can be obtained through the channel capacity formula. If analyzed in an OFDM system, it may be the bandwidth of the subcarrier; finally, the channel capacities of all subchannels are summed to obtain the total channel capacity of the subcarrier.

[0081] In this embodiment, by calculating the sum of channel capacities, the sum of channel capacities of subcarriers under given polarization codes and OFDM parameters can be more accurately evaluated, thereby providing an important theoretical basis for system design and optimization.

[0082] Optionally, obtaining the coding rate corresponding to each of the subcarriers by a coding allocation algorithm according to the total channel capacity and the block coding rate includes:

[0083] S41: Obtaining a total number of information bits according to a code length of the polarization code, a wave number of the subcarrier, and the block coding rate;

[0084] S42: Setting the lower limit of the capacity of the polarization subchannel;

[0085] S43: Acquire the number of polarization subchannels whose unallocated capacity is greater than the capacity lower limit among all the subcarriers;

[0086] S44: Determine the relationship between the total number of information bits and the number of polarization sub-channels;

[0087] S441: When the total number of information bits is less than or equal to the number of polarization subchannels, evenly distribute the total number of information bits to all the subcarriers to obtain coding rates corresponding to the subcarriers.

[0088] Specifically, combined Figure 3 As shown, the total number of information bits is obtained according to the code length of the polarization code, the wave number of the subcarrier, and the block coding rate. By setting a lower limit on the capacity of a polarization subchannel, relatively more reliable subchannels can be identified, whose capacities are higher than this lower limit and are therefore suitable for transmitting information bits. This step is to ensure that the information bits are given adequate protection by selecting high-capacity subchannels. Afterwards, the system calculates the number of all unallocated polarization subchannels whose capacities are greater than this lower limit, ensuring the efficiency and practicality of the coding allocation strategy. When the total number of information bits is less than or equal to the number of high-capacity subchannels screened out, it means that there are enough subchannels to allocate all information bits. At this point, the information bits will be evenly distributed to all these subcarriers to obtain the coding rate corresponding to each subcarrier.

[0089] In a preferred embodiment of the present invention, the code length N of the polarization code is set to 256, the wave number S of the subcarrier is set to 256, the block coding rate R is set to 0.5, the initial value L of the lower limit of the capacity of the polarization subchannel is 0.9, the total number of information bits M=N×S×R, and the number of polarization subchannels whose unallocated capacity in all subcarriers is greater than the lower limit of the capacity is C.

[0090] In this embodiment, by setting the capacity lower limit and allocating information bits on demand, not only can the allocation of information bits be adjusted according to actual conditions, but the load between subcarriers can also be effectively balanced, ensuring the robustness and performance of the communication system under various channel conditions.

[0091] Optionally, the obtaining, according to the total channel capacity and the block coding rate, a coding rate corresponding to each subcarrier through a coding allocation algorithm, further includes:

[0092] S442: When the total number of information bits is greater than the number of polarization subchannels, allocating the total number of information bits to all polarization subchannels according to the number of polarization subchannels, and obtaining a remaining number of information bits;

[0093] S433: reducing the capacity lower limit according to a preset capacity change value, and repeating S43 to S44 until the total number of information bits is less than or equal to the number of polarization subchannels.

[0094] Specifically, combined Figure 3 As shown, in the coding allocation process, when the total number of information bits is greater than the number of available high-capacity polarization subchannels (step S442), the situation becomes more complicated; at this time, the system needs to allocate information bits in all the screened polarization subchannels until the capacity of all polarization subchannels is fully utilized, but some information bits may not be able to find suitable subchannels in this round of allocation; therefore, in this embodiment, step S433 introduces an iterative mechanism that gradually reduces the capacity lower limit so as to find opportunities to allocate information bits in polarization subchannels with lower capacity. This process is repeated until all information bits are successfully allocated to the corresponding subchannels. In this way, the system not only allocates information bits to the most reliable subchannels, but also dynamically adjusts the allocation strategy according to the preset capacity change value to cope with the situation where the total number of information bits exceeds the number of high-capacity subchannels. This dynamic adjustment process ensures that information bits can be allocated in subchannels of different capacity levels, making maximum use of all available channel resources.

[0095] In a preferred embodiment of the present invention, the code length N of the polarization code is set to 256, the wave number S of the subcarrier is set to 256, the block coding rate R is set to 0.5, and the initial value L of the lower limit of the capacity of the polarization subchannel is 0.9. The preset capacity is 0.1, wherein the lower limit of the capacity is reduced to 0.8 according to the preset capacity change value, and the total number of information bits is allocated to all polarization subchannels according to the number of polarization subchannels, and the remaining number of information bits is obtained, wherein the remaining number can be understood as MC.

[0096] In this embodiment, when the information load exceeds the optimal channel resources, the above iterative allocation process ensures that the system can find additional allocation solutions in a dynamic and adaptive manner to meet the coding requirements.

[0097] Optionally, obtaining the subchannel for placing the information bits and the subchannel for placing the frozen bits according to the approximate Bhattacharyya parameter of the subchannel of the subcarrier and the number of information bits of the subcarrier includes:

[0098] Obtaining a subchannel ordering of each of the subcarriers according to the approximate Bhattacharyya parameters of the subchannels;

[0099] Selecting the subchannel for placing the information bits from the subchannel sorting according to the number of the information bits;

[0100] The remaining sub-channels in the sub-carrier are used as the sub-channels for placing the frozen bits.

[0101] Specifically, first, by evaluating the approximate Bhattacharyya parameters of each subchannel, all subchannels of the subcarrier can be sorted. Subchannels with lower Bhattacharyya parameters have higher reliability and are therefore more suitable for transmitting information bits. This sorting process ensures that information bits are preferentially allocated to the most reliable subchannels based on the reliability of the subchannels. Subsequently, based on the given number of information bits, the top subchannels are sequentially selected from the sorted subchannel list for placing information bits, which ensures that the channel where the information bits are located has the best channel quality. Finally, the remaining subchannels in the list are designated as locations for placing frozen bits, which are usually channels with lower reliability.

[0102] In a preferred embodiment of the present invention, if there are 3 subcarriers, the corresponding coding rates are 0.25, 0.5, and 0.75 respectively, and the code length is 256, then the number of information bits of the 3 subcarriers is; 64, 128, and 192; the Bhattacharyya parameter of each subchannel of each subcarrier has been calculated by the previous Monte Carlo experiment, and the subchannels are sorted from low to high according to the Bhattacharyya parameter value on each subcarrier; for each subcarrier, the corresponding number of subchannels ranked at the top in the sorting result are selected to place information bits, and the remaining subchannels are placed in frozen bits, then the first 64, first 128, and first 192 subchannels of the 3 subcarriers are selected to place information bits, and the remaining subchannels are placed in frozen bits.

[0103] In this embodiment, all sub-channels of the sub-carrier are sorted to ensure that sub-channels with high reliability are used to transmit key information, thereby reducing the overall error rate and improving the transmission quality.

[0104] Optionally, obtaining a subchannel ordering of each of the subcarriers according to the approximate Bhattacharyya parameters of the subchannels includes:

[0105] The subchannel sorting of the subcarriers is obtained by sorting the subchannels from low to high according to the approximate Bhattacharyya parameters of the subchannels.

[0106] Specifically, sorting the subchannels on the subcarrier using the approximate Bhattacharyya parameters of the subchannels is a key optimization step. The Bhattacharyya parameter is an indicator of channel reliability, where a lower Bhattacharyya parameter means a higher channel reliability. By sorting the subchannels from low to high according to the size of the Bhattacharyya parameter, it is possible to clearly distinguish which subchannels are more reliable and which are relatively poor.

[0107] In this embodiment, the subchannels on the subcarrier are sorted using the approximate Bhattacharyya parameters of the subchannels, which provides an important decision basis for subsequent coding allocation, distribution of information bits and frozen bits, and ensures that information bits can be preferentially allocated to the most reliable subchannels, thereby maximizing the reliability and efficiency of communication.

[0108] The present invention also provides a polarization code construction system based on an underwater acoustic channel, characterized in that it includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned polarization code construction method based on the underwater acoustic channel is implemented.

[0109] The polarization code construction system based on the underwater acoustic channel of the present invention obtains the approximate Bhattacharyya parameters of all subchannels of each subcarrier on the basis of Monte Carlo experiments, and independently allocates the coding rate of the subcarrier through a coding allocation algorithm in combination with the wave number of the subcarrier in the frequency domain of the underwater acoustic channel and the block coding rate, so as to ensure that the total block coding rate remains unchanged, and selects a high-capacity polarization subchannel as the information bit by optimizing the coding rate of each subcarrier, more accurately adapts to the specific characteristics of the underwater acoustic channel, and maximizes the use of the high-capacity polarization subchannel to transmit information bits. According to the coding rate of each subcarrier and the code length of the polarization code, the number of information bits of the subcarrier is determined, and then according to the approximate Bhattacharyya parameters of the subchannel and the number of information bits, the high-capacity polarization subchannel is selected as the information bit transmission channel, and the rest are used as the placement channels of frozen bits, so as to ensure that the information bits are transmitted through the most reliable subchannel, greatly reduce the bit error rate, and thus improve the efficiency and quality of signal transmission.

[0110] It should be noted that, in this article, relational terms such as "first" and "second" are only used 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 "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0111] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those 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 invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A polarization code construction method based on an underwater acoustic channel, characterized in that: include: Obtaining the preset number of experiments of the Monte Carlo experiment, the code length of the polarization code, the wave number of subcarriers in the frequency domain of the underwater acoustic channel, and the block coding rate; According to the preset number of experiments, the code length of the polarization code, and the wave number of the subcarrier, a Monte Carlo experiment is performed to obtain approximate Bhattacharyya parameters of all subchannels of each of the subcarriers; specifically comprising: generating a binary random sequence according to the code length of the polarization code and the wave number of the subcarrier, wherein the number of the binary random sequences is the wave number of the subcarrier, and the length of the binary random sequence is the code length of the polarization code; Performing interleaving processing according to a binary random sequence, distributing the polarization code along the time domain and performing OFDM modulation, obtaining a receiving sequence with the same number as the wave number of the subcarrier, decoding the subcarrier to obtain a decoding result vector, and increasing the number of experiments by one time; When the number of experiments reaches the preset number of experiments, the Monte Carlo experiment is judged to be completed, and the approximate Bhattacharyya parameters of all subchannels of each subcarrier are obtained according to the received sequence and the decoding result vector of the subcarrier obtained in each experiment; Wherein, the approximate Bhattacharyya parameter formula is: in, is the first to i-1th values ​​of the decoding result vector of the subcarrier, U i is the i-th value of the decoding result vector, is the received sequence, is the probability of satisfying the condition in brackets in the i-th subchannel of the polar code with the code length N; According to the approximate Bhattacharyya parameters of all the sub-channels, the sum of the channel capacities of the sub-carriers is obtained; specifically including: according to the approximate Bhattacharyya parameters of the sub-channels, the signal-to-noise ratio of the sub-channels is obtained; Obtaining a channel capacity of the subchannel according to the signal-to-noise ratio of the subchannel; According to the channel capacity of each of the subchannels, obtaining the sum of the channel capacities of all the subchannels of the subcarrier; According to the total channel capacity and the block coding rate, a coding rate corresponding to each of the subcarriers is obtained through a coding allocation algorithm; wherein after the coding rate corresponding to each of the subcarriers is obtained, the block coding rate remains unchanged; Obtaining the number of information bits of the subcarrier according to the coding rate corresponding to the subcarrier and the code length of the polarization code; including: obtaining the number of information bits that need to be placed in the subcarrier according to the product of the coding rate corresponding to the subcarrier and the code length of the polarization code, Obtaining, according to the approximate Bhattacharyya parameter of the subchannel of the subcarrier and the number of information bits of the subcarrier, a subchannel for placing the information bits and a subchannel for placing frozen bits, specifically includes: According to the approximate Bhattacharyya parameters of the subchannels, obtaining the subchannel ordering of each of the subcarriers; specifically comprising: sorting the subchannels from low to high according to the approximate Bhattacharyya parameters of the subchannels to obtain the subchannel ordering of the subcarriers; Selecting the subchannel for placing the information bits from the subchannel sorting according to the number of the information bits; And the remaining sub-channels in the sub-carrier are used as the placed sub-channels.

2. A polarization code construction system based on an underwater acoustic channel, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the polarization code construction method based on the underwater acoustic channel according to claim 1 is implemented.

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