Chaotic orthogonal dft-spread multi-layer check serial cancellation list decoding method

Abstract

The application relates to the field of computer communication technology, in particular to a chaotic orthogonal pilot multi-layer check serial cancellation list decoding method, which comprises an encoding process and a decoding process; the encoding process comprises the following steps: step S11, dividing a message sequence with a length of K to be sent into M groups of message submodules evenly; step S12, generating corresponding CRC check codes for each group of message submodules and sequentially splicing the CRC check codes into total CRC check codes; step S13, normalizing the total CRC check codes and obtaining a chaotic initial value g(0), generating corresponding chaotic spread spectrum sequences through the chaotic initial value g(0); step S14, converting the message sequence with the length of K to be sent into a source sequence with a length of N; and step S15, performing polar code encoding on the source sequence with the length of N; the application can reduce a large number of storage units required by CA-SCL, reduce the average decoding time delay, and improve the frequency band utilization rate of communication.

Description

Technical Field

[0001] This invention relates to the field of computer communication technology, and in particular to a chaotic orthogonal pilot multilayer check serial cancellation list decoding method. Background Technology

[0002] The complexity of wireless channels, primarily due to strong multipath effects causing selective fading in the frequency domain and Doppler shift leading to carrier tracking errors, necessitates a higher signal-to-noise ratio (SNR) for wireless multipath communication to achieve the same communication performance compared to ordinary white Gaussian noise channels. Employing appropriate channel coding methods can effectively improve system performance and enhance communication reliability. Commonly used channel coding schemes include Turbo codes, Low-Density Parity Check (LDPC) codes, convolutional codes, and RS codes. Among these, LDPC codes exhibit good performance when using soft-decision decoding methods with near-infinite codeword lengths. However, compared to Shannon's theoretical value, there is still a gap of approximately 0.0045 dB. Polar codes were proposed by Arikan in 2009 using channel polarization theory. Because they are 1) linear block codes with lower encoding and decoding complexity; and 2) can achieve Shannon limit performance in binary input discrete memoryless channels (BDMCs), they have attracted a lot of attention from scholars.

[0003] With the popularity of polar codes, their decoding methods have attracted much attention from scholars. Arikan proposed the Successive Cancellation (SC) decoding method, which is a classic decoding method. Although the SC decoding algorithm can achieve a low computational complexity of O(NlogN), it is susceptible to error propagation because each decoding operation depends on the information from the previous decoding, leading to a decrease in decoding performance, especially when the code length is small. Cyclic Redundancy Check Aided Successive Cancellation List (CA-SCL) decoding can achieve almost the same performance as Turbo codes and LDPC codes, or even better, but its storage space and decoding delay increase with the size of the list L. The source vector structure of CA-SCL is as follows: Figure 1 As shown, the information module is verified, and the resulting CRC checksum is placed after the information module. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a chaotic orthogonal pilot multilayer check serial cancellation list decoding method, which can reduce the large number of storage units required by CA-SCL, reduce the average decoding delay, and improve the bandwidth utilization of communication.

[0005] This invention is achieved using the following technical solution: a chaotic orthogonal pilot multilayer check serial cancellation list decoding method, comprising an encoding process and a decoding process;

[0006] The encoding process includes the following steps:

[0007] Step S11: Divide the message sequence of length K to be sent into M message sub-modules;

[0008] Step S12: Each message submodule generates a corresponding CRC checksum and concatenates them sequentially to form the total CRC checksum.

[0009] Step S13: Normalize the total CRC checksum and obtain the initial chaotic value g(0), and generate the corresponding chaotic spread spectrum sequence using the initial chaotic value g(0);

[0010] Step S14: Convert the message sequence of length K to be sent into a source sequence of length N;

[0011] Step S15: Encode the source sequence of length N using polar codes;

[0012] Step S16: Place the chaotic spread spectrum sequence generated in step S13 onto the pilot of OFDM, and place the polar code on the data position of OFDM, perform OFDM modulation processing, and finally generate the signal to be transmitted.

[0013] The decoding process includes the following steps:

[0014] Step S21: Perform OFDM demodulation on the signal obtained in step S16 to obtain frequency domain information, and perform equalization on the frequency domain information to obtain equalized frequency domain information.

[0015] Step S22: Despread the equalized frequency domain information by chaotic spreading to obtain the corresponding CRC check code for each message submodule.

[0016] Step S23: Decode the equalized frequency domain information using CA-SCL to obtain L candidate sequences of the message submodule and the value of the path metric PM.

[0017] Step S24: Perform CRC verification on the L candidate sequences of the message sub-modules obtained in step S23 using the CRC check codes corresponding to each group of message sub-modules obtained in step S22.

[0018] Step S25: Select the message sub-module with the smallest path metric PM from the message sub-modules that meet the CRC check and make them the surviving message sub-modules;

[0019] Step S26: The surviving message submodule participates in the next round of CA-SCL decoding. After all CRC check codes are successfully verified, the final surviving message submodule, i.e. the final decoding result, will be obtained.

[0020] Preferably, step S12 is further specified as follows: each group of message submodules generates a corresponding binary CRC check code, and then each binary CRC check code is concatenated into a total binary CRC check code in sequence.

[0021] Step S13 is further specified as follows: converting the total binary CRC check code into the total decimal CRC check code, normalizing the total decimal CRC check code and obtaining the initial chaotic value g(0), and generating the corresponding chaotic spread spectrum sequence through the initial chaotic value g(0).

[0022] Preferably, step S13 further comprises: generating a corresponding chaotic spreading sequence from the initial chaotic value g(0) using the following formula:

[0023] g(m+1), P-Qg 2 (m),

[0024] Where P and Q are the parameters for generating the chaotic spread spectrum sequence, and g(m) is an element of the chaotic spread spectrum sequence.

[0025] m takes values ​​of 0, 1, 2, 3, 4, ..., A, where A is the length of the chaotic spreading sequence. P and Q are set parameters. Substituting the initial chaotic value g(0) into the formula, we can recursively obtain:

[0026] g(1)=P-Qg 2 (0)

[0027] g(2)=P-Qg 2 (1)

[0028] g(3)=P-Qg 2 (2)

[0029] …

[0030] g(A) = P - Qg 2 (A-1)

[0031] A chaotic spread spectrum sequence of length A can be obtained by recursion.

[0032] Preferably, step S14 is further specifically: channel reliability estimation is performed by Gaussian construction method, the message sequence is placed on a reliable channel, and binary 0 is placed on an unreliable channel, thereby transforming it into a source sequence of length N.

[0033] Preferably, step S21 is further specified as follows: by correlating the local LFM signal at the receiving end with the received LFM signal, the time-domain channel estimate can be obtained; by Fourier transform, the frequency-domain channel can be obtained; the signal obtained in step S16 is subjected to OFDM demodulation processing to obtain frequency-domain information; and the frequency-domain channel and frequency-domain information are equalized to obtain the equalized frequency-domain information.

[0034] Preferably, step S22 is further specified as follows: the equalized frequency domain information is despread by chaotic spreading to obtain the chaotic spreading sequence, and the CRC check code of each message submodule can be obtained by using the inverse process of the encoding process.

[0035] The beneficial effects of this invention are:

[0036] This invention can reduce the large number of storage units required by CA-SCL, reduce the average decoding latency, and improve the bandwidth utilization of communication. Attached Figure Description

[0037] Figure 1 This is a diagram of the CA-SCL source vector structure.

[0038] Figure 2 It is the correlation coefficient of the CPM spread spectrum sequence with a length N of 32.

[0039] Figure 3 It is the correlation coefficient of the CPM spread spectrum sequence with a length N of 64.

[0040] Figure 4 It is the correlation coefficient of the CPM spread spectrum sequence with a length N of 128.

[0041] Figure 5 It is the correlation coefficient of the CPM spread spectrum sequence with a length N of 256.

[0042] Figure 6 This is a flowchart of the coding process.

[0043] Figure 7 This is a flowchart of the decoding process. Figure 8 This is a flowchart of an embodiment of the Survival Messages submodule. Detailed Implementation

[0044] The invention will now be further described with reference to the accompanying drawings.

[0045] Please see Figures 6 to 7 The present invention provides an embodiment: a chaotic orthogonal pilot multilayer check serial cancellation list decoding method, including an encoding process and a decoding process;

[0046] The encoding process includes the following steps:

[0047] Step S11: Divide the message sequence of length K to be sent into M message sub-modules;

[0048] Step S12: Each message submodule generates a corresponding CRC checksum and concatenates them sequentially to form the total CRC checksum.

[0049] Step S13: Normalize the total CRC checksum and obtain the initial chaotic value g(0), and generate the corresponding chaotic spread spectrum sequence using the initial chaotic value g(0);

[0050] Step S14: Convert the message sequence of length K to be sent into a source sequence of length N;

[0051] Step S15: Encode the source sequence of length N using polar codes;

[0052] Step S16: Place the chaotic spread spectrum sequence generated in step S13 onto the pilot of OFDM, and place the polar code on the data position of OFDM, perform OFDM modulation processing, and finally generate the signal to be transmitted.

[0053] The decoding process includes the following steps:

[0054] Step S21: Perform OFDM demodulation on the signal obtained in step S16 to obtain frequency domain information, and perform equalization on the frequency domain information to obtain equalized frequency domain information.

[0055] Step S22: Despread the equalized frequency domain information by chaotic spreading to obtain the corresponding CRC check code for each message submodule.

[0056] Step S23: Decode the equalized frequency domain information using CA-SCL to obtain L candidate sequences of the message submodule and the value of the path metric PM.

[0057] Step S24: Perform CRC verification on the L candidate sequences of the message sub-modules obtained in step S23 using the CRC check codes corresponding to each group of message sub-modules obtained in step S22.

[0058] Step S25: Select the message sub-module with the smallest path metric PM from the message sub-modules that meet the CRC check and make them the surviving message sub-modules;

[0059] Step S26: The surviving message submodule participates in the next round of CA-SCL decoding. After all CRC check codes are successfully verified, the final surviving message submodule, i.e. the final decoding result, will be obtained.

[0060] Step S12 is further specified as follows: each group of message submodules generates a corresponding binary CRC check code, and then each binary CRC check code is concatenated into a total binary CRC check code in sequence.

[0061] Step S13 is further specified as follows: converting the total binary CRC check code into the total decimal CRC check code, normalizing the total decimal CRC check code and obtaining the initial chaotic value g(0), and generating the corresponding chaotic spread spectrum sequence through the initial chaotic value g(0).

[0062] Step S13 is further specified as follows: the chaotic initial value g(0) is used to generate the corresponding chaotic spread spectrum sequence using the following formula:

[0063] g(m+1), P-Qg 2 (m),

[0064] Where P and Q are the parameters for generating the chaotic spread spectrum sequence, and g(m) is an element of the chaotic spread spectrum sequence.

[0065] m takes values ​​of 0, 1, 3, 4, ..., A, where A is the length of the chaotic spreading sequence. P and Q are set parameters. Substituting the initial chaotic value g(0) into the formula, we can recursively obtain:

[0066] g(1)=P-Qg 2 (0)

[0067] g(2)=P-Qg 2 (1)

[0068] g(3)=P-Qg 2 (2)

[0069] …

[0070] g(A) = P - Qg 2 (A-1)

[0071] A chaotic spread spectrum sequence of length A can be obtained by recursion.

[0072] Step S14 is further specified as follows: Channel reliability is estimated by using the Gaussian construction method, the message sequence is placed on a reliable channel, and binary 0s are placed on an unreliable channel, thereby transforming it into a source sequence of length N.

[0073] Step S21 is further specified as follows: by correlating the local LFM signal at the receiving end with the received LFM signal, the time-domain channel estimate can be obtained. The frequency-domain channel can be obtained by Fourier transform. The signal obtained in step S16 is subjected to OFDM demodulation processing to obtain frequency-domain information. The frequency-domain channel and frequency-domain information are equalized to obtain the equalized frequency-domain information.

[0074] Step S22 is further specified as follows: the chaotic spread spectrum is despread by the equalized frequency domain information to obtain the chaotic spread spectrum sequence, and the corresponding CRC check code of each message submodule can be obtained by using the inverse process of the encoding process.

[0075] The present invention will be further described below with reference to a specific embodiment:

[0076] A chaotic orthogonal pilot multilayer check serial cancellation list decoding method includes an encoding process and a decoding process;

[0077] The encoding process includes the following steps:

[0078] Step 11: Divide the message sequence of length K to be sent into M equal groups of message sub-modules;

[0079] Assuming the total length of the message sequence is 100 bits, and it is divided into 5 (the value of M) parts, then the length of each message sub-module is 20 bits.

[0080] Step 12: Each message submodule generates a corresponding CRC checksum and concatenates them sequentially to form the total CRC checksum.

[0081] Each message submodule generates a corresponding binary CRC checksum, and then each binary CRC checksum is concatenated into a total binary CRC checksum.

[0082] Generate a sub-CRC checksum for each message submodule. The checksum generation formula is not specifically defined here. Assuming the generated sub-CRC checksum is 2 binary bits, for example, 11, then the 5 sub-CRC checksums are concatenated sequentially to form the total checksum 1110001101 (the value here is just an example).

[0083] Step 13: Normalize the total CRC checksum and obtain the initial chaotic value g(0), and generate the corresponding chaotic spread spectrum sequence using the initial chaotic value g(0);

[0084] The total binary CRC checksum is converted into the total decimal CRC checksum. The total decimal CRC checksum is normalized and the initial chaotic value g(0) is obtained. The corresponding chaotic spread spectrum sequence is generated through the initial chaotic value g(0).

[0085] The chaotic initial value g(0) is used to generate the corresponding chaotic spread spectrum sequence using the following formula:

[0086] g(m+1), P-Qg 2 (m),

[0087] Where P and Q are the parameters for generating the chaotic spread spectrum sequence, and g(m) is an element of the chaotic spread spectrum sequence.

[0088] m takes values ​​of 0, 1, 2, 3, 4, ..., A, where A is the length of the chaotic spreading sequence. P and Q are set parameters. Substituting the initial chaotic value g(0) into the formula, we can recursively obtain:

[0089] g(1)=P-Qg 2 (0)

[0090] g(2)=P-Qg 2 (1)

[0091] g(3)=P-Qg 2 (2)

[0092] …

[0093] g(A) = P - Qg 2 (A-1)

[0094] A chaotic spread spectrum sequence of length A can be obtained by recursion.

[0095] Convert the binary total CRC checksum 1110001101 to decimal 909, then normalize the decimal total checksum to obtain the initial chaotic value g(0) = 909 / 1023*(1 / 2) = 0.444. Substitute these values ​​into the equation to obtain the chaotic sequence.

[0096] Let the chaotic spread spectrum generation parameters P and Q be 1 / 4 and 4, respectively. The generated example is as follows:

[0097] g(1) = 1 / 4 - 4*(0.444) 2

[0098] g(2) = 1 / 4 - 4*g 2 (1)

[0099] …

[0100] g(A) = P - Qg 2 (A-1)

[0101] Step 14: Convert the message sequence of length K to be sent into a source sequence of length N;

[0102] Channel reliability estimation is performed using the Gaussian construction method. The message sequence is placed on a reliable channel and binary 0s are placed on an unreliable channel, thus transforming it into a source sequence of length N.

[0103] Step 15: Encode the source sequence of length N using polar codes;

[0104] Step 16: Place the chaotic spread spectrum sequence generated in Step 13 onto the pilot of OFDM, and place the polar code on the data position of OFDM, perform OFDM modulation processing, and finally generate the signal to be transmitted.

[0105] The generated chaotic spread spectrum sequence is placed on the OFDM pilot. The polar code is placed in the data position. Finally, OFDM modulation is performed.

[0106] The decoding process includes the following steps:

[0107] Step 21: Perform OFDM demodulation on the signal obtained in step 16 to obtain frequency domain information, and perform equalization on the frequency domain information to obtain equalized frequency domain information.

[0108] By correlating the local LFM signal at the receiver with the received LFM signal, the time-domain channel estimate can be obtained. The frequency-domain channel can be obtained by Fourier transform. The signal obtained in step 16 is demodulated by OFDM to obtain frequency-domain information. The frequency-domain channel and frequency-domain information are then equalized to obtain the equalized frequency-domain information.

[0109] To reduce the impact of multiple channels on chaotic spread spectrum despreading, the frequency domain information needs to be pre-equalized using the channel obtained by LFM synchronization.

[0110] By adding an LFM signal before the main signal, signal synchronization (i.e., detecting when the signal arrives) is performed at the receiver. By correlating the local LFM signal at the receiver with the received LFM signal, the time-domain channel estimate can be obtained, and the frequency-domain channel can be obtained through Fourier transform.

[0111] The OFDM signal is demodulated to obtain frequency domain information. Equalization is then performed using the frequency domain channel and frequency domain information (there are many equalization methods, such as LS channel equalization and MMSE channel equalization).

[0112] Step 22: Despread the equalized frequency domain information using chaotic spread spectrum to obtain the corresponding CRC checksum for each message submodule.

[0113] By despreading the equalized frequency domain information using chaotic spread spectrum, a chaotic spread spectrum sequence can be obtained. By using the inverse process of the encoding process, the corresponding CRC check code for each message submodule can be obtained.

[0114] For the pre-equalized frequency domain information, the pilot signal is extracted at the corresponding position, which is the chaotic spread spectrum sequence sent by the transmitter.

[0115] Sub-check code acquisition method: The sending end performs chaotic spreading and despreading to obtain the chaotic spreading sequence. By using the reverse process of the encoding process, the binary CRC check code can be obtained, and then the sub-check code can be obtained.

[0116] Step 23: Decode the equalized frequency domain information using CA-SCL to obtain L candidate sequences of the message submodule and the value of the path metric PM;

[0117] The equalized frequency domain information is then subjected to CA-SCL decoding. At the transmitting end, the original information source is divided into M groups. When the receiving end decodes the first group of message submodules, it may decode L possible sequences.

[0118] Step 24: Perform CRC verification on the L candidate sequences of the message sub-modules obtained in Step 23 using the CRC check codes corresponding to each group of message sub-modules obtained in Step 22.

[0119] So how do we select the correct sequence? The selected sequence should meet the following conditions: 1. It meets the corresponding CRC check; 2. Among all the list message sequences, the path metric PM is the smallest. Here, the sub-CRC checksum obtained at the beginning comes in handy, and the path metric PM is a value given by CA-SCL, which is a well-known technique in this field.

[0120] Step 25: Select the message sub-module with the smallest path metric PM from the message sub-modules that meet the CRC check and make them the surviving message sub-modules;

[0121] Through the above filtering, the correct sub-module sequence can be selected from L candidate modules to become the surviving message sub-block.

[0122] Step 26: The surviving message submodule participates in the next round of CA-SCL decoding. After all CRC check codes are successfully verified, the final surviving message submodule, i.e. the final decoding result, will be obtained.

[0123] The surviving message sub-block will also participate in the decoding of the next sub-module.

[0124] like Figure 8 Taking the decoding of surviving message submodule 3 as an example, the implementation is as follows:

[0125] Step 1: CA-SCL Decoding First, decode the surviving message submodule 1.

[0126] Step 2: After the surviving message submodule 1 is decoded, it serves as the input for CA-SCL decoding.

[0127] Step 3: Decode the surviving message submodule 2 using CA-SCL.

[0128] Step 4: Surviving message submodules 1 and 2 also serve as inputs for CA-SCL decoding.

[0129] Step 5: CA-SCL decodes the surviving message submodule 3 based on the input.

[0130] …

[0131] Step N-1: Simultaneously use the surviving message submodules 1, 2, 3, ..., M-1 as inputs for CA-SCL decoding.

[0132] Step N: CA-SCL decodes the surviving message submodule M based on the input.

[0133] Step N+1: Surviving message submodules 1, 2, 3, ..., M are concatenated to form the final decoded sequence.

[0134] Storage space and decoding latency analysis:

[0135] The following analysis examines the storage units required for COPM-SCL decoding. Traditional CA-SCL decoding methods rely on a single CRC check, requiring K×L message bits to be stored across L paths before decoding K message bits. In contrast, the COPM-SCL method presented in this paper clears these storage units after decoding each message sub-block, performing the CRC check, and storing the selected sequence. New values ​​can then be written to these storage units in the next decoding process. The reduction in memory space is estimated below. Assuming the message sequence is divided into M sub-message modules, each with a length of K / M, then during SCL decoding, L paths require storing K / M×L message bits, and K storage units are needed to store the decoded message sequence. Therefore, the storage units required for COPM-SCL decoding are K / M×L+K. The storage unit ratio Rmem between COPM-SCL and CA-SCL decoders can be obtained:

[0136]

[0137] Secondly, COPM-SCL modulates the CRC checksum onto the OFDM pilot information using a chaotic spread spectrum sequence, thus improving bandwidth utilization.

[0138] Finally, we discuss the average delay of the output decoded bits for the two different schemes. Once the COPM-SCL decoder has completed decoding the message sub-block, it can output the sequence of that sub-block. We define the average decoding delay Td as follows:

[0139]

[0140] Where tdi is the decoding delay of the i-th sub-block. Clearly, the decoding delay is proportional to the decoding computational complexity; therefore, we only analyze the computational complexity of two different decoding schemes. For CA-SCL decoding with code length N and list size L, the computational complexity is O(LN logN), and the decoding delay can be expressed as:

[0141] T ds = c × L × N log N (2.24)

[0142] Where c is a constant factor. Dividing the information block into M equal segments, and neglecting the cost of CRC checking, the output delay of the i-th sub-block is:

[0143]

[0144] The average decoding latency of COPM-SCL can be expressed as follows:

[0145]

[0146] The average decoding latency ratio RT between the two decoding methods is:

[0147]

[0148] Table 2.1 shows the specific values ​​of the required storage unit ratio Rmem and the average decoding delay ratio RT under different parameters. It can be seen that, compared with the CA-SCL decoder, the proposed COPM-SCL decoding method reduces both the required storage unit and the decoding delay.

[0149] Table 2.1 Specific values ​​of Rmem and RT under different parameter conditions

[0150] Table 2.1 The specific values ​​of Rmem and RT under different parameters

[0151]

[0152] Chaotic phase modulation spread spectrum technology:

[0153] Traditional pseudo-random sequences, such as m-sequences and Gold sequences, have a limited number of codebooks, making it difficult to cover all sub-check codes. However, using chaotic sequences as spreading codes, the number of codebooks is not affected by the order of the spreading code, and a large number of well-correlated chaotic spreading sequences can be generated using different initial values.

[0154] Different mapping methods can obtain different types of chaotic sequences, and their correlation characteristics are also quite different. Commonly used chaotic sequence mappings include Quadratic mapping, Logistic mapping, Bernoulli mapping and Chebyshev mapping, etc. Combining the Quadratic mapping equation, the generation process of chaotic spread-spectrum sequences is introduced below:

[0155] g(m+1)=P-Qg 2 (m) (2.19)

[0156] where P and Q are generation parameters of the chaotic spread-spectrum sequence, and g(m) is an element of the chaotic spread-spectrum sequence.

[0157] When 3 / 4 < P*Q < 2, g(m)∈(-2 / Q,2 / Q). Therefore, let the values of the generation parameters P and Q of the chaotic spread-spectrum sequence be 1 / 4 and 4 respectively. Then g(m)∈(-2 / Q,2 / Q) can be obtained. Using the initial chaotic value g(0) and the above formula, a chaotic spread-spectrum sequence of length N can be generated as gN=(g(0),g(1),g(2),...,g(N-1)). By selecting K different initial chaotic values g(0), K mutually orthogonal chaotic spread-spectrum sequences can be generated, denoted as:

[0158]

[0159] It can be seen from the mapping equation of the chaotic sequence that the generated sequence is a real number sequence. In order to obtain a complex sequence, we map the generated sequence to the carrier phase again, thereby generating a Chaotic Phase Modulation (CPM) spread-spectrum code:

[0160] p N =exp(j2πg N ) (2.21)

[0161] where exp represents the exponential operation, and j is the imaginary unit,

[0162] Although the length N of the chaotic phase-modulated spread-spectrum sequence can take any value, different lengths will affect the orthogonality of the sequence. Generally speaking, the longer the sequence length, the better its orthogonality. The orthogonality of the sequences is evaluated by the correlation coefficient below.

[0163] Figures 2 to 5The correlation coefficients of CPM spread spectrum sequences are given for lengths N of 32, 64, 128, and 256, with a uniform codebook size K of 1024. In the figure, x = 0 represents the autocorrelation value of the CPM sequence, while x ≠ 0 represents the cross-correlation value. It can be seen that the cross-correlation between different CPM sequences gradually decreases with increasing codebook length. On the other hand, even with a large codebook size of 1024, different sequences still exhibit good autocorrelation and low cross-correlation at code lengths of 128 / 256.

[0164] In summary, this invention can reduce the large number of storage units required by CA-SCL, reduce the average decoding latency, and improve the bandwidth utilization of communication.

[0165] The above description is only a preferred embodiment of the present invention and should not be construed as a limitation of this application. All equivalent changes and modifications made in accordance with the scope of the patent application of the present invention should be covered by the present invention.

Claims

1. A chaotic orthogonal pilot multilayer check serial cancellation list decoding method, characterized in that: This includes both the encoding and decoding processes; The encoding process includes the following steps: Step S11: Divide the message sequence of length K to be sent into M message sub-modules; Step S12: Each message submodule generates a corresponding CRC checksum and concatenates them sequentially to form the total CRC checksum. Step S13: Normalize the total CRC checksum and obtain the initial chaotic value g(0), and generate the corresponding chaotic spread spectrum sequence using the initial chaotic value g(0); Step S14: Convert the message sequence of length K to be sent into a source sequence of length N; Step S15: Encode the source sequence of length N using polar codes; Step S16: Place the chaotic spread spectrum sequence generated in step S13 onto the pilot of OFDM, and place the polar code on the data position of OFDM, perform OFDM modulation processing, and finally generate the signal to be transmitted. The decoding process includes the following steps: Step S21: Perform OFDM demodulation on the signal obtained in step S16 to obtain frequency domain information, and perform equalization on the frequency domain information to obtain equalized frequency domain information. Step S22: Despread the equalized frequency domain information by chaotic spreading to obtain the corresponding CRC check code for each message submodule. Step S23: Decode the equalized frequency domain information using CA-SCL to obtain L candidate sequences of the message submodule and the value of the path metric PM. Step S24: Perform CRC verification on the L candidate sequences of the message sub-modules obtained in step S23 using the CRC check codes corresponding to each group of message sub-modules obtained in step S22. Step S25: Select the message sub-module with the smallest path metric PM from the message sub-modules that meet the CRC check and make them the surviving message sub-modules; Step S26: The surviving message submodule participates in the next round of CA-SCL decoding. After all CRC check codes are successfully verified, the final surviving message submodule, i.e. the final decoding result, will be obtained.

2. The chaotic orthogonal pilot multilayer check serial cancellation list decoding method according to claim 1, characterized in that: Step S12 is further specified as follows: each group of message submodules generates a corresponding binary CRC check code, and then each binary CRC check code is concatenated into a total binary CRC check code in sequence. Step S13 is further specified as follows: converting the total binary CRC check code into the total decimal CRC check code, normalizing the total decimal CRC check code and obtaining the initial chaotic value g(0), and generating the corresponding chaotic spread spectrum sequence through the initial chaotic value g(0).

3. The chaotic orthogonal pilot multilayer check serial cancellation list decoding method according to claim 1, characterized in that: Step S13 is further specified as follows: the chaotic initial value g(0) is used to generate the corresponding chaotic spread spectrum sequence using the following formula: ， Where P and Q are the parameters for generating the chaotic spread spectrum sequence, and g(m) is an element of the chaotic spread spectrum sequence. m takes values ​​of 0, 1, 2, 3, 4, ..., A, where A is the length of the chaotic spreading sequence. Substituting the initial chaotic value g(0) into the formula, we can recursively obtain: ； A chaotic spread spectrum sequence of length A can be obtained by recursion.

4. The chaotic orthogonal pilot multilayer check serial cancellation list decoding method according to claim 1, characterized in that: Step S14 is further specified as follows: Channel reliability is estimated by using the Gaussian construction method, the message sequence is placed on a reliable channel, and binary 0s are placed on an unreliable channel, thereby transforming it into a source sequence of length N.

5. The chaotic orthogonal pilot multilayer check serial cancellation list decoding method according to claim 1, characterized in that: Step S21 is further specified as follows: by correlating the local LFM signal at the receiving end with the received LFM signal, the time-domain channel estimate can be obtained. The frequency-domain channel can be obtained by Fourier transform. The signal obtained in step S16 is subjected to OFDM demodulation processing to obtain frequency-domain information. The frequency-domain channel and frequency-domain information are equalized to obtain the equalized frequency-domain information.

6. The chaotic orthogonal pilot multilayer check serial cancellation list decoding method according to claim 1, characterized in that: Step S22 is further specified as follows: the chaotic spread spectrum is despread by the equalized frequency domain information to obtain the chaotic spread spectrum sequence, and the corresponding CRC check code of each message submodule can be obtained by using the inverse process of the encoding process.

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