A multi-channel encoding and decoding system based on iterative feedback

Abstract

This invention discloses a multi-element channel coding and decoding system based on iterative feedback, belonging to the field of communication technology. It includes a transmitter and a receiver; the transmitter includes a multi-element LDPC coding module, a serial-to-parallel conversion / mapping module, and a modulator module; the receiver includes a soft demodulator module, a serial-to-parallel conversion / demapping module, and a multi-element LDPC soft decoding module. Based on multi-element LDPC coding, this invention designs a special modulation constellation diagram, such that each 16QAM symbol corresponds to two mutually related GF4 multi-element LDPC coded symbols, and the average Euclidean distance of each symbol is maximized. Simultaneously, it introduces iterative feedback decoding, improving noise immunity and enhancing the performance of the optical communication system.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and more specifically to a multi-channel encoding and decoding system based on iterative feedback. Background Technology

[0002] With the rapid increase in user demand for transmission distance and communication capacity, modern fiber optic communication systems face severe challenges in terms of growth rate and capacity expansion. Binary coding is a common coding method in existing optical communication systems. In its decoding process, the minimum Hamming distance rule is typically used, which focuses on finding the minimum distance between the received signal and the transmitted signal.

[0003] Based on existing spectrum resources, higher-order modulation is an inevitable way to improve the spectral efficiency of optical fiber communication systems. The decision-making process typically uses the minimum Euclidean distance rule, which is based on the Euclidean distance between the received signal sample and the ideal signal sample. However, the final decoding process requires the minimum Hamming distance rule, leading to performance loss. Unlike binary decoding, multi-symbol decoding directly encodes and decodes the received symbols, effectively avoiding the aforementioned performance differences. This method considers the relationships between multiple symbols, not just binary bits, thereby improving system performance and efficiency. By directly processing symbols, channel capacity can be better utilized, the bit error rate reduced, and overall communication quality improved.

[0004] LDPC codes are a type of high-performance FEC error correction coding that can approach the Shannon limit at high code lengths and has broad prospects. Multi-ary LDPC coding is more suitable for high-order modulation and has better noise immunity than binary LDPC coding.

[0005] In binary channel coding and decoding systems, introducing an iterative feedback decoding system, which uses the result of each decoding step to feed back the received signal, can improve noise immunity. Currently, there is no technical solution that combines this with multi-level coding.

[0006] Therefore, how to provide a multi-channel encoding and decoding system based on iterative feedback is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0007] In view of this, the present invention provides a multi-channel coding and decoding system based on iterative feedback. On the basis of multi-channel LDPC coding, a specially designed constellation diagram is used so that each symbol corresponds to two multi-channel LDPC coding symbols and the average Euclidean distance of each symbol is maximized. At the same time, iterative feedback decoding is introduced to improve noise resistance.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] A multi-channel encoding and decoding system based on iterative feedback includes: a transmitter and a receiver;

[0010] The transmitting end includes: a multi-element LDPC encoding module, a serial-to-parallel conversion / mapping module, and a modulator module;

[0011] The receiver includes: a soft demodulator module, a serial-to-parallel conversion / demapping module, and a multi-element LDPC soft decoding module.

[0012] The multivariate LDPC encoding module adopts multivariate LDPC encoding based on the finite field GF4, and the input and output symbol values ​​are in the range of 0 to 3.

[0013] The serial-to-parallel conversion / mapping module converts the symbols output by two consecutive LDPC encoding modules into a single symbol S with a value between 0 and 15. n As the original signal, the calculation formula is:

[0014] S n =s 2n-1 ×4+s 2n ;

[0015] In the formula, s 2n-1 s 2n S represents the symbols output by the two LDPC encoding modules. n This is the original signal.

[0016] The modulator module, according to a preset constellation diagram, directs S... n Modulate the upchannel to obtain 16QAM symbols.

[0017] The preset constellation diagram is as follows:

[0018] Each 16QAM symbol is mapped from two multi-dimensional LDPC symbols. The first multi-dimensional LDPC symbol corresponds to the four quadrants of the 16QAM constellation diagram; the second multi-dimensional LDPC symbol corresponds to the center, two sides and four vertices of the 16QAM constellation diagram. The two symbols are modulated into one symbol to obtain a constellation diagram viewed from the perspective of the two multi-dimensional LDPC symbols. This constellation diagram construction method maximizes the average Euclidean distance between the two symbols.

[0019] The soft demodulator module is connected to an optical receiver, which receives optical signals from the optical fiber and obtains 16QAM symbols after DSP processing. n , to use 16QAM symbols r n The input is given to the soft demodulator module, and the original signal S is output. n Take the prior probability vector for each value.

[0020] In each iteration, the serial-to-parallel conversion / demapping module processes the prior probability vector through the output s of the multivariate LDPC soft decoding module from the previous iteration. 2n-1 s 2n The corresponding corrected probability vector Weighted feedback, converted into s 2n-1 s 2n The corresponding error correction probability vector

[0021] The internal structure of the serial-to-parallel conversion / demapping module consists of a serial-to-parallel converter and two weighters.

[0022] The serial-to-parallel converter will feed back the corrected probability vector sequence. Divided into and Two routes;

[0023] respectively through the first weighter and the second weighter Weighted and

[0024] Then, through the aforementioned serial-to-parallel converter, and merged into Output.

[0025] The multivariate LDPC soft decoding module is used to input the error correction probability vector sequence. Output the corrected probability vector sequence The decoding results c0, c1, ... c 2n-1 ,c 2n …and complete the verification.

[0026] The multi-dimensional LDPC soft decoding module is internally divided into a soft decoding module, a verification module, and a decision module;

[0027] The soft decoding module input The updated probability vector sequence is obtained after software decoding.

[0028] The updated probability vector sequence The input to the decision module determines the value of the code element by taking the maximum value in each vector.

[0029] The verification module outputs the symbol sequence. Perform a checksum verification, let the checksum matrix be H, and the checksum be... when The time check is successful.

[0030] As can be seen from the above technical solutions, compared with the prior art, the present invention discloses a multi-channel coding and decoding system based on iterative feedback decoding, which combines 16QAM modulation and GF4 multi-dimensional LDPC coding (or other multi-dimensional coding), increases the Euclidean distance of symbols through a special 16QAM constellation diagram and introduces an outer loop iterative decoding, thereby improving the error correction capability of multi-dimensional LDPC codes and thus improving noise immunity. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0032] Figure 1 This is a schematic diagram of the overall system structure of the present invention;

[0033] Figure 2 This is a schematic diagram of the transmitter structure provided by the present invention;

[0034] Figure 3 This is a schematic diagram of the receiver structure provided by the present invention;

[0035] Figure 4 The 16QAM constellation diagram provided for this invention;

[0036] Figure 5 This invention provides a constellation diagram corresponding to the first multivariate LDPC symbol for each 16QAM symbol.

[0037] Figure 6 This invention provides a constellation diagram corresponding to the second multivariate LDPC symbol for each 16QAM symbol.

[0038] Figure 7 The constellation diagram provided by this invention is viewed from the perspective of two multi-element LDPC symbols simultaneously.

[0039] Figure 8 This is a schematic diagram of the serial-to-parallel conversion / demapping module structure provided by the present invention;

[0040] Figure 9 This is a schematic diagram of the structure of the weighter 1 provided by the present invention;

[0041] Figure 10 This is a schematic diagram of the structure of the weighter 2 provided by the present invention;

[0042] Figure 11 This is a schematic diagram of the multi-element LDPC soft decoding module structure provided by the present invention. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] The purpose of this invention is to provide a multi-channel coding and decoding system based on iterative feedback, comprising: a transmitter and a receiver; wherein, the transmitter includes: a multi-channel LDPC coding module, a serial-to-parallel conversion / mapping module, and a modulator module; the receiver includes: a soft demodulator module, a serial-to-parallel conversion / demapping module, and a multi-channel LDPC soft decoding module. By combining 16QAM modulation and GF4 multi-channel LDPC coding (or other multi-channel coding), increasing the Euclidean distance of symbols through a special 16QAM constellation diagram and introducing an outer loop iterative feedback decoding, the error correction capability of the multi-channel LDPC code is improved, thereby enhancing its noise immunity. This provides a solution for improving the error correction capability of the soft decision algorithm for multi-channel LDPC codes by introducing an outer loop iterative decoding based on a special constellation diagram.

[0045] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0046] Example 1:

[0047] See Figure 1-3 Embodiment 1 of the present invention discloses a multi-channel encoding and decoding system based on iterative feedback, comprising: a transmitter and a receiver; wherein, the transmitter comprises: a multi-channel LDPC encoding module, a serial-to-parallel conversion / mapping module, and a modulator module; the receiver comprises: a soft demodulator module, a serial-to-parallel conversion / demapping module, and a multi-channel LDPC soft decoding module.

[0048] Specifically, the multivariate LDPC encoding module adopts multivariate LDPC encoding based on the finite field GF4, and the input and output symbol values ​​are in the range of 0 to 3.

[0049] Specifically, the serial-to-parallel converter / mapper module converts the code symbols s output by two consecutive LDPC encoding modules. 2n-1 s 2n Convert to a symbol S with a value between 0 and 15. n The calculation formula is:

[0050] S n =s 2n-1 ×4+s 2n ;

[0051] Specifically, the modulator module, according to a specially designed constellation diagram, will... n Modulate the upchannel to obtain 16QAM symbols. It is a 16QAM signal, which is transmitted through the channel.

[0052] Specifically, the preset constellation diagram is as follows: based on the constellation diagram of the first multi-dimensional LDPC symbol corresponding to each 16QAM symbol and the constellation diagram of the second multi-dimensional LDPC symbol corresponding to each 16QAM symbol, the two symbols are modulated into one symbol.

[0053] For details, please refer to its constellation chart. Figures 4-7 As shown, where, Figure 4 This is a 16QAM constellation diagram; starting from the first symbol of each 16QAM symbol, we obtain... Figure 5 The constellation diagram corresponding to the first symbol shown; looking at the second symbol of each 16QAM symbol, we obtain... Figure 6 The constellation diagram corresponding to the second symbol shown; each value of a symbol contains all the values ​​of another symbol, and when viewed together, they appear as follows: Figure 7 The constellation diagram shown is viewed from the perspective of two symbols simultaneously. The two symbols are modulated into a 16QAM symbol. Red represents the value of the first symbol, and blue represents the value of the second symbol.

[0054] Specifically, each 16QAM symbol is mapped from two multi-dimensional LDPC symbols. The first multi-dimensional LDPC symbol corresponds to the four quadrants of the 16QAM constellation diagram; the second multi-dimensional LDPC symbol corresponds to the center, two sides and four vertices of the 16QAM constellation diagram. The two symbols are modulated into one symbol to obtain a constellation diagram viewed from the perspective of the two multi-dimensional LDPC symbols. This constellation diagram construction method maximizes the Euclidean distance between the two symbols.

[0055] Specifically, the soft demodulator module optical receiver receives optical signals from the optical fiber, and after DSP processing, obtains 16QAM symbols. n (At the receiving end, after the optical signal is received by the receiver and processed by the DSP to obtain the 16QAM symbol), it is input to the soft demodulator module, and the original signal S is output. n Prior probability vectors for each value:

[0056]

[0057] In the formula, i is S n Possible values ​​for .

[0058] Specifically, assuming the channel noise follows a two-dimensional normal distribution, i.e., N(0,0,σ,σ,0), the calculation method is as follows:

[0059]

[0060] In the formula, θ is the normalization parameter. re represents taking the real part, and im represents taking the imaginary part;

[0061] σ is the standard deviation of the noise. This represents the probability that the nth symbol takes the value i.

[0062] Specifically, the serial-to-parallel conversion / demapping module converts S in each iteration. n The corresponding probability vector After the previous iteration, the LDPC decoder output s 2n-1 s 2n The corresponding corrected probability vector Weighted feedback, converted into s 2n-1 s 2n The corresponding error correction probability vector

[0063] Specifically, before the correction:

[0064]

[0065] For code element s 2n-1 The probability of taking the value i

[0066]

[0067] For code element s 2n The probability of taking the value i

[0068] Correction (Feedback)

[0069]

[0070] Specifically, the calculation method involves summing the probabilities of the modulation symbols corresponding to each coded symbol by weighting them with the feedback probabilities of the other symbol, and then normalizing the sum.

[0071]

[0072] α is the normalization parameter, satisfying

[0073] No feedback value was received during the first calculation; the default value was used. Therefore, there is

[0074]

[0075] α is the normalization parameter, satisfying

[0076] For details, see Figure 8The serial-to-parallel conversion / demapping module consists of a serial-to-parallel converter and two weighters. The serial-to-parallel converter feeds back (corrected) the probability vector sequence. Divided into two routes and The weights are respectively applied by the first weighter 1 and the second weighter 2. Weighted and Then, through a parallel-to-serial converter, and merged into Output.

[0077] For details, see Figure 9 Based on the principle of multi-dimensional encoding weighting with iterative feedback, in the first weighter 1, through the feedback sequence right Weighted average The calculation formula is as follows:

[0078]

[0079] For details, see Figure 10 Based on the iterative feedback multivariate decoding weighting principle, in the second weighter 2, through the feedback sequence... right Weighted average The calculation formula is as follows:

[0080]

[0081] Specifically, in iterative decoding, the demodulation result of the previous iteration is needed in each iteration, but not in the first iteration. The input here is the output of the previous decoding.

[0082] Specifically, the multivariate LDPC soft decoding module inputs a sequence of probability vectors prior to correction. Output the corrected probability vector sequence The decoding results c0, c1, ... c 2n-1 ,c 2n …and perform verification at the same time.

[0083] For details, see Figure 11 The multivariate LDPC soft decoding module is internally divided into a soft decoding module, a verification module, and a decision module, wherein:

[0084] Soft decoding module: Input The updated probability vector sequence is obtained after soft decoding (such as BP decoding).

[0085] Decision module: Input The code element value is determined by taking the maximum value in each vector.

[0086] Verification module: verifies the output symbol sequence. Perform a checksum verification, let the checksum matrix be H, and the checksum be... when The time check is successful.

[0087] Example 2:

[0088] Embodiment 2 of this invention discloses a communication method for a multi-channel encoding and decoding system based on iterative feedback, provided by this invention. This communication method is a multi-channel LDPC encoding and decoding method that combines a special constellation diagram and an outer loop information transmission. It adds an outer loop iterative decoding process to the traditional decoding process, improving its error correction capability and noise resistance.

[0089] Specifically, the FEC (Forward Error Correction Coding) of this invention employs a multi-element LDPC coding derived from the QC-LDPC coding of the 5G standard. The coefficients of the base matrix of the QC-LDPC coding in the 5G standard are replaced with random GF4 coefficients to obtain the required multi-element QC LDPC coding base matrix. Taking base matrix 1 from the 5G QC-LDPC standard for expansion, at a code rate of 0.5, the expansion coefficient Z = 32 is set, resulting in a code length of 1408 GF4 symbols and 704 GF4 symbols for information bits, equivalent to a code length of 2816 bits and 1408 information bits. 16QAM transmission is used. The upper limit for the number of inner loop iterations during decoding is set to 50, and the upper limit for the number of outer loop iterations is set to 30.

[0090] The specific implementation includes the following steps:

[0091] A1. Generate a parity check matrix H with random coefficients based on the base map, code length, and code rate.

[0092] A2. The transmitter randomly generates 704 GF4 information sequences [g0, g1, ... g] with values ​​between 0 and 3. 703 ];

[0093] A3. [g0, g1, ... g 703 The input is processed by the multivariate LDPC encoding module, which encodes the sequence based on the H matrix according to the characteristics of QC-LDPC encoding, resulting in the encoded sequence [s0, s1, ... s]. 1407 The specific process refers to the 5G LDPC (Low-Density Parity-Check) standard.

[0094] A4. Enter the serial-to-parallel conversion / mapping module to obtain the GF16 symbol sequence [S0, S1, ... S]. 703 ].

[0095] A5. Enter the modulator module and convert it into a QAM16 symbol sequence [v0, v1, ... v 703 ], modulated on the optical fiber channel.

[0096] A6. Receive signals from the optical fiber, process them using a DSP, and then recover the symbol information sequence [r0, r1, ... r]. 703 Specifically, after DSP processing, the specific algorithm depends on the system configuration, and this invention does not impose any limitations.

[0097] A7. After passing through the soft demodulator module, a probability vector sequence is obtained.

[0098] A8. Will The feedback (correction) probability vector sequence of the A9 output from the previous iteration (During the first loop, the output of A9 is replaced with a probability vector of all 1s) Input to the serial-to-parallel conversion / demapping module, output the corrected probability vector

[0099] A9. Will The input is a soft decoding module. After 50 rounds of QSPA decoding, a verification is performed. If the verification is successful, the output result sequence [c0, c1, ... c] is generated. 1407 If the verification fails, output the corrected probability vector sequence. Then jump to A8.

[0100] A10. Output a decoding failure message when the number of iterations between A8 and A9 reaches the upper limit of the outer loop iterations.

[0101] Based on multi-element LDPC coding, this invention designs a special modulation constellation architecture, so that each 16QAM symbol corresponds to two multi-element LDPC coding symbols, and the average Euclidean distance of each symbol is maximized. At the same time, feedback decoding is introduced to improve noise immunity and enhance the performance of optical communication systems.

[0102] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0103] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily 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 invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A multi-channel encoding and decoding system based on iterative feedback, characterized in that, include: Transmitter and receiver; The transmitting end includes: a multi-element LDPC encoding module, a serial-to-parallel conversion / mapping module, and a modulator module; The receiver includes: a soft demodulator module, a serial-to-parallel conversion / demapping module, and a multi-element LDPC soft decoding module; The serial-to-parallel conversion / mapping module converts the symbols output by two consecutive LDPC encoding modules into a single symbol with a value between 0 and 15. As the original signal, the calculation formula is: ； In the formula, The symbols output by the two LDPC encoding modules. The original signal; The modulator module, according to a preset constellation diagram, will... Modulate the upchannel to obtain 16QAM symbols. ; The preset constellation diagram is as follows: Each 16QAM symbol is mapped from two multi-dimensional LDPC symbols. The first multi-dimensional LDPC symbol corresponds to the four quadrants of the 16QAM constellation diagram; the second multi-dimensional LDPC symbol corresponds to the center, two sides and four vertices of the 16QAM constellation diagram. The two symbols are modulated into one symbol to obtain the constellation diagram viewed from the perspective of the two multi-dimensional LDPC symbols simultaneously. In each iteration, the serial-to-parallel conversion / demapping module converts the prior probability vector through the output of the multivariate LDPC soft decoding module from the previous iteration. The corresponding corrected probability vector Weighted feedback, converted into The corresponding error correction probability vector ; The internal structure of the serial-to-parallel conversion / demapping module consists of a serial-to-parallel converter and two weighters. The serial-to-parallel converter will feed back the corrected probability vector sequence [...] …] divided into and Two routes; respectively through the first weighter and the second weighter Weighted and ; Then, through the aforementioned serial-to-parallel converter, and merged into Output.

2. The multi-channel encoding and decoding system based on iterative feedback according to claim 1, characterized in that, The multivariate LDPC encoding module adopts multivariate LDPC encoding based on the finite field GF4, and the input and output symbol values ​​are between 0 and 3.

3. The multi-channel encoding and decoding system based on iterative feedback according to claim 1, characterized in that, The soft demodulator module is connected to an optical receiver, which receives optical signals from the optical fiber and obtains 16QAM symbols after DSP processing. , 16QAM symbols The input is given to the soft demodulator module, and the original signal is output. Take the prior probability vector for each value.

4. The multi-channel encoding and decoding system based on iterative feedback according to claim 1, characterized in that, The multivariate LDPC soft decoding module is used to input the error correction probability vector sequence. Output the corrected probability vector sequence and decoding results And complete the verification.

5. A multi-channel encoding and decoding system based on iterative feedback according to claim 4, characterized in that, The multi-dimensional LDPC soft decoding module is internally divided into a soft decoding module, a verification module, and a decision module; The soft decoding module input After soft decoding, the updated probability vector sequence is obtained. ; The updated probability vector sequence The input to the decision module determines the value of the code element by taking the maximum value in each vector. ; The verification module outputs the symbol sequence. Perform a checksum verification, let the checksum matrix be H, and the checksum be... ,when The time check is successful.

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