Hollow-core optical fiber communication method and system for reducing complexity

Abstract

The invention discloses a hollow-core optical fiber communication method and system for reducing complexity, and the method comprises the steps: obtaining original bit data, and mapping the original bit data to an initial constellation diagram through a quadrature amplitude modulation mapping algorithm; rotating the initial constellation diagram according to a preset rotation angle to obtain a first constellation optimization diagram, adjusting the first constellation optimization diagram by using a sparrow search algorithm to obtain a second constellation optimization diagram, converting the second constellation optimization diagram into a transmission signal, and transmitting the transmission signal to the receiving end through a hollow-core optical fiber; performing data preprocessing on the received transmission signal to obtain a de-noised signal, performing phase recovery on the de-noised signal based on a quadratic algorithm to obtain a second constellation optimization graph, and performing de-mapping on the second constellation optimization graph to re-convert the second constellation optimization graph into original bit data; according to the invention, the complexity of digital signal processing is reduced, and the accuracy and efficiency of phase recovery are obviously improved, so that the performance of a coherent optical communication system based on the hollow-core optical fiber is comprehensively improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of optical fiber communications, and in particular relates to a hollow-core optical fiber communication method and system for reducing complexity. Background Art

[0002] With the rapid development of communications technology, data traffic has experienced explosive growth. In long-distance, high-data-volume transmission scenarios, the transmission latency of traditional solid-core optical fibers cannot meet the stringent ultra-low latency standards required for current and future high-speed communications, severely hindering the performance of communication networks. Against this backdrop, hollow-core optical fiber (HCF), with its unique air transmission medium, significantly reduces optical signal transmission latency compared to traditional solid-core optical fiber. This demonstrates its enormous potential in meeting the urgent demand for ultra-low latency in the communications sector.

[0003] However, the signal processing architecture of existing hollow-core fiber systems still continues the traditional coherent detection algorithm framework. The traditional coherent detection algorithm framework needs to rely on complex signal processing processes, resulting in waste of hardware resources and excessive digital signal processing (DSP) calculations, which restricts the full utilization of the ultra-low transmission delay and low loss characteristics of hollow-core fiber. Summary of the Invention

[0004] The present invention provides a hollow-core optical fiber communication method and system for reducing complexity, which reduces the complexity of digital signal processing and significantly improves the accuracy and efficiency of phase recovery, thereby comprehensively improving the performance of coherent optical communication systems based on hollow-core optical fibers.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A first aspect of the present invention provides a hollow-core optical fiber communication method for reducing complexity, comprising:

[0007] Obtaining the original bit data to be sent, and mapping the original bit data to the initial constellation diagram through an orthogonal amplitude modulation mapping algorithm;

[0008] The initial constellation diagram is rotated according to a preset rotation angle to obtain a first constellation optimization diagram, the first constellation optimization diagram is adjusted using a sparrow search algorithm to obtain a second constellation optimization diagram, the second constellation optimization diagram is converted into a transmission signal, and the transmission signal is transmitted to a receiving end through a hollow-core optical fiber;

[0009] Data preprocessing is performed on the received transmission signal to obtain a denoised signal, phase recovery is performed on the denoised signal based on a quadratic algorithm to obtain a second constellation optimization graph, and the second constellation optimization graph is demapped and reconverted into original bit data.

[0010] Furthermore, the original bit data is mapped to the initial constellation diagram through an orthogonal amplitude modulation mapping algorithm, which specifically includes:

[0011] Will The constellation points are distributed in an h-row and h-column grid on the complex plane to construct an initial constellation diagram; the original bit data is divided into bit groups according to the set number of bits, and Gray coding is used to map each bit group to a constellation point on the initial constellation diagram.

[0012] Furthermore, rotating the initial constellation diagram according to a preset rotation angle to obtain a first constellation optimization diagram specifically includes:

[0013] The rotation factor is calculated according to the preset rotation angle, and the expression formula is:

[0014]

[0015] In the formula, is the rotation factor, is the rotation angle; j represents the imaginary unit;

[0016] Multiply each constellation point in the initial constellation diagram by the rotation factor to obtain the first constellation optimization diagram.

[0017] Furthermore, the first constellation optimization graph is adjusted using a sparrow search algorithm to obtain a second constellation optimization graph, specifically including:

[0018] Each constellation point in the first constellation optimization graph is regarded as a sparrow individual, and the sparrow individuals are divided into discoverers, followers and vigilants; the discoverers, followers and vigilants form a sparrow population;

[0019] A fitness function is constructed based on the Euclidean distance between constellation points. The Euclidean distance between constellation points is substituted into the fitness function to obtain a fitness value. The sparrow population is updated with the goal of maximizing the fitness value under constraints. The constraints are:

[0020] like hour, ;

[0021] In the formula, is the modulation phase of the kth constellation point, The outermost constellation point set in the current constellation diagram; is pi; is the phase offset;

[0022] Adjust the constellation point position according to the sparrow population; repeatedly iteratively adjust the first constellation optimization map using the sparrow search algorithm until the fitness value converges or the maximum number of iterations is reached to output the second constellation optimization map.

[0023] Furthermore, the sparrow population is updated with the goal of maximizing the fitness value, specifically including:

[0024] According to the modulation phase Calculating the exploration vector , randomly generate the first unit vector Q, and use the first unit vector Q and the exploration vector Update the discoverer's position, the expression formula is:

[0025] ; In the formula, is the finder position of the k-th constellation point in the t-th iteration, is the finder position of the k-th constellation point in the t-1-th iteration; is the step size coefficient; is the outermost constellation point set in the current constellation diagram; I is the inner constellation point set in the current constellation diagram;

[0026] Substitute the positions of the discoverer, follower and sentinel in the t-1th iteration into the fitness function to obtain the optimal sparrow individual position corresponding to the maximum fitness value ; According to the optimal individual position of sparrows Update the follower position, the expression formula is:

[0027]

[0028] In the formula, is the follower position of the k-th constellation point in the t-th iteration; is the follower position of the k-th constellation point in the t-1-th iteration; is the learning coefficient;

[0029] Randomly generate a second unit vector , according to the second unit vector Update the position of the sentinel, and the expression formula is:

[0030]

[0031] In the formula, is the position of the sentinel at the kth constellation point in the tth iteration; is the position of the sentinel at the kth constellation point in the t-1th iteration; Is the warning factor.

[0032] Furthermore, the positions of the discoverer, follower, and sentinel in the t-1th iteration are substituted into the fitness function to obtain the optimal individual sparrow position corresponding to the maximum fitness value. , specifically including:

[0033]

[0034]

[0035]

[0036]

[0037] In the formula, For the location of the discoverer, the follower and the vigilant, is the constellation diagram output by the t-1th iteration, 、 、 and is the constellation point coordinate vector corresponding to the position of the individual sparrow; 、 、 and is the constellation point number; Output the outermost constellation point set in the constellation diagram for the t-1th iteration, Output the set of inner constellation points in the constellation diagram for the t-1th iteration; is the fitness value, and To set weights; The minimum Euclidean distance between the four outermost constellation points in the current constellation diagram; It is the minimum Euclidean distance of the inner constellation points in the current constellation diagram.

[0038] Furthermore, data preprocessing is performed on the received transmission signal to obtain a denoised signal, specifically including:

[0039] The received transmission signal is input into a low-pass filter to suppress additive Gaussian white noise: the expression formula is:

[0040]

[0041]

[0042]

[0043] In the formula, represents the kth transmission signal sent by the transmitter; represents the symbol amplitude corresponding to the k-th constellation point in the second constellation optimization diagram, represents the symbol phase corresponding to the k-th constellation point in the second constellation optimization diagram; is the additive white Gaussian noise of the k-th transmission signal; is the phase noise of the kth transmitted signal; is the kth transmission signal after noise reduction; is the kth transmission signal received;

[0044] A phase-locked loop is used to recover the clock and frequency of the transmission signal to obtain the denoised signal.

[0045] Furthermore, the phase of the denoised signal is recovered based on a quadratic algorithm to obtain a second constellation optimization graph, which specifically includes:

[0046] The phase noise of the denoised signal is extracted based on the quadratic algorithm, and the expression formula is:

[0047]

[0048] In the formula, is the kth denoised signal; represents the symbol amplitude corresponding to the k-th constellation point in the second constellation optimization diagram; is pi; is the phase noise of the kth denoised signal; is the phase offset;

[0049] According to the phase noise Phase compensation is performed on the kth denoised signal to obtain a second constellation optimization graph.

[0050] A second aspect of the present invention provides a hollow-core optical fiber communication system for reducing complexity, comprising:

[0051] The transmitting module is used to obtain the original bit data to be sent and map the original bit data to the initial constellation diagram through the orthogonal amplitude modulation mapping algorithm;

[0052] An optimization module, configured to rotate the initial constellation diagram according to a preset rotation angle to obtain a first constellation optimization diagram, and adjust the first constellation optimization diagram using a sparrow search algorithm to obtain a second constellation optimization diagram;

[0053] a transmission module, configured to convert the second constellation optimization graph into a transmission signal, and transmit the transmission signal to the receiving end through a hollow-core optical fiber;

[0054] The receiving module is used to perform data preprocessing on the received transmission signal to obtain a denoised signal, perform phase recovery on the denoised signal based on a quadratic algorithm to obtain a second constellation optimization map, and demap the second constellation optimization map and reconvert it into original bit data.

[0055] The third aspect of the present invention provides an electronic terminal, comprising a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the hollow-core optical fiber communication method described in the first aspect.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] This invention rotates the initial constellation diagram by a preset angle to produce a first optimized constellation diagram. This rotation operation alters the distribution of constellation points. The first optimized constellation diagram is then further adjusted using the Sparrow Search Algorithm (SSA) to produce a second optimized constellation diagram. The SSA simulates the foraging behavior of sparrows to optimize the positions of constellation points globally and locally, further improving the performance of the constellation diagram. The optimized constellation diagram not only increases the minimum Euclidean distance between constellation points, but also enhances the system's anti-interference capability and bit error performance.

[0058] The present invention preprocesses the received transmission signal to remove noise interference and obtain a denoised signal. Phase recovery is then performed on the denoised signal using a quadratic algorithm to obtain a second optimized constellation. The quadratic algorithm simplifies the phase recovery process, reduces computational complexity at the receiver, and improves phase estimation accuracy.

[0059] The present invention significantly improves the spectrum efficiency, anti-interference capability and data transmission reliability of the communication system by combining constellation diagram optimization, signal processing and efficient modulation and demodulation technology, while reducing the complexity and power consumption of the system, providing an efficient solution for hollow-core optical fiber communication systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 This is a flow chart of hollow-core optical fiber communication provided by Example 1 of the present invention;

[0061] Figure 2 This is a flow chart of the constellation diagram optimized by the sparrow search algorithm provided in Example 1 of the present invention;

[0062] Figure 3 This is an optimized structural diagram of the constellation diagram provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0063] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention.

[0064] Example 1

[0065] like Figure 1 As shown, this embodiment provides a hollow-core optical fiber communication method for reducing complexity, including:

[0066] Obtain the original bit data to be sent and map it to the initial constellation diagram using the orthogonal amplitude modulation mapping algorithm, specifically including:

[0067] In this embodiment, the orthogonal amplitude modulation mapping algorithm is selected as the 16QAM mapping algorithm; the 16 constellation points are distributed in a 4-row, 4-column grid on the complex plane to construct an initial constellation diagram; the original bit data is divided into bit groups according to a set number of bits, and each bit group is mapped to a constellation point on the initial constellation diagram using Gray coding. Orthogonal amplitude modulation enables a single symbol to carry more bit information, effectively improving spectrum efficiency and transmission capacity.

[0068] like Figure 3 As shown, the initial constellation diagram is rotated according to a preset rotation angle to obtain a first constellation optimization diagram, which specifically includes:

[0069] The rotation factor is calculated according to the preset rotation angle, and the expression formula is:

[0070]

[0071] In the formula, is the rotation factor, is the rotation angle; j represents the imaginary unit; in this embodiment 45 degrees;

[0072] Multiply each constellation point in the initial constellation diagram by the rotation factor to obtain the first constellation optimization diagram.

[0073] like Figure 2 As shown, the first constellation optimization graph is adjusted using the sparrow search algorithm to obtain the second constellation optimization graph, specifically including:

[0074] Each constellation point in the first constellation optimization graph is regarded as a sparrow individual, and the sparrow individuals are divided into discoverers, followers and vigilants; the discoverers, followers and vigilants form a sparrow population;

[0075] A fitness function is constructed based on the Euclidean distance between the constellation points, the Euclidean distance between the constellation points is substituted into the fitness function to obtain a fitness value, and the sparrow population is updated with the goal of maximizing the fitness value under constraints, specifically including:

[0076] According to the modulation phase Calculating the exploration vector , randomly generate the first unit vector Q, and use the first unit vector Q and the exploration vector Update the discoverer's position, the expression formula is:

[0077]

[0078]

[0079] In the formula, is the finder position of the k-th constellation point in the t-th iteration, is the finder position of the k-th constellation point in the t-1-th iteration; is the step size coefficient; is the outermost constellation point set in the current constellation diagram; I is the inner constellation point set in the current constellation diagram; is the modulation phase of the kth constellation point, is pi; is the phase offset; the discoverer increases the minimum Euclidean distance of the four outermost constellation points and reduces the minimum Euclidean distance of other constellation points;

[0080] Substitute the positions of the discoverer, follower and sentinel in the t-1th iteration into the fitness function to obtain the optimal sparrow individual position corresponding to the maximum fitness value ; The expression formula is:

[0081]

[0082]

[0083]

[0084]

[0085] In the formula, For the location of the discoverer, the follower and the vigilant, is the constellation diagram output by the t-1th iteration, 、 、 and is the constellation point coordinate vector corresponding to the position of the individual sparrow; 、 、 and is the constellation point number; Output the outermost constellation point set in the constellation diagram for the t-1th iteration, Output the set of inner constellation points in the constellation diagram for the t-1th iteration; is the fitness value, and To set weights; The minimum Euclidean distance between the four outermost constellation points in the current constellation diagram; The minimum Euclidean distance of the inner constellation points in the current constellation diagram;

[0086] According to the optimal individual position of sparrows Update the follower position, the expression formula is:

[0087]

[0088] In the formula, is the follower position of the k-th constellation point in the t-th iteration; is the follower position of the k-th constellation point in the t-1-th iteration; is the learning coefficient;

[0089] Randomly generate a second unit vector , according to the second unit vector Update the position of the sentinel, and the expression formula is:

[0090]

[0091] In the formula, is the position of the sentinel at the kth constellation point in the tth iteration; is the position of the sentinel at the kth constellation point in the t-1th iteration; is the warning factor;

[0092] When the sparrow search algorithm falls into a local optimum and the fitness function value no longer changes significantly over multiple iterations, the alerter triggers a danger warning mechanism and the positions of the constellation points are adjusted, allowing the sparrow search algorithm to escape the local optimum and continue searching for a better constellation point distribution. This helps prevent the algorithm from converging prematurely, making it more likely to find a constellation point distribution that meets the target.

[0093] Adjust the constellation point position according to the sparrow population; repeatedly iteratively adjust the first constellation optimization map using the sparrow search algorithm until the fitness value converges or the maximum number of iterations is reached to output the second constellation optimization map.

[0094] The second constellation optimization diagram can make the signal points better resist the influence of phase rotation, maintain the distinguishability of the signal, make the outermost constellation points easier to detect and recover, and reduce the computational complexity of the signal recovery process at the receiving end.

[0095] Converting the second constellation optimization graph into a transmission signal, and transmitting the transmission signal to the receiving end through a hollow-core optical fiber;

[0096] Performing data preprocessing on the received transmission signal to obtain a denoised signal, specifically including:

[0097] The received transmission signal is input into a low-pass filter to suppress additive Gaussian white noise: the expression formula is:

[0098]

[0099]

[0100]

[0101] In the formula, represents the kth transmission signal sent by the transmitter; represents the symbol amplitude corresponding to the k-th constellation point in the second constellation optimization diagram, represents the symbol phase corresponding to the k-th constellation point in the second constellation optimization diagram; is the additive white Gaussian noise of the k-th transmission signal; is the phase noise of the kth transmitted signal; is the kth transmission signal after noise reduction; is the kth transmission signal received;

[0102] A phase-locked loop is used to recover the clock and frequency of the transmission signal to obtain the denoised signal.

[0103] In the traditional 16QAM modulation format, the value of M is 4. After the M-th power operation, the received signal can be expressed as:

[0104]

[0105] When the outermost constellation points are selected for phase noise estimation, the modulation phases of these constellation points satisfy:

[0106]

[0107] Therefore, it is only necessary to use the quadratic algorithm to recover the phase of the denoised signal to obtain the second constellation optimization graph, which specifically includes:

[0108] The phase noise of the denoised signal is extracted based on the quadratic algorithm, and the expression formula is:

[0109]

[0110] In the formula, is the kth denoised signal; represents the symbol amplitude corresponding to the k-th constellation point in the second constellation optimization diagram; is pi; is the phase noise of the kth denoised signal; is the phase offset;

[0111] According to the phase noise Phase compensation is performed on the kth denoised signal to obtain a second constellation optimization graph.

[0112] The second constellation optimization diagram is demapped and reconverted into the original bit data. This embodiment reduces the fourth-order operation to a quadratic operation, reducing the amount of calculation in the signal detection and phase recovery process, and lowering the hardware processing requirements of the optical fiber communication system. On the other hand, it effectively improves the system's anti-interference ability and reduces the bit error rate. In long-distance, high-speed hollow-core optical fiber communication scenarios, it can ensure the stability and reliability of signal transmission.

[0113] Example 2

[0114] This embodiment provides a hollow-core optical fiber communication system for reducing complexity. The hollow-core optical fiber communication system is used to perform the hollow-core optical fiber communication method described in Example 1. The hollow-core optical fiber communication system includes:

[0115] The transmitting module is used to obtain the original bit data to be sent and map the original bit data to the initial constellation diagram through the orthogonal amplitude modulation mapping algorithm;

[0116] An optimization module, configured to rotate the initial constellation diagram according to a preset rotation angle to obtain a first constellation optimization diagram, and adjust the first constellation optimization diagram using a sparrow search algorithm to obtain a second constellation optimization diagram;

[0117] a transmission module, configured to convert the second constellation optimization graph into a transmission signal, and transmit the transmission signal to the receiving end through a hollow-core optical fiber;

[0118] The receiving module is used to perform data preprocessing on the received transmission signal to obtain a denoised signal, perform phase recovery on the denoised signal based on a quadratic algorithm to obtain a second constellation optimization map, and demap the second constellation optimization map and reconvert it into original bit data.

[0119] The optimization module uses the sparrow search algorithm to adjust the first constellation optimization graph to obtain the second constellation optimization graph, specifically including:

[0120] Each constellation point in the first constellation optimization graph is regarded as a sparrow individual, and the sparrow individuals are divided into discoverers, followers and vigilants; the discoverers, followers and vigilants form a sparrow population;

[0121] A fitness function is constructed based on the Euclidean distance between constellation points. The Euclidean distance between constellation points is substituted into the fitness function to obtain a fitness value. The sparrow population is updated with the goal of maximizing the fitness value under constraints. The constraints are:

[0122] like hour, ;

[0123] In the formula, is the modulation phase of the kth constellation point, The outermost constellation point set in the current constellation diagram; is pi; is the phase offset;

[0124] Adjust the constellation point position according to the sparrow population; repeatedly iteratively adjust the first constellation optimization map using the sparrow search algorithm until the fitness value converges or the maximum number of iterations is reached to output the second constellation optimization map.

[0125] Example 3

[0126] This embodiment provides an electronic terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the hollow-core optical fiber communication method described in Example 1.

[0127] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0128] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0129] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0130] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0131] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A hollow-core optical fiber communication method for reducing complexity, characterized in that: include: Obtaining the original bit data to be sent, and mapping the original bit data to the initial constellation diagram through an orthogonal amplitude modulation mapping algorithm; The initial constellation diagram is rotated according to a preset rotation angle to obtain a first constellation optimization diagram, the first constellation optimization diagram is adjusted using a sparrow search algorithm to obtain a second constellation optimization diagram, the second constellation optimization diagram is converted into a transmission signal, and the transmission signal is transmitted to a receiving end through a hollow-core optical fiber; Data preprocessing is performed on the received transmission signal to obtain a denoised signal, phase recovery is performed on the denoised signal based on a quadratic algorithm to obtain a second constellation optimization graph, and the second constellation optimization graph is demapped and reconverted into original bit data.

2. The hollow-core optical fiber communication method according to claim 1, wherein: The original bit data is mapped to the initial constellation diagram through the orthogonal amplitude modulation mapping algorithm, which includes: Will The constellation points are distributed in an h-row and h-column grid on the complex plane to construct an initial constellation diagram; the original bit data is divided into bit groups according to the set number of bits, and Gray coding is used to map each bit group to a constellation point on the initial constellation diagram.

3. The hollow-core optical fiber communication method according to claim 1, wherein: The initial constellation diagram is rotated according to a preset rotation angle to obtain a first constellation optimization diagram, specifically including: The rotation factor is calculated according to the preset rotation angle, and the expression formula is: ； In the formula, is the rotation factor, is the rotation angle; j represents the imaginary unit; Multiply each constellation point in the initial constellation diagram by the rotation factor to obtain the first constellation optimization diagram.

4. The hollow-core optical fiber communication method according to claim 1, wherein: The first constellation optimization graph is adjusted using the sparrow search algorithm to obtain the second constellation optimization graph, specifically including: Each constellation point in the first constellation optimization graph is regarded as a sparrow individual, and the sparrow individuals are divided into discoverers, followers and vigilants; the discoverers, followers and vigilants form a sparrow population; A fitness function is constructed based on the Euclidean distance between constellation points. The Euclidean distance between constellation points is substituted into the fitness function to obtain a fitness value. The sparrow population is updated with the goal of maximizing the fitness value under constraints. The constraints are: like hour, ; In the formula, is the modulation phase of the kth constellation point, The outermost constellation point set in the current constellation diagram; is pi; is the phase offset; Adjust the constellation point position according to the sparrow population; repeatedly iteratively adjust the first constellation optimization map using the sparrow search algorithm until the fitness value converges or the maximum number of iterations is reached to output the second constellation optimization map.

5. The hollow-core optical fiber communication method according to claim 4, wherein: The sparrow population is updated with the goal of maximizing the fitness value under the constraints, including: According to the modulation phase Calculating the exploration vector , randomly generate the first unit vector Q, and use the first unit vector Q and the exploration vector Update the discoverer's position, the expression formula is: ； In the formula, is the finder position of the k-th constellation point in the t-th iteration, is the finder position of the k-th constellation point in the t-1-th iteration; is the step size coefficient; is the outermost constellation point set in the current constellation diagram; I is the inner constellation point set in the current constellation diagram; Substitute the positions of the discoverer, follower and sentinel in the t-1th iteration into the fitness function to obtain the optimal sparrow individual position corresponding to the maximum fitness value ; According to the optimal individual position of sparrows Update the follower position, the expression formula is: ； In the formula, is the follower position of the k-th constellation point in the t-th iteration; is the follower position of the k-th constellation point in the t-1-th iteration; is the learning coefficient; Randomly generate a second unit vector , according to the second unit vector Update the position of the sentinel, and the expression formula is: ； In the formula, is the position of the sentinel at the kth constellation point in the tth iteration; is the position of the sentinel at the kth constellation point in the t-1th iteration; Is the warning factor.

6. The hollow-core optical fiber communication method according to claim 5, wherein: Substitute the positions of the discoverer, follower and sentinel in the t-1th iteration into the fitness function to obtain the optimal sparrow individual position corresponding to the maximum fitness value , specifically including: ； ； ； ； In the formula, For the location of the discoverer, the follower and the vigilant, is the constellation diagram output by the t-1th iteration, 、 、 and is the constellation point coordinate vector corresponding to the position of the individual sparrow; 、 、 and is the constellation point number; Output the outermost constellation point set in the constellation diagram for the t-1th iteration, Output the set of inner constellation points in the constellation diagram for the t-1th iteration; is the fitness value, and To set weights; The minimum Euclidean distance between the four outermost constellation points in the current constellation diagram; It is the minimum Euclidean distance of the inner constellation points in the current constellation diagram.

7. The hollow-core optical fiber communication method according to claim 1, wherein: Performing data preprocessing on the received transmission signal to obtain a denoised signal, specifically including: The received transmission signal is input into a low-pass filter to suppress additive Gaussian white noise: the expression formula is: ； ； ； In the formula, represents the kth transmission signal sent by the transmitter; represents the symbol amplitude corresponding to the k-th constellation point in the second constellation optimization diagram, represents the symbol phase corresponding to the k-th constellation point in the second constellation optimization diagram; is the additive white Gaussian noise of the k-th transmission signal; is the phase noise of the kth transmitted signal; is the kth transmission signal after noise reduction; is the kth transmission signal received; A phase-locked loop is used to recover the clock and frequency of the transmission signal to obtain the denoised signal.

8. The hollow-core optical fiber communication method according to claim 7, wherein: The second constellation optimization graph is obtained by performing phase recovery on the denoised signal based on the quadratic algorithm, specifically including: The phase noise of the denoised signal is extracted based on the quadratic algorithm, and the expression formula is: ； In the formula, is the kth denoised signal; represents the symbol amplitude corresponding to the k-th constellation point in the second constellation optimization diagram; is pi; is the phase noise of the kth denoised signal; is the phase offset; According to the phase noise Phase compensation is performed on the kth denoised signal to obtain a second constellation optimization graph.

9. A hollow-core optical fiber communication system for reducing complexity, characterized in that: include: The transmitting module is used to obtain the original bit data to be sent and map the original bit data to the initial constellation diagram through the orthogonal amplitude modulation mapping algorithm; An optimization module, configured to rotate the initial constellation diagram according to a preset rotation angle to obtain a first constellation optimization diagram, and adjust the first constellation optimization diagram using a sparrow search algorithm to obtain a second constellation optimization diagram; a transmission module, configured to convert the second constellation optimization graph into a transmission signal, and transmit the transmission signal to the receiving end through a hollow-core optical fiber; The receiving module is used to perform data preprocessing on the received transmission signal to obtain a denoised signal, perform phase recovery on the denoised signal based on a quadratic algorithm to obtain a second constellation optimization map, and demap the second constellation optimization map and reconvert it into original bit data.

10. An electronic terminal, characterized in that: It comprises a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the hollow-core optical fiber communication method according to any one of claims 1 to 8.

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