Dimension-level constellation disassembly transmission method based on high-dimensional constellation selective mapping

Abstract

The invention discloses a dimension-level constellation disassembly transmission method based on high-dimensional constellation selective mapping, and belongs to the technical field of optical fiber communication. The method comprises the steps that a traditional high-dimensional constellation is constructed, the number of constellation points needing to be extracted is determined through an entropy limit adaptive tuning function, then needed constellation points are extracted from the traditional high-dimensional constellation, and a shaped high-dimensional constellation is obtained; performing dimension-level disassembly on the shaped high-dimensional constellation to obtain a low-dimensional constellation set; performing phase conversion on the low-dimensional constellation set, and transmitting the converted low-dimensional constellation set to a channel for transmission in a spherical coordinate And receiving the low-dimensional constellation set at a receiving end, combining and restoring the low-dimensional constellation set into a high-dimensional constellation, and performing corresponding judgment on the high-dimensional constellation to obtain bit data. Part of constellation points are selected from a high-dimensional constellation to carry out data bearing and transmission, and the Euclidean distance between the constellation points is increased to reduce the bit error rate. And a high-dimensional constellation is disassembled into a low-dimensional constellation set for transmission in the form of a spherical coordinate system, so that the bit error rate rise caused by relatively large influence of a channel on transmission is avoided.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of optical fiber communication, and particularly relates to a dimension-level constellation disassembling transmission method based on high-dimensional constellation selective mapping. BACKGROUND

[0002] High-dimensional constellation modulation technology can well improve information rate, capacity and spectrum efficiency. In constellation modulation technology, ordinary two-dimensional constellation or even three-dimensional constellation can hardly meet the demand of large-capacity information transmission, and therefore a higher-dimensional constellation is needed to process information. High-dimensional (dimension >= 4) constellation can provide more data points or symbols to represent different bit information. Under the same time and bandwidth conditions, high-dimensional constellation can transmit more data and improve data transmission rate. At the same time, high-dimensional constellation can transmit more information under limited spectrum resources, greatly improving the utilization rate of spectrum and the efficiency of communication system. With the increase of dimension, the minimum Euclidean distance of the same number of constellation points will also increase, and the larger minimum Euclidean distance can better improve the noise immunity of the constellation. However, with the increase of the number of constellation points, the noise influence in transmission is also greater.

[0003] Therefore, the dimension-level constellation disassembling transmission method based on high-dimensional constellation selective mapping is proposed. SUMMARY

[0004] In view of the deficiencies of the prior art, the purpose of the application is to provide a dimension-level constellation disassembling transmission method based on high-dimensional constellation selective mapping, which solves the problems in the prior art.

[0005] The purpose of the application can be achieved by the following technical solutions.

[0006] The dimension-level constellation disassembling transmission method based on high-dimensional constellation selective mapping comprises the following steps:

[0007] A traditional high-dimensional constellation is constructed, the number of constellation points needed to be extracted is determined by an entropy limit self-adaptive tuning function, then the required constellation points are extracted from the traditional high-dimensional constellation to obtain a reshaped high-dimensional constellation;

[0008] The reshaped high-dimensional constellation is disassembled at the dimension level to obtain a low-dimensional constellation set;

[0009] The low-dimensional constellation set is converted in phase and sent into a channel in the form of a spherical coordinate system; at the receiving end, the low-dimensional constellation set is combined and restored into a high-dimensional constellation, and corresponding decision is made on the high-dimensional constellation to obtain bit data.

[0010] Further, the dimension of the high-dimensional constellation is >= 4, and the dimension of the low-dimensional constellation is <= 3.

[0011] Further, the expression of the determination of the number of constellation points to be extracted is:

[0012]

[0013] wherein N(s) is a constellation point selection function, floor is a down rounding, M represents the original number of constellation points of the modulation mode, η represents the channel sensitivity, μ max represents the maximum theoretical spectral efficiency, κ is a normalized entropy power coefficient; S is a dynamic tuning input parameter.

[0014] Further, the process of extracting the required constellation points includes that each constellation point in the traditional high-dimensional constellation is marked with a number, and then the constellation points are selected by a random number array.

[0015] Further, the process of dimension-level disassembly of the shaped high-dimensional constellation includes that the shaped high-dimensional constellation is disassembled into a plurality of independent low-dimensional constellations by orthogonal projection to form a low-dimensional constellation set.

[0016] Further, the process of phase conversion of the low-dimensional constellation set includes that the position of the constellation point is determined by constructing a spherical coordinate system and using the phase angle and the elevation angle.

[0017] The dimension-level constellation disassembly transmission system based on high-dimensional constellation selective mapping includes:

[0018] The constellation shaping module: a traditional high-dimensional constellation is constructed, the number of constellation points to be extracted is determined by an entropy limit adaptive tuning function, and then the required constellation points are extracted from the traditional high-dimensional constellation to obtain a shaped high-dimensional constellation;

[0019] The dimension-level disassembly module: the shaped high-dimensional constellation is disassembled at the dimension level to obtain a low-dimensional constellation set;

[0020] The transmission module: the low-dimensional constellation set is phase-converted and sent into the channel in the form of a spherical coordinate system; at the receiving end, the low-dimensional constellation set is combined to restore the high-dimensional constellation, and the high-dimensional constellation is judged to obtain the bit data.

[0021] A computer storage medium stores a readable program, when the program runs, the program can instruct a computing device to execute the above-mentioned dimension-level constellation disassembly transmission method based on high-dimensional constellation selective mapping.

[0022] An electronic device includes a processor, a memory, a communication interface and a communication bus, the processor, the memory and the communication interface complete the communication among each other through the communication bus;

[0023] The memory is used to store at least one executable instruction, and the executable instruction makes the processor execute the operation corresponding to the high-dimensional constellation selective mapping dimension-level constellation disassembly transmission method.

[0024] A computer program product comprises computer instructions instructing a computing device to execute the operation corresponding to the high-dimensional constellation selective mapping dimension-level constellation disassembly transmission method.

[0025] The beneficial effects of the present application are:

[0026] 1. The present application uses a constellation point selection method to select part of the constellation points in the high-dimensional constellation for data carrying and transmission. This method can increase the Euclidean distance between the constellation points and thus reduce the bit error rate.

[0027] 2. The present application disassembles the high-dimensional constellation to obtain a low-dimensional constellation set. The low-dimensional constellation set is sent to the channel in the form of a spherical coordinate system for transmission, which can well avoid the situation that the high-dimensional and high-order constellation is greatly affected by the channel during transmission and thus the bit error rate rises. BRIEF DESCRIPTION OF DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without any creative effort.

[0029] Figure 1 is the flow chart of the high-dimensional constellation selective mapping dimension-level constellation disassembly transmission method of the present application;

[0030] Figure 2 is the constellation point layout chart before and after the four-dimensional constellation shaping of the present application;

[0031] Figure 3 is the 8 constellation point schematic diagram under different coordinate systems of the present application;

[0032] Figure 4 is the bit error rate gain under different SNRs of the present application. DETAILED DESCRIPTION

[0033] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without any creative effort are within the scope of protection of the present application.

[0034] Embodiment 1

[0035] As shown in Figure 1 , the dimension-level constellation disassembly transmission method based on high-dimensional constellation selective mapping includes the following steps:

[0036] S1, a traditional high-dimensional constellation is constructed, the number of constellation points needed to be extracted is determined by an entropy limit adaptive tuning function, and then the required constellation points are extracted from the traditional high-dimensional constellation to obtain a shaped high-dimensional constellation;

[0037] Geometric shaping technology is widely used because it can achieve high receiving sensitivity and flexibility while maintaining low complexity. By adjusting and distributing the constellation point positions through geometric constellation shaping technology, and considering factors such as minimum Euclidean distance (MED), channel noise, and symmetry, the spectral utilization and transmission performance of the system can be effectively improved. On this basis, in order to further improve the anti-interference ability in the constellation transmission process, a dimension-level disassembly technology will be used to process the high-dimensional constellation. The dimension-level disassembly technology disassembles the high-dimensional constellation into multiple low-dimensional constellations and transmits them into the channel. Low-dimensional constellations have stronger anti-interference ability than high-dimensional constellations, so disassembling high-dimensional constellations into multiple low-dimensional constellations can effectively reduce the impact of noise on high-dimensional constellations in the channel, significantly improving the anti-interference ability and reliability of the system.

[0038] S11, construct an entropy limit adaptive tuning function and confirm the number of constellation points;

[0039] When constructing a high-dimensional constellation, the order of the constructed high-dimensional constellation needs to be determined first. This embodiment takes a 4D-4096 constellation diagram as an example. As shown in Figure 2 , where Figure 2 (a) in the above figure is a traditional 4D-4096 constellation diagram. Based on this constellation diagram, an entropy limit adaptive tuning function is used to limit the number of selected constellation points in the high-dimensional constellation. The entropy limit adaptive tuning function dynamically adjusts the channel state, with information entropy as the core driver, and adjusts the size of the constellation point subset according to the demand, to achieve the optimal balance between spectral efficiency and transmission reliability. By changing the entropy limit adaptive tuning function, different numbers of constellation points are selected according to different environments to achieve dynamic adjustment. The entropy limit adaptive tuning function is shown in formula (1):

[0040]

[0041] where N(s) is the constellation point selection function, floor is the floor function, M represents the original number of constellation points of the modulation mode, η represents the channel sensitivity, μ maxκ represents the maximum theoretical spectral efficiency, and κ is the normalized entropy power coefficient, used to balance the difference between information entropy and signal power. S is the dynamic tuning input parameter, which dynamically adjusts the number of constellation points selected based on externally input system state indicators. As the value of S decreases, the value of N also decreases, meaning the number of selected constellation points decreases. With a decrease in the number of constellation points, the Euclidean distance between them increases, resulting in better sensitivity gain. However, a decrease in the number of constellation points also leads to a loss of spectral resources. Therefore, different numbers of constellation points can be selected according to different scenarios to meet different needs.

[0042] Taking the 4D-4096 constellation point as an example, first assign values ​​to the parameters in the formula, letting M = 4096, μ max =12, κ=In2, η=2, the variable S can be flexibly adjusted according to factors such as the information transmission environment and the strength of noise interference. When the channel quality is poor, S is set to 5, that is, 512 constellation points are selected, thereby improving the noise immunity of the constellation; when the channel quality is good, S can be set to 10, that is, 1024 constellation points are selected, thereby improving the transmission capacity.

[0043] S12 Constellation Point Extraction

[0044] After determining the required number of constellation points, the points need to be selected and extracted. First, each constellation point in a traditional high-dimensional constellation is labeled with a number. Then, a random number array is used to select the constellation points, resulting in constellations as follows: Figure 2 As shown in (b) above. This completes the design and extraction of the high-dimensional constellation, resulting in the shaped high-dimensional constellation.

[0045] S2, decompose the high-dimensional constellations after the transformation at the dimensional level to obtain a set of low-dimensional constellations;

[0046] After obtaining the shaped high-dimensional constellation, directly transmitting it into the channel would result in greater noise interference and reduced transmission quality compared to lower-dimensional, lower-order constellations. Therefore, based on the shaped high-dimensional constellation, it is further decomposed at the dimensional level. This dimensional decomposition yields a set composed of multiple lower-dimensional, lower-order constellations.

[0047] In this embodiment, the above-mentioned 4D-1024 constellation point constellation diagram (the shaped high-dimensional constellation) is used as an example.

[0048] The 4D-1024 constellation contains four dimensions: W, X, Y, and Z, with eight coordinate points in each dimension. Based on the principle of dimension matching, the 3D-8 constellation is selected as the dimensional data carrier unit. Through orthogonal projection, the original four-dimensional constellation (the shaped four-dimensional constellation) is decomposed into four independent three-dimensional constellations, forming a three-dimensional constellation set. This dimensionality reduction process effectively disperses the cumulative effect of noise interference by reducing the constellation density of each transmission unit.

[0049] S3 transforms the phase of the low-dimensional constellation set and sends it into the channel for transmission in spherical coordinates; at the receiving end, the low-dimensional constellation set is received, combined and restored into a high-dimensional constellation, and the high-dimensional constellation is judged accordingly to obtain bit data.

[0050] Transmitting a low-dimensional constellation set through phase conversion into a channel can effectively reduce noise interference and thus achieve better performance.

[0051] This embodiment utilizes a two-degree-of-freedom phase transformation method to process a three-dimensional constellation set. This method constructs a spherical coordinate system and uses phase and elevation angles to determine the positions of constellation points. The phase-transformed constellation diagram can better enhance the linear correlation characteristics between adjacent constellation points. For example... Figure 3 In (a) of the diagram, constellation points 1 and 3 differ in both x and y parameters in Cartesian coordinates. However, in spherical coordinates, only θ differs. Figure 3 As shown in (b), the process from constellation point 3 to constellation point 1 in spherical coordinates is a phase angle change... Increase to The process of linear increase.

[0052] This linear variation characteristic of the phase angle parameter allows the receiver to more accurately locate the spatial coordinates of high-dimensional constellation points when restoring a low-dimensional constellation set to a high-dimensional constellation through the phase continuity feature, thereby improving the overall performance of signal demodulation.

[0053] In this embodiment, the dimension of the high-dimensional constellation is 4, and the dimension of the low-dimensional constellation is 3; in other embodiments, the dimension of the high-dimensional constellation can be greater than 4, and the dimension of the low-dimensional constellation can be 1 or 2.

[0054] Based on a similar inventive concept, embodiments of the present invention also provide a computer storage medium storing a readable program that, when run by a processor, can execute the above-described method for dimensional constellation disassembly and transmission based on high-dimensional constellation selective mapping.

[0055] Based on a similar inventive concept, this invention provides an electronic device, including: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus;

[0056] The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the above-described dimension-level constellation disassembly and transmission method based on high-dimensional constellation selective mapping.

[0057] Based on a similar inventive concept, embodiments of the present invention also provide a computer program product, including computer instructions, which instruct a computing device to perform the operations corresponding to the above-described dimensional constellation disassembly and transmission method based on high-dimensional constellation selective mapping.

[0058] Example 2

[0059] In this embodiment, the high-dimensional constellation disassembly and transmission method is simulated and verified.

[0060] Simulation experiments were conducted in the MATLAB system to verify the results. A pseudo-random binary sequence was generated using a MATLAB program as the original data. The effective subcarrier number was set to 2^16, and the number of inverse Fourier transform points was set to 512. Each orthogonal frequency division multiplexing (OFDM) symbol was given a cyclic prefix with a length of 1 / 16 of the OFDM symbol. After the constellation was split and overlapped, the signal was loaded into an arbitrary waveform generator at a rate of 25 GSa / s for digital-to-analog conversion. After linear amplification by an electrical amplifier, the analog signal was used to drive a Mach-Zehnder modulator. A laser generated a 1550 nm optical carrier for optical signal modulation. The modulated optical signal was amplified by an erbium-doped fiber amplifier, split into 7 beams by an optical coupler, and then input into a 2 km 7-core optical fiber through a fan-in device. The used fiber was a weakly coupled 7-core fiber with a single core diameter of 8 μm and a core spacing of 41.5 μm. The coating diameter was 245 μm, and the cladding diameter was 150 μm. The average insertion loss per fiber core is approximately 1.5 dB, and the crosstalk between adjacent fiber cores is less than -50 dB. At the receiver, a variable optical attenuator is used to adjust the received optical power. Photodiodes are used for signal detection. After analog-to-digital conversion using a mixed-signal oscilloscope with a sampling rate of 50 GSa / s, offline DSP processing is performed to recover the original data.

[0061] Data obtained through simulation, such as Figure 4 As shown. Figure 4The graph illustrates the gain of constellations with selected constellation points compared to traditional constellations under different signal-to-noise ratios (SNR). As the SNR increases, the bit error rate (BER) decreases under various conditions. Furthermore, the fewer constellation points selected in a high-dimensional constellation, the higher the gain at the same SNR. This is because, in the same spatial context, fewer constellation points result in a larger Euclidean distance between constellations, which effectively reduces the BER. Simultaneously, the reduced number of constellation points allows for better Gray code encoding at the coding level, further lowering the BER.

[0062] Example 3

[0063] A dimensional constellation decomposition and transmission system based on high-dimensional constellation selective mapping specifically includes:

[0064] Constellation Shaping Module: Construct a traditional high-dimensional constellation, determine the number of constellation points to be extracted through an entropy-limited adaptive tuning function, and then extract the required constellation points from the traditional high-dimensional constellation to obtain the shaped high-dimensional constellation;

[0065] Dimensional decomposition module: Performs dimensional decomposition on the reshaped high-dimensional constellations to obtain a set of low-dimensional constellations;

[0066] Transmission module: After phase transformation of the low-dimensional constellation set, it is sent into the channel for transmission in spherical coordinates; at the receiving end, the low-dimensional constellation set is received, combined and restored into a high-dimensional constellation, and the corresponding decision is made on the high-dimensional constellation to obtain bit data.

[0067] The methods of the present invention can be implemented in hardware, firmware, or as software or computer code that can be stored in a recording medium (such as a CD-ROM, RAM, floppy disk, hard disk, or magneto-optical disk), or as computer code originally stored on a remote recording medium or a non-transitory machine-readable medium and subsequently stored on a local recording medium, downloaded via a network. Thus, the methods described herein can be processed by software stored on a recording medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware (such as an ASIC or FPGA). It is understood that the computer, processor, microprocessor controller, or programmable hardware includes storage components (e.g., RAM, ROM, flash memory, etc.) capable of storing or receiving software or computer code that, when accessed and executed by the computer, processor, or hardware, implements the methods described herein. Furthermore, when a general-purpose computer accesses the code used to implement the methods shown herein, the execution of the code transforms the general-purpose computer into a dedicated computer for performing the methods shown herein.

[0068] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A dimensional constellation decomposition and transmission method based on high-dimensional constellation selective mapping, characterized in that, Includes the following steps: Construct a traditional high-dimensional constellation, determine the number of constellation points to be extracted using an entropy-limited adaptive tuning function, and then extract the required constellation points from the traditional high-dimensional constellation to obtain the shaped high-dimensional constellation. The high-dimensional constellations after the transformation are decomposed at the dimensional level to obtain a set of low-dimensional constellations; The low-dimensional constellation set is phase-transformed and sent into the channel for transmission in spherical coordinates. At the receiving end, the low-dimensional constellation set is received, combined and restored into a high-dimensional constellation, and the high-dimensional constellation is judged accordingly to obtain bit data.

2. The dimension-level constellation decomposition and transmission method based on high-dimensional constellation selective mapping according to claim 1, characterized in that, The dimensions of the higher-dimensional constellations are ≥4, and the dimensions of the lower-dimensional constellations are ≤3.

3. The dimension-level constellation decomposition and transmission method based on high-dimensional constellation selective mapping according to claim 1, characterized in that, The expression for determining the constellation points to be extracted is: Where N(s) is the constellation point selection function, floor is the floor function, M represents the original number of constellation points for the modulation scheme, η represents the channel sensitivity, and μ max κ represents the maximum theoretical spectral efficiency, S represents the normalized entropy power coefficient, and S represents the dynamic tuning input parameter.

4. The dimension-level constellation decomposition and transmission method based on high-dimensional constellation selective mapping according to claim 2, characterized in that, The process of extracting the required constellation points includes: labeling each constellation point in a traditional high-dimensional constellation with a numerical tag, and then selecting the constellation points using a random number array.

5. The dimension-level constellation decomposition and transmission method based on high-dimensional constellation selective mapping according to claim 2, characterized in that, The process of decomposing the reshaped high-dimensional constellation at the dimensional level includes: decomposing the reshaped high-dimensional constellation into multiple independent low-dimensional constellations through orthogonal projection, forming a set of low-dimensional constellations.

6. The dimension-level constellation decomposition and transmission method based on high-dimensional constellation selective mapping according to claim 2, characterized in that, The process of phase transformation of the low-dimensional constellation set includes: determining the position of constellation points by constructing a spherical coordinate system and using phase angles and elevation angles.

7. A dimension-level constellation decomposition and transmission system based on high-dimensional constellation selective mapping, characterized in that, include: constellation The shaping module constructs a traditional high-dimensional constellation, determines the number of constellation points to be extracted through an entropy-limited adaptive tuning function, and then extracts the required constellation points from the traditional high-dimensional constellation to obtain the shaped high-dimensional constellation. Dimensional decomposition module: Performs dimensional decomposition on the shaped high-dimensional constellations to obtain a set of low-dimensional constellations; Transmission module: After phase transformation of the low-dimensional constellation set, it is sent into the channel for transmission in spherical coordinates; at the receiving end, the low-dimensional constellation set is received, combined and restored into a high-dimensional constellation, and the corresponding decision is made on the high-dimensional constellation to obtain bit data.

8. A computer storage medium storing a readable program, characterized in that, When the program runs, it can instruct the computing device to execute the dimension-level constellation disassembly and transmission method based on high-dimensional constellation selective mapping as described in any one of claims 1-6.

9. An electronic device, characterized in that, include: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the dimension-level constellation disassembly and transmission method based on high-dimensional constellation selective mapping as described in any one of claims 1-6.

10. A computer program product comprising computer instructions, characterized in that, The computer instructions instruct the computing device to perform the operation corresponding to the dimension-level constellation disassembly and transmission method based on high-dimensional constellation selective mapping as described in any of claims 1-6.

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