Extensible constellation construction method and system and signal transmission method
By using parallel cross geometry to generate and filter candidate constellation point sets, the problems of compact symbol point distribution and design efficiency in high-order constellation modulation are solved, achieving higher constellation gain index and noise immunity, and simplifying the design process.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-25
- Publication Date
- 2026-04-07
AI Technical Summary
Existing technologies struggle to achieve a compact symbol point distribution in high-order constellation modulation while maintaining a constant minimum Euclidean distance. This results in high average symbol energy, limited room for improvement in constellation gain exponent, and significant computational resource consumption and inconsistent results during the design process.
Using a parallel intersecting geometric structure as the basic framework of the constellation, and by generating and filtering candidate constellation point sets, the minimum Euclidean distance is kept constant, resulting in a compact and symmetrical constellation point set, which is suitable for multi-order constellation construction.
This approach achieves a more compact constellation point layout under the same distance constraint, improves the constellation gain index and noise immunity, reduces the average symbol energy, simplifies the design process, and enhances design efficiency and result reproducibility.
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Figure CN121809022A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of communication technology, and in particular to a scalable constellation construction method, system, and signal transmission method. Background Technology
[0002] In modern high-speed digital communication systems, high-order constellation modulation, with its advantages of balancing high bandwidth efficiency and noise immunity under limited spectrum resources, is widely used in technologies such as Orthogonal Frequency Division Multiplexing (OFDM), Orthogonal Code Division Multiplexing (OCDM), and single-carrier coherent transmission. With the rapid growth of big data, cloud computing, and ultra-high-definition video services, the requirements for constellation density and energy efficiency in communication links are constantly increasing. While the current mainstream three-dimensional cube constellation can achieve simple deployment due to its regular three-dimensional grid distribution and analytical coordinate representation, it suffers from a relatively small number of equidistant nearest neighbors and a relatively loose symbol distribution while maintaining a constant minimum Euclidean distance (MED). This makes it difficult to effectively reduce the average symbol energy and limits the potential for improving the constellation figure of merit (CFM), making it difficult to meet the stringent requirements of higher-order modulation for energy efficiency and link tolerance.
[0003] To overcome this bottleneck, the industry has begun to treat the position of the symbol points as degrees of freedom, transforming the constellation layout problem into a multidimensional optimization problem. This involves placing the candidate symbol set in an adjustable geometric space and using numerical iteration to find configurations with lower energy and better neighbor relationships. Such methods typically require repeated initialization of the point set, adjustment of control parameters, and long-term searches on complex multi-peak energy surfaces to achieve a balance between local and global optima. While some performance improvement can be achieved with a single point number, this process is highly sensitive to initial conditions and algorithmic strategies. Furthermore, whenever the constellation order changes, the entire iterative process must be re-executed, consuming significant computational resources. The consistency of the generated results is also difficult to guarantee, making online or large-scale deployment challenging.
[0004] Meanwhile, hand-constructed geometric schemes for a limited number of specific orders are also emerging. Designers analyze geometric symmetry and manually combine basic units to achieve a more compact point cloud distribution by fine-tuning parameters. While this method can achieve excellent CFM and power performance in individual cases, its design approach often requires re-deriving the skeleton structure and key parameters for each order and verifying them through tedious simulation experiments. A more practical problem is that real-world hardware platforms, such as Field-Programmable Gate Arrays (FPGAs) and Application Specific Integrated Circuits (ASICs), are extremely sensitive to the fixed-point representation and lookup table methods of coordinates. Even slight truncation, rotation, or quantization errors can cause the MED to deviate from the preset value or trigger nonlinear distortion, making it difficult to demonstrate theoretical performance in real-world environments. Summary of the Invention
[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a scalable constellation construction method, system and signal transmission method. Under the premise of strictly ensuring the minimum distance, it realizes the unified construction of multi-order constellations under the same process, significantly improves symbol energy utilization and CFM, and at the same time takes into account design efficiency and result reproducibility.
[0006] To achieve the above objectives, the present invention is implemented using the following technical solution:
[0007] On one hand, the present invention provides a scalable constellation construction method, comprising:
[0008] Two parallel line segments in three-dimensional space are used as the basic geometric units;
[0009] In the horizontal plane, one line segment in the geometric basic unit is rotated to be perpendicular to another line segment, and in the vertical plane, the distance between the two line segments in the geometric basic unit is compressed to obtain a parallel intersecting geometric structure.
[0010] Using parallel intersecting geometric structures as the basic framework of constellations, a set of candidate constellation points is generated on the basic framework of constellations;
[0011] The candidate constellation point set is filtered according to the preset minimum Euclidean distance to obtain the constellation point set;
[0012] An expandable constellation map is generated based on the constellation point set.
[0013] Optionally, using parallel intersecting geometry as the basic constellation framework, a set of candidate constellation points on the basic constellation framework is generated, including:
[0014] Generate the minimum coordinate step size based on the preset minimum Euclidean distance;
[0015] Based on the minimum coordinate step size, a set of candidate constellation points is generated that are symmetrically distributed in odd multiples of each coordinate axis in a three-dimensional rectangular coordinate system.
[0016] Optionally, the formula for the minimum coordinate step size is:
[0017] ;
[0018] in, Indicates the minimum coordinate step size; This represents the preset minimum Euclidean distance.
[0019] Optionally, the coordinate formula for the candidate constellation point set is:
[0020] ;
[0021] ;
[0022] in, Describes the set of one-witness number lattice points representing the candidate constellation point set; Represents the candidate constellation point set; Represents the set of all integers; Represents a constant; Indicates the minimum coordinate step size; This represents the coordinates of the i-th candidate constellation point in the candidate constellation point set.
[0023] Optionally, the candidate constellation point set is filtered according to a preset minimum Euclidean distance to obtain a constellation point set, including:
[0024] Calculate the Euclidean distance from each candidate constellation point in the candidate constellation point set to the origin of the coordinate system, and arrange the candidate constellation points in ascending order of Euclidean distance;
[0025] The selection process begins with choosing the candidate constellation point with the smallest Euclidean distance. Initially, the set of selected constellation points is empty. The candidate constellation point with the smallest Euclidean distance is directly added to the set of selected constellation points. For other candidate constellation points, the Euclidean distances between them and all constellation points in the set of selected constellation points are calculated, and the minimum Euclidean distance is selected. ;;
[0026] like If so, then discard that candidate constellation point;
[0027] like If so, then add the candidate constellation point to the constellation point set;
[0028] in, This represents the preset minimum Euclidean distance.
[0029] Optionally, calculate the Euclidean distance from each candidate constellation point in the candidate constellation point set to the origin, using the following formula:
[0030] ;
[0031] in, This represents the Euclidean distance from the i-th candidate constellation point in the candidate constellation point set to the origin. This represents the coordinates of the i-th candidate constellation point in the candidate constellation point set.
[0032] Secondly, this invention provides a scalable constellation building system, comprising:
[0033] The basic unit acquisition module is used to: take two parallel line segments in three-dimensional space as geometric basic units;
[0034] The geometric structure construction module is used to: rotate one line segment in the geometric basic unit to be perpendicular to another line segment in the horizontal plane, and compress the distance between two line segments in the geometric basic unit in the vertical plane to obtain a parallel intersecting geometric structure;
[0035] The candidate generation module is used to generate a set of candidate constellation points on the basic constellation skeleton, using the parallel intersecting geometric structure as the basic skeleton of the constellation.
[0036] The constellation point filtering module is used to: filter the candidate constellation point set according to the preset minimum Euclidean distance to obtain the constellation point set;
[0037] The constellation graph construction module is used to generate an expandable constellation graph based on the constellation point set.
[0038] Thirdly, the present invention provides a signal transmission method for a communication system, comprising:
[0039] Acquire the bit signal to be transmitted;
[0040] The bit signal to be transmitted is mapped onto a set of constellation points in an expandable constellation diagram to generate a three-dimensional constellation symbol;
[0041] The three-dimensional constellation symbol is subjected to digital-to-analog conversion and signal modulation to obtain a modulated signal;
[0042] The modulated signal is input into the communication channel for signal transmission;
[0043] The scalable constellation diagram is obtained using the scalable constellation construction method described in the first aspect.
[0044] Fourthly, the present invention provides a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implements the steps of the scalable constellation construction method described in the first aspect.
[0045] Fifthly, the present invention provides a computer device, comprising:
[0046] Memory, used to store computer programs / instructions;
[0047] A processor for executing the computer program / instructions to implement the steps of the scalable constellation construction method described in the first aspect.
[0048] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:
[0049] In terms of scalability, this invention relies on a parallel cross geometric skeleton and candidate constellation point set generation mechanism. Whether it is a 16-point, 32-point, or 64-point constellation, it can be quickly obtained through the same generation framework, avoiding the repetitive work of redesigning and verifying for different orders, significantly shortening the design cycle, and reducing R&D and implementation costs. In terms of performance, by strictly maintaining a constant minimum Euclidean distance during the generation process and optimizing the spatial distribution of candidate points, the final constellation has more equidistant nearest neighbor points under the same distance constraint, thereby significantly improving constellation compactness and CFM, effectively reducing average symbol energy, and improving the noise resistance and system sensitivity of the link. Attached Figure Description
[0050] Figure 1 The diagram shown is a flowchart of one embodiment of the scalable constellation construction method of the present invention;
[0051] Figure 2 The diagram shown illustrates the generation process of the parallel intersecting geometric structure of the present invention in one embodiment.
[0052] Figure 3 The diagram shown illustrates the generation process of a Cube constellation diagram in one embodiment.
[0053] Figure 4 The diagram shown is a schematic representation of the generation process of the constellation diagram of the parallel intersecting geometric structure of the present invention in one embodiment.
[0054] Figure 5 The diagram shown is a three-dimensional distribution schematic of a Cube constellation diagram in one embodiment;
[0055] Figure 6 The diagram shown is a three-dimensional distribution schematic of the constellation diagram of the parallel intersecting geometric structure of the present invention in one embodiment. Detailed Implementation
[0056] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations thereof. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.
[0057] The term "and / or" simply describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.
[0058] Example 1
[0059] like Figure 1 As shown in the figure, this embodiment introduces a scalable constellation construction method, including the following steps:
[0060] Step 1: Geometric skeleton construction, specifically:
[0061] Construct a geometric structure with symmetry and parallel intersection features in three-dimensional space as the basic framework for constellation layout;
[0062] like Figure 2 As shown, in three-dimensional space, two parallel line segments are used as the basic geometric units:
[0063] First, in the horizontal plane, rotate one of the line segments in the geometric basic unit by 90° relative to the other line segment so that the two line segments are perpendicular to each other in the horizontal plane;
[0064] Then, in the vertical plane, the distance between two straight line segments in the compressed geometric basic unit is used to obtain a parallel intersecting geometric structure, so that their endpoints form an intersecting polygonal structure in space.
[0065] The parallel intersecting geometry obtained in this way appears as two sets of parallel line segments in the front view and as mutually perpendicular intersections in the top view. Therefore, it is called a parallel intersecting skeleton. Before rotation, the distance between the two endpoints of any line segment is 2, and the distance between the two line segments is 2. After rotation, the distance between the two endpoints of any line segment remains 2, and the distance between the two line segments remains 2, thus ensuring that the minimum Euclidean distance of the configuration remains unchanged. After compression, the distance between the two endpoints of any line segment remains 2, and the distance between the two line segments is compressed to 1.414. This distance can be set according to actual needs.
[0066] The formation process of parallel intersecting geometric structures is as follows: Figure 2As shown, two sets of parallel straight line segments are rotated and compressed relative to each other in the vertical direction to form a parallel intersecting geometric structure, which serves as the basic framework of the constellation.
[0067] This skeletal structure possesses high symmetry and can be expanded to a larger spatial range through translation and symmetrical replication along the three-dimensional coordinate axes. This provides a basic framework for constructing three-dimensional compact constellations of arbitrary order. Compared with traditional cubic skeletons, parallel intersecting skeletons can provide more nearest neighbors in more directions for each point, improving the connection density between points and space utilization, thus laying a geometric foundation for enhancing the geometric compactness and performance of constellations.
[0068] Step 2: Candidate constellation point generation, specifically:
[0069] Using parallel intersecting geometric structures as the basic framework of constellations, a set of candidate constellation points is generated on the basic framework of constellations;
[0070] To uniformly describe the geometric characteristics of the parallel intersecting skeleton series constellations, a preset minimum Euclidean distance is first defined as... According to the preset minimum Euclidean distance Generate minimum coordinate step size The formula is:
[0071] .
[0072] In a three-dimensional Cartesian coordinate system, the candidate constellation points in the candidate constellation point set must satisfy the condition of being symmetrically distributed in odd multiples along each coordinate axis. Therefore, using the minimum coordinate step size, the three components of the candidate constellation points are taken from the set:
[0073] ;
[0074] Based on this, an infinitely extended pool of candidate constellation points can be constructed:
[0075] ;
[0076] in, Describes the set of one-witness number lattice points representing the candidate constellation point set; Represents the candidate constellation point set; Represents the set of all integers; Represents a constant; This represents the coordinates of the i-th candidate constellation point in the candidate constellation point set.
[0077] Therefore, the distance between any two adjacent candidate constellation points along the same coordinate axis is 1. This ensures the minimum geometric interval between candidate constellation points.
[0078] Step 3: Euclidean distance constraint screening, specifically:
[0079] To accurately select constellation points that satisfy the minimum Euclidean distance constraint from the above candidate constellation point set, the following two-step screening process is adopted:
[0080] First, calculate the Euclidean distance from each candidate constellation point in the candidate constellation point set to the origin of the coordinate system, and then arrange the candidate constellation points in ascending order of Euclidean distance;
[0081] Euclidean distance from the i-th candidate constellation point in the candidate constellation point set to the origin The formula is:
[0082] ;
[0083] Then, starting with the candidate constellation point with the smallest Euclidean distance, the selection process begins. Initially, the set of selected constellation points is empty. The candidate constellation point with the smallest Euclidean distance is directly added to the set of selected constellation points. For other candidate constellation points, the Euclidean distances between them and all constellation points in the set of selected constellation points are calculated, and the minimum Euclidean distance is selected. ;;
[0084] like If so, then discard that candidate constellation point;
[0085] like If so, then add the candidate constellation point to the constellation point set;
[0086] Continue until the coordinates of valid constellation points that satisfy the minimum Euclidean distance constraint are obtained, thus obtaining the constellation point set.
[0087] Through the above coordinate generation and filtering process, a constellation point set that satisfies the minimum Euclidean distance constraint, has a symmetrical structure, and is evenly distributed can be obtained efficiently.
[0088] Step 4: Generate the constellation chart, specifically:
[0089] By performing a scaling operation on the constellation point set, the final constellation diagram achieves the target scale and energy level while maintaining the geometric structure, resulting in a three-dimensional scalable constellation diagram that meets the order requirements and has stable performance, which can be directly applied to the implementation of high-order modulation systems.
[0090] This embodiment maintains consistency in skeleton geometry and distance constraints throughout the process, enabling constellations of different orders to achieve high compactness and constellation pattern factor within the same geometric framework. At the same time, it ensures a constant minimum distance and low average symbol energy, thereby balancing energy efficiency and bit error rate performance, and meeting the comprehensive requirements of high-order modulation in terms of performance and stability.
[0091] Example 2
[0092] Based on Example 1, this example presents an experimental case study of a scalable constellation construction method:
[0093] The formation process of parallel intersecting geometric structures is as follows: Figure 2 As shown, two sets of parallel straight line segments are rotated and compressed relative to each other in the vertical direction to form a parallel intersecting geometric structure, which serves as the basic framework of the constellation.
[0094] Figure 3 and Figure 4 The layout effects of constructing a 32-point 3D constellation diagram using a cube skeleton and a parallel intersecting skeleton within the same coordinate envelope size were compared.
[0095] Figure 3 The diagram shows that the 32-point constellation of the Cube skeleton is arranged in a regular grid along three orthogonal directions. The nearest neighbors of each symbol are distributed only in the coordinate axis directions, and the connections between the points are in sparse strips.
[0096] Figure 4 The constellation diagram shown inherits the intersecting characteristics of the parallel intersecting skeleton, with densely distributed symbol points and adjacent edges radiating outwards in space, significantly increasing the number of nearest neighbors per unit volume.
[0097] Because the point cloud of the constellation diagram of the parallel cross skeleton is more concentrated under the same minimum Euclidean distance constraint, its average symbol energy is lower than that of the Cube constellation diagram, and the corresponding constellation figure of merit (CFM) is higher, the advantage of geometric compactness is obvious.
[0098] CFM is defined as:
[0099] ;
[0100] in, This represents the preset minimum Euclidean distance; This represents the normalized average power of every two dimensions in the constellation diagram; Indicates the dimensions of a constellation; Represents the coordinate vector of constellation points Euclidean energy The average Euclidean power; This represents the total number of points in a three-dimensional constellation. Let represent the coordinate vector of the i-th constellation point.
[0101] Calculations show that when =2, =32, =3, the CFM of the constellation diagram composed of Cube skeleton and parallel cross skeleton are 0.6667 and 0.8 respectively. It can be seen that the CFM is improved by 20%. This improvement lays the foundation for optimizing the system's bit error rate performance and provides a unified design method for the expansion of higher-order constellations.
[0102] by Figure 4 Taking a constellation as an example, after a two-step filtering algorithm, 32 valid symbol points in three-dimensional space can be selected. Table 1 lists all the three-dimensional coordinates of the constellation, with the coordinates set at the minimum coordinate step size. The step size is symmetrically distributed in odd multiples in each axial direction, which fully reflects the high symmetry and compactness of the parallel cross skeleton.
[0103] Table 1. Coordinate set of 32 constellation points of parallel intersecting skeleton
[0104] number 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 x 3u 3u 3u 3u 3u 3u 3u 3u u u u u u u u u y 3u 3u u u -u -u -3u -3u 3u 3u u u -u -u -3u -3u z 3u -u u -3u 3u -u u -3u u -3u 3u -u u -3u 3u -u number 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 x -u -u -u -u -u -u -u -u -3u -3u -3u -3u -3u -3u -3u -3u y 3u 3u u u -u -u -3u -3u 3u 3u u u -u -u -3u -3u z 3u -u u -3u 3u -u u -3u u -3u 3u -u u -3u 3u -u
[0105] Based on the 32-point constellation diagram, this embodiment continues to select symbol points along the predetermined candidate point sorting sequence, and performs minimum Euclidean distance verification with the selected points for each newly added point, so that the constellation scale can be smoothly expanded to 64 points; the geometric relationship of the original 32 points remains unchanged.
[0106] The expanded 64-point constellation diagram still follows the odd-symmetric distribution of parallel intersecting skeletons, and the nearest neighbor directions of the symbol points are significantly more numerous than those of the same-order cube (Cube-64) constellation diagram.
[0107] Calculations show that the CFM of the parallel cross skeleton constellation diagram is approximately 0.5107, which is about 27.7% higher than the CFM of 0.400 of the Cube-64 constellation diagram. This indicates that while keeping the minimum distance constant, the average sign energy is effectively reduced and the geometric compactness is significantly improved.
[0108] Figure 5 and Figure 6 This difference is visually demonstrated. Figure 5 The Cube-64 point constellation map still maintains a regular cube grid, with nearest neighbors only along three coordinate axes; Figure 6 The 64-point parallel intersecting skeleton constellation diagram is laid out in a crisscross pattern within the same coordinate range. The number of nearest neighbors of a single point increases, and the edges connecting points are more dense, which geometrically confirms its higher CFM and energy efficiency advantages.
[0109] This embodiment can efficiently and deterministically obtain a compact and uniformly distributed three-dimensional constellation point set that satisfies the minimum distance constraint at any order. The process has good algorithm complexity and can be directly extended to constellation design requirements of higher orders.
[0110] Example 3
[0111] This embodiment introduces a scalable constellation building system, including:
[0112] The basic unit acquisition module is used to: take two parallel line segments in three-dimensional space as geometric basic units;
[0113] The geometric structure construction module is used to: rotate one line segment in the geometric basic unit to be perpendicular to another line segment in the horizontal plane, and compress the distance between two line segments in the geometric basic unit in the vertical plane to obtain a parallel intersecting geometric structure;
[0114] The candidate generation module is used to generate a set of candidate constellation points on the basic constellation skeleton, using the parallel intersecting geometric structure as the basic skeleton of the constellation.
[0115] The constellation point filtering module is used to: filter the candidate constellation point set according to the preset minimum Euclidean distance to obtain the constellation point set;
[0116] The constellation graph construction module is used to generate an expandable constellation graph based on the constellation point set.
[0117] The specific functions of each module described above are explained in the relevant content of the method in Embodiment 1, and will not be repeated here.
[0118] Example 4
[0119] This embodiment describes a signal transmission method for a communication system, including:
[0120] Acquire the bit signal to be transmitted;
[0121] The bit signal to be transmitted is mapped onto a set of constellation points in an expandable constellation diagram to generate a three-dimensional constellation symbol;
[0122] The three-dimensional constellation symbol is subjected to digital-to-analog conversion and signal modulation to obtain a modulated signal;
[0123] The modulated signal is input into the communication channel for signal transmission;
[0124] The scalable constellation diagram is obtained using the scalable constellation construction method based on parallel intersecting geometry described in Example 1.
[0125] In practical digital communication, the scalable constellation diagram constructed in Example 1 can be directly used as the symbol set during modulation for signal transmission. During transmission, the signal is affected by noise, interference, and other non-ideal factors, causing the received signal to deviate from its ideal constellation position. After demodulation and sampling, the receiving end maps the received samples back to the constellation point set using minimum Euclidean distance decision or other symbol decision methods, and recovers the original bit information. Because the constellation diagram of the parallel cross skeleton in Example 1 has higher geometric compactness and more uniform energy distribution under the same minimum distance constraint, it can improve the reliability of symbol decision under various communication channel conditions, thereby effectively reducing the risk of bit errors and possessing good engineering applicability.
[0126] Example 5
[0127] This embodiment describes a computer-readable storage medium storing a computer program / instructions that, when executed by a processor, implement the steps of the scalable constellation construction method described in Embodiment 1.
[0128] Example 6
[0129] This embodiment describes a computer device, including:
[0130] Memory, used to store computer programs / instructions;
[0131] A processor for executing the computer program / instructions to implement the steps of the scalable constellation construction method described in Embodiment 1.
[0132] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0133] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1A device that provides the functions specified in one or more boxes.
[0134] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0135] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0136] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.
Claims
1. A scalable constellation construction method, characterized in that, include: Two parallel line segments in three-dimensional space are used as the basic geometric units; In the horizontal plane, one line segment in the geometric basic unit is rotated to be perpendicular to another line segment, and in the vertical plane, the distance between the two line segments in the geometric basic unit is compressed to obtain a parallel intersecting geometric structure. Using parallel intersecting geometric structures as the basic framework of constellations, a set of candidate constellation points is generated on the basic framework of constellations; The candidate constellation point set is filtered according to the preset minimum Euclidean distance to obtain the constellation point set; An expandable constellation map is generated based on the constellation point set.
2. The scalable constellation construction method according to claim 1, characterized in that, Using parallel intersecting geometric structures as the basic framework of the constellation, a set of candidate constellation points is generated on the basic framework, including: Generate the minimum coordinate step size based on the preset minimum Euclidean distance; Based on the minimum coordinate step size, a set of candidate constellation points is generated that are symmetrically distributed in odd multiples of each coordinate axis in a three-dimensional rectangular coordinate system.
3. The scalable constellation construction method according to claim 2, characterized in that, The formula for the minimum coordinate step size is: ； in, Indicates the minimum coordinate step size; This represents the preset minimum Euclidean distance.
4. The scalable constellation construction method according to claim 2, characterized in that, The coordinate formula for the candidate constellation point set is: ； ； in, Describes the set of one-witness number lattice points representing the candidate constellation point set; Represents the candidate constellation point set; Represents the set of all integers; Represents a constant; Indicates the minimum coordinate step size; This represents the coordinates of the i-th candidate constellation point in the candidate constellation point set.
5. The scalable constellation construction method according to claim 1, characterized in that, The candidate constellation point set is filtered according to a preset minimum Euclidean distance to obtain a constellation point set, including: Calculate the Euclidean distance from each candidate constellation point in the candidate constellation point set to the origin of the coordinate system, and arrange the candidate constellation points in ascending order of Euclidean distance; The selection process begins with choosing the candidate constellation point with the smallest Euclidean distance. Initially, the set of selected constellation points is empty. The candidate constellation point with the smallest Euclidean distance is directly added to the set of selected constellation points. For other candidate constellation points, the Euclidean distances between them and all constellation points in the set of selected constellation points are calculated, and the minimum Euclidean distance is selected. ; like If so, then discard that candidate constellation point; like If so, then add the candidate constellation point to the constellation point set; in, This represents the preset minimum Euclidean distance.
6. The scalable constellation construction method according to claim 5, characterized in that, The Euclidean distance from each candidate constellation point in the candidate constellation point set to the origin is calculated using the following formula: ； in, This represents the Euclidean distance from the i-th candidate constellation point in the candidate constellation point set to the origin. This represents the coordinates of the i-th candidate constellation point in the candidate constellation point set.
7. A scalable constellation building system, characterized in that, include: The basic unit acquisition module is used to: take two parallel line segments in three-dimensional space as geometric basic units; The geometric structure construction module is used to: rotate one line segment in the geometric basic unit to be perpendicular to another line segment in the horizontal plane, and compress the distance between two line segments in the geometric basic unit in the vertical plane to obtain a parallel intersecting geometric structure; The candidate generation module is used to generate a set of candidate constellation points on the basic constellation skeleton, using the parallel intersecting geometric structure as the basic skeleton of the constellation. The constellation point filtering module is used to: filter the candidate constellation point set according to the preset minimum Euclidean distance to obtain the constellation point set; The constellation graph construction module is used to generate an expandable constellation graph based on the constellation point set.
8. A signal transmission method for a communication system, characterized in that, include: Acquire the bit signal to be transmitted; The bit signal to be transmitted is mapped onto a set of constellation points in an expandable constellation diagram to generate a three-dimensional constellation symbol; The three-dimensional constellation symbol is subjected to digital-to-analog conversion and signal modulation to obtain a modulated signal; The modulated signal is input into the communication channel for signal transmission; The scalable constellation diagram is obtained using the scalable constellation construction method according to any one of claims 1-6.
9. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the scalable constellation construction method as described in any one of claims 1-6.
10. A computer device, characterized in that, include: Memory, used to store computer programs / instructions; A processor for executing the computer program / instructions to implement the steps of the scalable constellation construction method according to any one of claims 1-6.