A fast detection method based on regular hexagon modulation
By constructing a regular hexagonal QAM modulation system and using axial coordinates to convert the received signal, combined with linear detection, the problem of high HQAM detection complexity is solved, and faster and more accurate detection is achieved.
Patent Information
- Application Number
- CN202411758577.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-03
- Publication Date
- 2025-10-17
- Estimated Expiration
- 2044-12-03
AI Technical Summary
Existing detection methods for HQAM are highly complex and waste computing resources, making the detection process impractical.
A regular hexagonal QAM modulation system is constructed. The received signal is converted by axial coordinates and retrieved in the information matrix. The linear detection method is combined to reduce the detection complexity.
While ensuring detection accuracy, the detection complexity is significantly reduced and the detection efficiency is improved. It is suitable for high signal-to-noise ratio and low signal-to-noise ratio environments.
Smart Images
Figure CN119544446B_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the field of communication, in particular to a fast detection method based on regular hexagon modulation. BACKGROUND
[0002] In the wireless communication system beyond 5G and 6G, ultra-high data rate and energy efficiency are of great importance. With the emergence of emerging applications such as virtual reality and augmented reality, industrial Internet of Things, digital twin, etc., the capabilities of digital communication systems need to be further expanded. For this reason, in recent years, research interest has focused on higher-order two-dimensional (2D) constellations that can provide high-speed data communication with efficient energy utilization. In this direction, hexagonal quadrature amplitude modulation (HQAM) is considered as a modulation scheme that can play a key role in future wireless systems, as it significantly improves performance in terms of data rate and energy efficiency, thanks to its compact symbol distribution in the two-dimensional plane.
[0003] MLD (Maximum Likelihood Detection) is the most commonly used detection scheme, which calculates the distance between the received symbol and each constellation point, and judges the constellation point with the smallest distance as the transmitted symbol. Although MLD has high accuracy, it is not practical in the detection process because its detection process is too cumbersome. There are many existing detection methods for HQAM, and the complexity is , the detection is too complex, which is a fatal flaw, and a lot of computing resources are wasted in the detection process. SUMMARY
[0004] In view of the above defects of the prior art, the technical problem to be solved by the present application is the problem of high complexity and waste of computing resources of the existing detection method for HQAM. Therefore, the present application provides a fast detection method based on regular hexagon modulation, which reduces detection calculation and first proposes a detection complexity less than The complexity of the detection method is Under the condition of ensuring the detection accuracy, the detection complexity is reduced, and the detection process is accelerated.
[0005] Therefore, the present application provides a fast detection method based on regular hexagon modulation, characterized in that it comprises the following steps:
[0006] Construct a hexagonal QAM (HQAM) modulation system and configure an AWGN channel environment;
[0007] Extract HQAM constellation point information, including constellation point coordinates and corresponding decimal symbols, and then store the HQAM constellation point information in a matrix with matrix index as Axial Coordinates;
[0008] The signal of the receiving end of HQAM is converted into Axial Coordinates;
[0009] The Axial Coordinates are used to search in the information matrix, and it is determined whether there is a constellation point in the corresponding Axial Coordinates. If there is, a symbol decision is directly made;
[0010] If the information matrix does not have a corresponding element, the value of the Axial Coordinates is ±1, and the six adjacent constellation points of the received symbol are found to see whether there is a corresponding element. If there is, a symbol decision is made;
[0011] If the six adjacent hexagons do not have corresponding elements, the minimum Euclidean distance between the constellation point and the received symbol is calculated in a linear detection manner, that is, the received symbol is determined as the constellation point.
[0012] Further, the HQAM constellation point information is extracted, and the data is stored in a matrix with the matrix index being Axial Coordinates, which specifically includes:
[0013] The HQAM is modeled by constellation, and the constellation point set S is:
[0014]
[0015] v1 = [d min , 0]
[0016]
[0017] v3 = [h0, v0]
[0018] where d min is the minimum distance between constellation points; h0 and v0 are horizontal and vertical offset parameters.
[0019] Regarding the calculation of h0 and v0, related parameters for even-order constellation and odd-order constellation need to be defined:
[0020]
[0021] where M is the number of constellation points, and n is the modulation order. Since the constellation points are arranged in a hexagonal shape, the size of the information matrix is larger than that of the rectangular QAM modulation constellation point information matrix. The sizes of the even-order constellation and the odd-order constellation are:
[0022]
[0023] Further, the horizontal and vertical offset parameters can be calculated respectively:
[0024]
[0025] Consider a special case, when M is 8, need to do special processing, the corresponding h0 and v0 are:
[0026]
[0027] Each star point corresponding to c1 and c2 constitute Axial Coordinates, and then calculate the c1 and c2 are converted to positive value so as to constitute the index of information matrix; define two information matrix, respectively, store the coordinates of the constellation points and each corresponding decimal symbol.
[0028] Further, the signal conversion of the receiving end of HQAM into Axial Coordinates, is to convert the signal through the AWGN channel to Axial Coordinates, conversion equation as follows:
[0029] The real part of the received signal and the imaginary part are added to the offset parameter respectively:
[0030] x temp = x + h0
[0031] y temp = y + v0
[0032] The calculated x temp and y temp are converted to Cube Coordinates, conversion equation as follows:
[0033]
[0034] Because the received signal through the channel attenuation, so the calculated Cube Coordinates is not an integer, so it needs to be simplified, and it is about to integer, the simplification rule as follows:
[0035] b round = round (b)
[0036] r round = round (r)
[0037] g round = round (g)
[0038] b diff = |b - b round |
[0039] r diff = |r - r round |
[0040] g diff = |g - g round |
[0041] Find the coordinate with the largest difference, and let it equal the opposite of the sum of the other two coordinates;
[0042] If b diff is the largest, then
[0043] b = -r - g
[0044] If r diff is the largest, then
[0045] r = -b - g
[0046] If g diff is the largest, then
[0047] g = -r - b
[0048] Convert Cube Coordinates to Axial Coordinates as follows:
[0049] c1 = r + Coor offset + 1
[0050] c2 = b + 1
[0051] Axial Coordinates = (c1, c2)
[0052] where Coor offset is a coordinate offset parameter set for constructing the information matrix, defined as follows:
[0053]
[0054] Further, the obtained Axial Coordinates are searched in the sign information matrix.
[0055] Further, if the sign information matrix located by the Axial Coordinates has a corresponding element, the received signal is directly judged as the element.
[0056] Further, if the sign information matrix located by the Axial Coordinates does not have a corresponding element, it is determined whether the adjacent six hexagons have corresponding elements, and the determination process is as follows:
[0057] First, find the Axial Coordinates of the adjacent six hexagons:
[0058]
[0059] The six axial coordinates obtained by the above equation are searched in the symbol information matrix to check whether corresponding elements exist, and if so, the received signal is determined as the element.
[0060] Further, the above process is realized by using the "try-catch" statement of MATLAB, wherein a parameter minDist for recording the minimum Euclidean distance is set as inf, and the row and column numbers of an information matrix for storing constellation coordinates and constellation symbols are set as maxRows and maxColums respectively; then six conditional statements are used to determine whether the received signal is a constellation point around a circle of the constellation diagram.
[0061] Further, if the corresponding elements do not exist in the adjacent six hexagons, the Euclidean distances between the received signal and all constellation points are calculated by using the linear detection method MLD, the constellation point with the minimum Euclidean distance is taken, and the constellation point is determined as the received symbol.
[0062] Technical effects
[0063] The application provides a fast detection method based on regular hexagon modulation, a information matrix for storing constellation point coordinates and corresponding decimal symbols is constructed at a sending end, the real part and the imaginary part of a signal are converted into axial coordinates at a receiving end, the axial coordinates in the hexagons are convenient, the axial coordinates of the adjacent six hexagons can be obtained, and then the symbol can be searched in the information matrix. In an extreme (low signal-to-noise ratio) case, the signal point is far away from the constellation diagram, and the constellation point with the minimum Euclidean distance from the received symbol can be calculated by using the linear detection method, so that the determination can be made. In this way, a large amount of unnecessary calculation is reduced, the detection complexity of the HQAM is effectively reduced, and the practicalization process of the HQAM is promoted. BRIEF DESCRIPTION OF DRAWINGS
[0064] Figure 1 is a flowchart of the fast detection method based on regular hexagon modulation provided by the embodiment of the application;
[0065] Figure 2 is a coordinate system conversion part of the fast symbol detection algorithm provided by the embodiment of the application;
[0066] Figure 3 is a low signal-to-noise ratio detection part of the fast symbol detection algorithm provided by the embodiment of the application;
[0067] Figure 4 is a symbol detection method diagram of the receiving end for detecting symbols other than the conventional constellation points provided by the embodiment of the application;
[0068] Figure 5 is a schematic diagram of the effect of a fast detection method based on regular hexagonal modulation according to an embodiment of the present application. DETAILED DESCRIPTION
[0069] In order to make the technical problems to be solved by the present application, technical solutions and beneficial effects clearer, the present application will be further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.
[0070] In the present application, the terms "first", "second", etc. (if any) in the present application and the drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence.
[0071] The technical solutions in the present application will be described below in combination with the drawings.
[0072] As shown in Figure 1 , the present application provides a fast detection method based on regular hexagonal modulation, which comprises steps S101 to S108.
[0073] Step S101, a hexagonal QAM (HQAM) modulation system is constructed, and an AWGN channel environment is configured.
[0074] Step S102, HQAM constellation point information is extracted, including constellation point coordinates and corresponding decimal symbols, and then the coordinate and symbol information are stored in SymbolCoordinates and SymbolData matrices respectively, and the matrix index is the value corresponding to AxialCoordinates;
[0075] Step S103, the signal received at the receiving end is converted into Axial Coordinates, and the algorithm is as shown in Figure 2 , and the steps are as follows:
[0076] The real part and the imaginary part of the received signal are added with offset parameters respectively:
[0077] x temp =real(S x )+h0
[0078] y temp =imag(S x )+v0
[0079] The calculated x temp and y temp are converted into Cube Coordinates, and the conversion equation is as follows:
[0080]
[0081] where d min is the distance between constellation points.
[0082] Since the received signal is through AWGN channel, the calculated Cube Coordinates are not integers, so it is necessary to simplify them to integers, and the simplification rules are as follows:
[0083] b round = round (b)
[0084] r round = round (r)
[0085] g round = round (g)
[0086] b diff = |b-b round |
[0087] r diff = | r-r round |
[0088] g diff = | g-g round |
[0089] where round is the rounding function.
[0090] Find the coordinate with the largest difference, and let it equal the opposite of the sum of the other two coordinates.
[0091] If b diff is the largest, then
[0092] b = -r-g
[0093] If r diff is the largest, then
[0094] r = -b-g
[0095] If g diff is the largest, then
[0096] g = -r-b
[0097] Convert the Cube Coordinates to Axial Coordinates as follows:
[0098] c1 = r + Coor offset +1
[0099] c2 = b +1
[0100] AxialCoordinates = (c1, c2)
[0101] where Coor offset is a coordinate offset parameter set for constructing the information matrix, defined as follows:
[0102]
[0103] In steps S104 to S105, the information matrix is searched using the obtained Axial Coordinates, and it is determined whether there is a constellation point in the corresponding Axial Coordinates. If there is, a symbol decision is directly made.
[0104] In steps S106 to S107, if the information matrix does not have a corresponding element in the case of a low signal-to-noise ratio, the value of the Axial Coordinates is added or subtracted by 1. Since only the adjacent hexagons of the surrounding six hexagons of the outer region of the constellation diagram have constellation points, it is first determined whether it is a constellation point in the surrounding six hexagons of the constellation diagram. If it is, the six constellation points adjacent to the received symbol are found, and it is determined whether there is a corresponding element. If there is, a symbol decision is made. If it is not a constellation point in the surrounding six hexagons of the constellation diagram, step S108 is entered.
[0105] In step S108, the constellation point with the smallest Euclidean distance from the received symbol is calculated by linear detection, and the received symbol is determined as this constellation point.
[0106] The implementation algorithm of steps S104 to S108 is shown in FIG. 6, and the specific steps are as follows: Figure 3
[0107] If the corresponding element of the SymbolData matrix exists, a symbol decision is directly made. If the value corresponding to the AxialCoordinates does not exist in the SymbolData matrix, the next decision is made. This process uses the "try-catch" statement of MATLAB to realize the above functions. The "try" statement is used to determine whether there is a corresponding element in the corresponding SymbolData information matrix. If there is not, the "catch" statement is entered. If the existing element is a null value (set as -1 in the algorithm), an error is thrown, and the "catch" statement is entered. The parameter minDist used to record the minimum Euclidean distance is set to inf. The row and column numbers of the information matrix used to store the constellation coordinates and constellation symbols are set to maxRows and maxColums, respectively. Then, six conditional statements are used to determine whether the received signal is a constellation point in the surrounding six hexagons of the constellation diagram.
[0108] Figure 4 Take 64 HQAM as an example, explain the algorithm part: condition 1, 2, 3, 4, 5, 6 correspond to the orange part, green part, light blue part, yellow part, purple part, red part in the constellation diagram. If it is judged that the above six parts, move the hexagon in the Axial Coordinates for each part, judge whether it exists in the Symbol Coordinates matrix, if it exists, calculate the minimum Euclidean distance of the remaining received signal and update the matrix index (indexc1, indexc2).
[0109] Finally, if minDist is not equal to inf, the obtained matrix index is used for symbol decision. Otherwise, use the linear detection method MLD to calculate the Euclidean distance between the received signal and all constellation points, and take the minimum point to make a decision.
[0110] After proposing the detection method, it is necessary to ensure that the detection algorithm works as expected. The detection algorithm should also be suitable for cases where the signal-to-noise ratio is poor. Construct a signal point grid larger and more detailed than the constellation diagram, where the signal points on the edge of the point grid can be analogous to the received symbols in the case of poor signal-to-noise ratio, test whether the proposed detection algorithm can correctly find all signal points in the point grid to the decision region it belongs to, and decide it to the corresponding constellation point of the constellation diagram. Compared with the linear detection method MLD, draw the points where the detection algorithm and the linear detection algorithm differ in blue. The effect is as follows Figure 5 It can be seen that there are some blue points, but these points are located on the boundary of the decision region, which can be ignored because the received symbol is unlikely to be exactly located on the boundary of the decision region. The simulation results show that the detection error of the method is comparable to the MLD method and has high detection efficiency, reducing the time complexity from to
[0111] A fast detection method based on regular hexagon modulation in an embodiment of the application, by the advantage of Axial Coordinates in hexagon modulation in the hexagon QAM modulation system, for the first time, the detection complexity is less than The complexity of the detection method is Under the condition of ensuring the detection accuracy, the detection complexity is reduced. The symbol decision based on regular hexagon modulation can complete the detection more quickly and accurately, overcoming the high complexity and large calculation of the existing detection scheme.
[0112] The specific embodiments of the present application have been described above. It should be understood that various modifications and changes can be made to the present application by those skilled in the art without departing from the spirit and scope of the present application. Therefore, the scope of the present application shall be limited only by the appended claims.
Claims
1. A fast detection method based on regular hexagonal modulation, characterized in that: The following steps are involved: Construct HQAM modulation system and configure AWGN channel environment; Extract HQAM constellation point information, including constellation point coordinates and corresponding decimal symbols, and then store the HQAM constellation point information in an information matrix with the information matrix indexed by the value corresponding to Axial Coordinates; At the receiving end of HQAM, the received signal is converted into Axial Coordinates; Use the value of the required AxialCoordinates to search in the information matrix to determine whether the constellation point exists in the corresponding information matrix. If so, perform symbol decision directly. If the information matrix does not have a corresponding element, the value of Axial Coordinates is ±1, and the six constellation points adjacent to the received symbol are found to see if there is a corresponding element; if so, symbol decision is performed; If there is no corresponding element in any of the six adjacent hexagons, a linear detection method is used to find the constellation point with the smallest Euclidean distance to the received symbol, and the received symbol is judged to be this constellation point; Among them, the HQAM constellation point information is extracted, the data is stored in a matrix and the matrix index is Axial Coordinates, specifically including: The constellation modeling of HQAM is performed, where the constellation point set S is: v1=[d min ,0] v3=[h0,v0] where d min is the minimum distance between constellation points; h0 and v0 are the horizontal and vertical offset parameters; Regarding the calculation of h0 and v0, it is necessary to define the relevant parameters for even-order constellations and odd-order constellations: Where M is the number of constellation points and n is the modulation order. Since the constellation points are arranged in a hexagon, the size of the information matrix is larger than that of the constellation point information matrix of rectangular QAM modulation. The sizes of the even-order constellation and odd-order constellation are: Then the horizontal and vertical offset parameters can be calculated separately: Considering a special case, when M is 8, special processing is required, and the corresponding h0 and v0 are: The c1 and c2 corresponding to each constellation point constitute the axial coordinates. After calculation, c1 and c2 are converted to positive values to form the index of the information matrix. Two information matrices are defined to store the coordinates of the constellation points and the decimal symbols corresponding to each constellation point respectively. At the HQAM receiver, the received signal is converted into axial coordinates by converting the signal through the AWGN channel into axial coordinates. The conversion equation is as follows: Add the offset parameters to the real and imaginary parts of the received signal respectively: x temp =x+h0 and temp =y+v0 The calculated x temp and y temp First convert to Cube Coordinates. The conversion equation is as follows: Because the received signal passes through the AWGN channel, the calculated Cube Coordinates are not integers and need to be simplified to be approximately integers. The simplification rules are as follows: b round =round(b) r round =round(r) g round =round(g) b diff =|b-b round | r diff ＝|r-r round | g diff =|gg round | Find the coordinate with the largest difference and make it equal to the opposite of the sum of the other two coordinates; If b diff Maximum, then b=-rg If r diff Maximum, then r=-bg If g diff Maximum, then g=-rb Convert Cube Coordinates to Axial Coordinates as follows: c1=r+Coor offset +1 c2=b+1 Axial Coordinates = (c1, c2) Among them, Coor offset It is a coordinate offset parameter set for constructing the information matrix and is defined as follows: If the symbol information matrix located by Axial Coordinates does not have a corresponding element, then by adding ±1 to the value of Axial Coordinates, find the six adjacent constellation points of the received symbol to see if there is a corresponding element. That is, determine whether there is a corresponding element in the six adjacent hexagons. The specific judgment process is as follows: First find the Axial Coordinates of the six adjacent hexagons: The six axial coordinates obtained from the above equations are searched in the symbol information matrix to see if there is a corresponding element. If so, the Euclidean distance between the axial coordinate and the received symbol is calculated and temporarily stored, and then the next direction is jumped to determine whether there is a corresponding element. After the search in all six directions is completed, the constellation point corresponding to the minimum Euclidean distance to the received symbol is found and this constellation point is determined to be the received symbol.
2. A fast detection method based on regular hexagonal modulation according to claim 1, characterized in that: Retrieve the desired Axial Coordinates from the symbol information matrix.
3. A fast detection method based on regular hexagonal modulation as claimed in claim 2, characterized in that: If the corresponding element is found through the symbol information matrix search of the Axial Coordinates positioning, the received symbol is directly judged as the constellation point.
4. A fast detection method based on regular hexagonal modulation as claimed in claim 3, characterized in that: If there are no corresponding elements in the six adjacent hexagons, the linear detection method MLD is used to calculate the Euclidean distance between the received signal and all constellation points, and the constellation point with the smallest Euclidean distance is selected as the received symbol.