Rapid detection method based on regular regular hexagon modulation

Abstract

The invention discloses a quick detection method based on regular regular hexagon modulation, which is suitable for regular hexagon QAM (Quadrature Amplitude Modulation) in a communication system. The method comprises the following steps: constructing a communication system based on HQAM modulation, and configuring an additive white Gaussian noise (AWGN) channel; hQAM modulation constellation point information is extracted and stored in an information matrix, and axial coordinates (Axial Coordinates) serve as an information matrix index. The signal passing through the AWGN channel is converted into the Axial Coordines, and the AWGN channel is converted into the Axial Coordines; the value of the Axial Coordines is used for carrying out retrieval in the information matrix; if corresponding elements exist in the matrix, symbol judgment is carried out; if the corresponding elements do not exist in the matrix, judging whether the matrix indexes corresponding to the six adjacent hexagons have elements in the information matrix or not; if the corresponding elements still do not exist in the six adjacent hexagons, symbol judgment is carried out through linear detection. The invention provides a rapid detection method based on regular hexagon modulation, so that symbol judgment based on regular hexagon modulation can complete detection more rapidly and more accurately.

Description

Technical Field

[0001] The invention relates to the field of communications, and in particular to a fast detection method based on regular hexagonal modulation. Background Art

[0002] Ultra-high data rates and energy efficiency are crucial in wireless communication systems beyond 5G and 6G. With the emergence of emerging applications such as virtual and augmented reality, industrial Internet of Things, and digital twins, the capabilities of digital communication systems need to be further expanded. Because of this, research interest in recent years has focused on the study of higher-order two-dimensional (2D) constellations that can provide high-speed data communication in an energy-efficient manner. In this direction, hexagonal quadrature amplitude modulation (HQAM) is considered to be a modulation method that can play a key role in future wireless systems because it significantly improves performance in terms of data rate and energy efficiency, thanks to its compact symbol distribution on a 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 determines 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, with different levels of complexity. The detection is too complicated, which is also its fatal flaw. A lot of computing resources will be wasted during the detection process. Summary of the invention

[0004] In view of the above-mentioned defects of the prior art, the technical problem to be solved by the present invention is that the existing detection method for HQAM has high complexity and wastes computing resources. Therefore, the present invention provides a fast detection method based on regular hexagonal modulation, which reduces detection calculations and proposes for the first time that the detection complexity is less than The complexity of this detection method is While ensuring detection accuracy, reduce detection complexity and speed up the detection process.

[0005] Therefore, the present invention provides a fast detection method based on regular hexagonal modulation, characterized in that it includes the following steps:

[0006] Construct a regular 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 the matrix index being Axial Coordinates;

[0008] Convert the HQAM receiving end signal into Axial Coordinates;

[0009] Use the required Axial Coordinates to search in the information matrix to determine whether the constellation point exists in the corresponding Axial Coordinates. If so, perform symbol decision directly.

[0010] If there is no corresponding element in the information matrix, the value of Axial Coordinates is ±1 to find the six constellation points adjacent to the received symbol to see if there is a corresponding element. If so, symbol decision is performed;

[0011] If there are no corresponding elements in the six adjacent hexagons, the minimum Euclidean distance between the constellation point and the received symbol is calculated by linear detection, and the received symbol is judged to be this constellation point.

[0012] Further, the HQAM constellation point information is extracted, and the data is stored in a matrix with the matrix index being AxialCoordinates, specifically including:

[0013] The constellation modeling of HQAM is performed, where 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 the horizontal and vertical offset parameters.

[0019] Regarding the calculation of h0 and v0, it is necessary to define the relevant parameters for even-order constellations and odd-order constellations:

[0020]

[0021] 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 even-order constellations and odd-order constellations are:

[0022]

[0023] Then the horizontal and vertical offset parameters can be calculated separately:

[0024]

[0025] Considering a special case, when M is 8, special processing is required, and the corresponding h0 and v0 are:

[0026]

[0027] The c1 and c2 corresponding to each constellation point constitute the Axial Coordinates, and then c1 and c2 are converted into positive values ​​through calculation 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.

[0028] Furthermore, the signal at the receiving end of HQAM is converted into Axial Coordinates by converting and approximating the signal passing through the AWGN channel to obtain Axial Coordinates. The conversion equation is as follows:

[0029] Add the offset parameters to the real and imaginary parts of the received signal respectively:

[0030] x temp =x+h0

[0031] y temp =y+v0

[0032] The calculated x temp and temp Convert to Cube Coordinates, the conversion equation is as follows:

[0033]

[0034] Since the received signal is attenuated by the channel, the calculated Cube Coordinates are not integers, so they need to be simplified and approximated to integers. The simplification rules are as follows:

[0035] b round = round (b)

[0036] r round = round (r)

[0037] g round = round (g)

[0038] b diff =|bb round |

[0039] r diff =|rr round |

[0040] g diff =|gg round |

[0041] Find the coordinate with the largest difference and make it equal to the opposite of the sum of the other two coordinates;

[0042] If b diff Maximum, then

[0043] b=-rg

[0044] If r diff Maximum, then

[0045] r=-bg

[0046] If g diff Maximum, then

[0047] g=-rb

[0048] Convert Cube Coordinates to Axial Coordinates as follows:

[0049] c1=r+Coor offset +1

[0050] c2=b+1

[0051] AxialCoordinates=(c1,c2)

[0052] Among them, Coor offset is a coordinate offset parameter set for constructing the information matrix and is defined as follows:

[0053]

[0054] Furthermore, the required Axial Coordinates are retrieved from the symbol information matrix.

[0055] Furthermore, if a corresponding element exists in the symbol information matrix located by Axial Coordinates, the received signal is directly judged to be the element.

[0056] Furthermore, if the symbol information matrix located by Axial Coordinates does not have a corresponding element, it is determined whether the six adjacent hexagons have a corresponding element. The determination process is as follows:

[0057] First find the Axial Coordinates of the six adjacent hexagons:

[0058]

[0059] The six Axial Coordinates obtained by the above equations are searched in the symbol information matrix to see if there is a corresponding element. If so, the received signal is judged to be the element.

[0060] Furthermore, the above process is implemented using MATLAB's "try-catch" statement, in which the parameter minDist for recording the minimum Euclidean distance is set to inf, and the number of rows and columns of the information matrix for storing constellation coordinates and constellation symbols is set, represented by maxRows and maxColums respectively; followed by six conditional statements to determine whether the received signal is a constellation point around the constellation diagram.

[0061] Furthermore, if there are no corresponding elements in the six adjacent hexagons, the linear detection method MLD is used to calculate the Euclidean distances between the received signal and all constellation points, and the constellation point with the smallest Euclidean distance is selected and judged as the received symbol.

[0062] Technical Effects

[0063] The present invention provides a fast detection method based on regular hexagonal modulation. An information matrix storing the coordinates of constellation points and their corresponding decimal symbols is constructed at the transmitting end. At the receiving end, the real and imaginary parts of the signal are converted into Axial Coordinates. Then, by using the convenience of Axial Coordinates in the hexagon, the Axial Coordinates of the six adjacent hexagons can be obtained at the same time, and then the symbol retrieval can be performed directly in the information matrix. In extreme cases (low signal-to-noise ratio), the signal point is far away from the constellation diagram. At this time, the constellation point with the smallest Euclidean distance to the received symbol can be calculated by linear detection to make a judgment. This reduces a large number of unnecessary calculations and effectively reduces the detection complexity of HQAM, thereby promoting the practical application of HQAM. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is a flowchart of a fast detection method based on regular hexagonal modulation provided by an embodiment of the present invention;

[0065] Figure 2 The embodiment of the present invention provides a coordinate system conversion part of a fast symbol detection algorithm;

[0066] Figure 3 The embodiment of the present invention provides a low signal-to-noise ratio calibration part of a fast symbol detection algorithm;

[0067] Figure 4 It is a schematic diagram of a method for a receiving end to detect symbols other than conventional constellation points provided by an embodiment of the present invention;

[0068] Figure 5 It is a schematic diagram of the effect of a fast detection method based on regular hexagonal modulation according to an embodiment of the present invention. DETAILED DESCRIPTION

[0069] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0070] In the present invention, the terms "first", "second", etc. (if any) in the present invention and the accompanying drawings are used to distinguish similar objects but not necessarily to describe a specific order or sequence.

[0071] The technical solution in this application will be described below in conjunction with the accompanying drawings.

[0072] like Figure 1 As shown, an embodiment of the present invention provides a fast detection method based on regular hexagonal modulation, and the steps include S101 to S108.

[0073] Step S101, constructing a regular hexagonal QAM (HQAM) modulation system and configuring an AWGN channel environment.

[0074] Step S102, extracting HQAM constellation point information, including: constellation point coordinates and corresponding decimal symbols, and then storing the coordinate and symbol information in SymbolCoordinates and SymbolData matrices respectively, and the matrix index is the value corresponding to AxialCoordinates;

[0075] Step S103, convert the signal received by the receiving end into Axial Coordinates, and implement the algorithm as follows Figure 2 As shown, the steps are as follows:

[0076] Add the offset parameters to the real and imaginary parts of the received signal respectively:

[0077] x temp =real(S x )+h0

[0078] y temp =imag(S x )+v0

[0079] The calculated x temp and temp Convert to Cube Coordinates, the conversion equation is as follows:

[0080]

[0081] Among them, d min is the distance between constellation points.

[0082] Since the received signal passes through the AWGN channel, the calculated Cube Coordinates are not integers, so they need to be simplified to integers. The simplification rules are as follows:

[0083] b round = round (b)

[0084] r round = round (r)

[0085] g round = round (g)

[0086] b diff =|bb round |

[0087] r diff =|rr round |

[0088] g diff =|gg round |

[0089] Among them, round is the rounding function.

[0090] Find the coordinate with the largest difference and set it equal to the opposite of the sum of the other two coordinates.

[0091] If b diff Maximum, then

[0092] b=-rg

[0093] If r diff Maximum, then

[0094] r=-bg

[0095] If g diff Maximum, then

[0096] g=-rb

[0097] Convert Cube Coordinates to Axial Coordinates as follows:

[0098] c1=r+Coor offset +1

[0099] c2=b+1

[0100] AxialCoordinates=(c1,c2)

[0101] Among them, Coor offset is a coordinate offset parameter set for constructing the information matrix and is defined as follows:

[0102]

[0103] In step S104 to step S105, the required Axial Coordinates are used to search in the information matrix to determine whether a constellation point exists in the corresponding Axial Coordinates. If so, symbol decision is directly performed.

[0104] In step S106 to step S107, when the signal-to-noise ratio is low, if there is no corresponding element in the information matrix, the value of Axial Coordinates is ±1. Since there are only adjacent hexagons in the surrounding hexagonal area in the area outside the constellation diagram, it is first determined whether it is a constellation point in a circle around the constellation diagram. If so, the six constellation points adjacent to the received symbol are found to see if there are corresponding elements. If so, symbol judgment is performed. If it is not a constellation point in a circle around the constellation diagram, step S108 is entered.

[0105] In step S108, a constellation point with the smallest Euclidean distance to the received symbol is calculated by linear detection, and the received symbol is determined to be this constellation point.

[0106] The implementation algorithm of step S104 to step S108 is as follows: Figure 3 As shown, the specific steps are as follows:

[0107] If the corresponding elements in the SymbolData matrix exist, the symbol decision is made directly. If the value corresponding to AxialCoordinates is indexed in the SymbolData matrix and there is no corresponding element, the next decision is made. This process uses MATLAB's "try-catch" statement to implement the above functions. The "try" statement is used to determine whether there is a corresponding element in the corresponding SymbolData information matrix. If not, the "catch" statement is entered; if the existing element is a null value (set to -1 in the algorithm), an error is thrown and the "catch" statement is entered. Set the parameter minDist used to record the minimum Euclidean distance to inf; set the number of rows and columns of the information matrix used to store constellation coordinates and constellation symbols, represented by maxRows and maxColums respectively; followed by six conditional statements to determine whether the received signal is a circle of constellation points around the constellation diagram.

[0108] Figure 4Take 64HQAM as an example to explain this part of the algorithm: Conditions 1, 2, 3, 4, 5, and 6 correspond to the orange, green, light blue, yellow, purple, and red parts in the constellation diagram, respectively. If it is determined to be one of the above six parts, for each part, move the hexagon in the Axial Coordinates to determine whether it has an element in the Symbol Coordinates matrix. If so, calculate the minimum Euclidean distance of the remaining received signals 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, the linear detection method MLD is used to calculate the Euclidean distance between the received signal and all constellation points, and the point with the minimum Euclidean distance is selected for decision.

[0110] After proposing a detection method, it is necessary to ensure that the detection algorithm works as expected. The detection algorithm should also be applicable to situations with poor signal-to-noise ratios. Construct a signal point grid that is larger and finer than the constellation diagram, where the signal points at the edge of this point grid can be analogous to the symbols received when the signal-to-noise ratio is poor, and test whether the proposed detection algorithm can correctly find the decision area to which all signal points in the point grid belong, and judge them to the corresponding constellation points of the constellation diagram. Compare it with the linear detection method MLD, and draw the points where the detection algorithm and the linear detection algorithm have different judgment results in blue. The effect is as follows Figure 5 , we can see that there are some blue points, but these points are located at the boundary of the decision area and can be ignored because the symbols at the receiving end are unlikely to be exactly at the boundary of the decision area. The simulation results show that the detection error of the method is comparable to that of the MLD method and has a higher detection efficiency, reducing the time complexity from Reduce to

[0111] In the embodiment of the present invention, a fast detection method based on regular hexagonal modulation is proposed for the first time in a hexagonal QAM modulation system by taking advantage of the axial coordinates in hexagonal modulation. The complexity of this detection method is While ensuring detection accuracy, the detection complexity is reduced, so that symbol decision based on regular hexagonal modulation can complete detection more quickly and accurately, overcoming the high complexity and large amount of calculation of existing detection solutions.

[0112] The specific embodiments of the present invention are described in detail above. It should be understood that a person skilled in the art can make many modifications and changes to the concept of the present invention without creative work. Therefore, any technical solution obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of the prior art should be within the scope of protection determined by the 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 required AxialCoordinates value 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 there is no corresponding element in the information matrix, the value of Axial Coordinates is ±1 to find the six constellation points adjacent to the received symbol to see if there is a corresponding element; if so, symbol decision is performed; If there are no corresponding elements in 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.

2. A fast detection method based on regular hexagonal modulation as claimed in claim 1, characterized in that: Extract HQAM constellation point information, store the data in a matrix and the matrix index is AxialCoordinates, 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 even-order constellations and odd-order constellations 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, and then c1 and c2 are converted into positive values ​​through calculation 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.

3. A fast detection method based on regular hexagonal modulation as claimed in claim 2, characterized in that: At the receiving end of HQAM, 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 temp First convert to Cube Coordinates. The conversion equation is as follows: Since 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, Cooro ffset is a coordinate offset parameter set for constructing the information matrix and is defined as follows:

4. A fast detection method based on regular hexagonal modulation as claimed in claim 3, characterized in that: Retrieve the required Axial Coordinates from the symbol information matrix.

5. A fast detection method based on regular hexagonal modulation as claimed in claim 4, characterized in that: If the corresponding element is found by searching the symbol information matrix located by Axial Coordinates, the received symbol is directly judged as the constellation point.

6. A fast detection method based on regular hexagonal modulation as claimed in claim 4, characterized in that: If the symbol information matrix located by AxialCoordinates does not have a corresponding element, the value of AxialCoordinates is ±1 to find the six adjacent constellation points of the received symbol to see if there is a corresponding element, that is, to 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: Search the six Axial Coordinates obtained by the above equation in the symbol information matrix to see if there are corresponding elements; if so, calculate the Euclidean distance between it and the received symbol and store it temporarily, then jump to the next direction to determine if there are corresponding elements; After the six-directional search is completed, the constellation point corresponding to the minimum Euclidean distance to the received symbol is found, and the constellation point is determined as the received symbol.

7. A fast detection method based on regular hexagonal modulation as claimed in claim 6, characterized in that: The above process is implemented using MATLAB's "try-catch" statement, in which the parameter minDist used to record the minimum Euclidean distance is set to inf, and the number of rows and columns of the information matrix used to store the constellation coordinates and constellation symbols is set, represented by maxRows and maxColums respectively; followed by six conditional statements to determine whether the received signal is a constellation point around the constellation diagram.

8. A fast detection method based on regular hexagonal modulation as claimed in claim 7, 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 taken and judged as the received symbol.

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