QAM constellation rotation estimation method, storage medium and device caused by frequency offset

Abstract

The application discloses a method for estimating QAM constellation rotation caused by frequency offset, a storage medium and equipment. The method comprises the following steps: mapping a received signal into an original quadrature amplitude modulation (QAM) constellation in a complex plane, wherein the original QAM constellation comprises a group of signal data points; sequentially adopting a plurality of rotation angles to compensate the rotation angles of the group of signal data points, and obtaining a plurality of groups of compensated data points, wherein each group of compensated data points corresponds to a rotated QAM constellation in the complex plane; calculating the graph distance between each of the plurality of rotated QAM constellations corresponding to the plurality of groups of compensated data points and a theoretical QAM constellation, and obtaining a plurality of graph distance values; and determining the rotation angle corresponding to the QAM constellation closest to the theoretical QAM constellation in the plurality of rotated QAM constellations as the deflection angle of the original QAM constellation caused by the frequency offset according to the plurality of graph distance values. The application solves the technical problem that there is no reliable method for accurately estimating the rotation angle of the QAM constellation caused by the frequency offset.

Description

Technical Field

[0001] The present invention relates to the field of wireless communications, and in particular to a method, storage medium, and device for estimating QAM constellation rotation caused by frequency offset. Background Art

[0002] QAM is an important vector modulation method in wireless communication systems. It can first map the input bits onto a complex plane (constellation diagram) to form complex modulation symbols, and then use amplitude modulation on the I and Q components of the symbols to correspond to two orthogonal carriers in the time domain, such as Figure 1 QAM is a combined amplitude and phase modulation technique that uses both the carrier amplitude and phase to transmit information bits. This allows for higher bandwidth utilization while maintaining the same minimum distance between data points. Compared to amplitude modulation (AM), QAM doubles spectrum efficiency.

[0003] In wireless communication systems, frequency synchronization is required between the transmitter and receiver due to differences in Doppler frequency and local oscillators (LOs) between the transmitter and receiver. Due to uncertainties such as interference and noise, there is often a certain frequency deviation between the transmitter and receiver after synchronization. Therefore, estimation and compensation algorithms are needed to estimate and compensate for the received signal's frequency deviation.

[0004] When a wireless communication system is stable, frequency offset manifests as a linear phase difference between consecutive time-domain symbols. Multi-symbol DM-RS can be used to estimate and compensate for frequency offset, a common approach in related technologies. However, when the system is unstable, frequency offset fluctuates, and the phase offset between different time-domain symbols is random. The multi-symbol DM-RS method can only estimate the frequency offset for the symbol where the DM-RS is transmitted; it cannot estimate the frequency offset for other symbols where the DM-RS is not transmitted. Therefore, when the system is unstable and frequency offset fluctuates, the multi-symbol DM-RS estimation method is no longer effective. Without compensation for residual frequency offset, the demodulation module error rate will increase significantly, significantly degrading system performance. For some other modulation schemes, such as OFDM, frequency offset estimation can be performed using the cyclic prefix (CP) of the time-domain signal and the signal at the end of the corresponding symbol. However, since the CP length only accounts for a small fraction of the entire symbol, the amount of available data is insufficient, resulting in reduced estimation accuracy.

[0005] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0006] Embodiments of the present invention provide a method, storage medium, and device for estimating QAM constellation rotation caused by frequency offset, to at least solve the technical problem of lacking a reliable method for accurately estimating the rotation angle of the QAM constellation caused by frequency offset.

[0007] According to one aspect of an embodiment of the present invention, a constellation diagram rotation estimation method is provided, comprising: mapping a received signal into an original quadrature amplitude modulation (QAM) constellation diagram in a complex plane, wherein the original QAM constellation diagram comprises a group of signal data points, and the complex plane adopts an I component and a Q component as coordinate components; performing rotation angle compensation on the group of signal data points in sequence using multiple rotation angles to obtain multiple groups of compensated data points, wherein each group of compensated data points corresponds to a rotated QAM constellation diagram in the complex plane; respectively calculating the graph distances between multiple rotated QAM constellations corresponding to the multiple groups of compensated data points and a theoretical QAM constellation diagram to obtain multiple graph distance values; and determining, based on the multiple graph distance values, that the rotation angle corresponding to the constellation diagram that is closest to the theoretical QAM constellation diagram among the multiple rotated QAM constellations is the rotation angle of the original QAM constellation diagram caused by frequency offset.

[0008] Optionally, the method of sequentially using multiple rotation angles to perform rotation angle compensation on the group of signal data points to obtain multiple groups of compensated data points includes: determining the angle traversal step, the number of traversals and the initial value of the angle traversal; determining multiple rotation angles based on the angle traversal step, the number of traversals and the initial value of the angle traversal; sequentially using the multiple rotation angles to perform rotation angle compensation on the group of signal data points to obtain the multiple groups of compensated data points, wherein each group of compensated data points is obtained by compensating each data point in the signal data points according to the rotation angle.

[0009] Optionally, the calculating of the graph distances between each of the multiple rotated QAM constellation diagrams corresponding to the multiple groups of compensated data points and the theoretical QAM constellation diagram to obtain multiple graph distance values ​​includes: determining the target graph distance values ​​between the target constellation diagram in the multiple rotated QAM constellation diagrams and the theoretical QAM constellation diagram in the following manner, wherein the target constellation diagram is any one of the multiple rotated QAM constellation diagrams: determining multiple nearest data points in the theoretical QAM constellation diagram that correspond one-to-one to the multiple target data points included in the target constellation diagram; determining multiple Euclidean distances that correspond one-to-one to the multiple nearest data points and the multiple target data points, wherein any one of the multiple Euclidean distances is the distance between the target data point and the corresponding nearest data point; summing the multiple Euclidean distances to obtain the target graph distance value between the target constellation diagram and the theoretical QAM constellation diagram, wherein the multiple graph distance values ​​include the target graph distance value.

[0010] Optionally, the mapping the received signal to an original quadrature amplitude modulation (QAM) constellation diagram in a complex plane comprises: determining a target number of data points in original data points of the received signal, wherein the target number of data points are a target number of data points ranked at the top in the received signal ordered from large to small in amplitude; determining a data point standard value corresponding to the received signal according to the target number of data points; and quantizing the original data points in turn using the data point standard value to obtain the signal data points included in the original QAM constellation diagram.

[0011] Optionally, the determining the target number of data points in the original data points of the received signal comprises: determining the target number according to a formula N max = 4·N / M, wherein N represents a number of the original data points, M represents a number of data points in the theoretical QAM constellation diagram, and N max represents the target number; and the determining the data point standard value corresponding to the received signal according to the target number of data points comprises: calculating modules of the target number of data points in turn; and taking a median of the modules of the target number of data points as the data point standard value corresponding to the received signal.

[0012] Optionally, the determining a plurality of nearest data points in the theoretical QAM constellation diagram corresponding to a plurality of target data points included in the target constellation diagram comprises: performing amplitude scaling on the target constellation diagram based on a scaling factor to obtain a first scaling diagram; performing amplitude scaling on the theoretical QAM constellation diagram based on the scaling factor to obtain a second scaling diagram; and determining the plurality of nearest data points in the theoretical QAM constellation diagram corresponding to the plurality of target data points according to the first scaling diagram and the second scaling diagram.

[0013] Optionally, the scaling factor is determined according to a formula: α = (log2 M-1) / 2, wherein α represents the scaling factor.

[0014] According to another aspect of an embodiment of the present invention, a constellation rotation estimation device is also provided, including: a mapping module for mapping a received signal into an original quadrature amplitude modulation (QAM) constellation in a complex plane, wherein the received signal is a baseband digital signal, the original QAM constellation includes a group of signal data points, and the complex plane uses I component and Q component as coordinate components; a compensation module for sequentially using multiple rotation angles to perform rotation angle compensation on the group of signal data points to obtain multiple groups of compensated data points, wherein each group of compensated data points corresponds to a rotated QAM constellation in the complex plane; a calculation module for calculating the graph distance between each of the multiple rotated QAM constellations corresponding to the multiple groups of compensated data points and the theoretical QAM constellation to obtain multiple graph distance values; a determination module for determining, based on the multiple graph distance values, that the rotation angle corresponding to the constellation that is closest to the theoretical QAM constellation in the multiple rotated QAM constellations is the deflection angle of the original QAM constellation caused by frequency offset.

[0015] According to another aspect of an embodiment of the present invention, a non-volatile storage medium is further provided, wherein the non-volatile storage medium includes a stored program, wherein when the program is running, the device where the non-volatile storage medium is located is controlled to execute any one of the above-mentioned constellation diagram rotation estimation methods.

[0016] According to another aspect of an embodiment of the present invention, a computer device is further provided, comprising a memory and a processor, wherein the memory is used to store programs, and the processor is used to run the programs stored in the memory, wherein the program executes any one of the above-mentioned constellation diagram rotation estimation methods when running.

[0017] In an embodiment of the present invention, a received signal is mapped to an original quadrature amplitude modulation (QAM) constellation in a complex plane, and rotation angle compensation is performed on a group of signal data points using multiple rotation angles in sequence to obtain multiple groups of compensated data points. Then, the graph distances between the multiple rotated QAM constellations corresponding to the multiple groups of compensated data points and the theoretical QAM constellation are calculated to obtain multiple graph distance values. Based on the multiple graph distance values, the rotation angle corresponding to the constellation closest to the theoretical QAM constellation among the multiple rotated QAM constellations is determined to be the deflection angle of the original QAM constellation due to frequency offset, thereby achieving the purpose of determining the rotation angle of the QAM constellation due to frequency offset, thereby realizing the technical effect of improving the estimation accuracy of the rotation angle of the QAM constellation due to frequency offset, and further solving the technical problem of the lack of a reliable method for accurately estimating the rotation angle of the QAM constellation due to frequency offset. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0019] Figure 1 is a schematic diagram of a 16-QAM constellation diagram provided according to the relevant technology;

[0020] Figure 2 A hardware structure block diagram of a computer terminal for implementing a constellation diagram rotation estimation method is shown;

[0021] Figure 3 1 is a flow chart of a constellation diagram rotation estimation method according to an embodiment of the present invention;

[0022] Figure 4 is a schematic diagram of constellation rotation caused by frequency offset according to an optional embodiment of the present invention;

[0023] Figure 5 is a schematic diagram of the horizontal axis of a quantized 16-QAM constellation diagram provided according to an optional embodiment of the present invention;

[0024] Figure 6 2 is a flow chart of a method for blindly estimating M-QAM constellation rotation caused by frequency offset according to an optional embodiment of the present invention;

[0025] Figure 7 4 is a structural block diagram of a constellation diagram rotation estimation device provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] First, some nouns or terms that appear in the description of the embodiments of this application are subject to the following interpretations:

[0029] Quadrature Amplitude Modulation (QAM) is a vector modulation method used in wireless communication systems. In QAM, a data signal is represented by the amplitude changes of two mutually orthogonal carrier waves.

[0030] Multi-level Quadrature Amplitude Modulation (M-QAM), M represents the order of the M-QAM modulation method. Common M-QAM forms include 4-QAM, 16-QAM, 64-QAM, etc. Taking 16-QAM as an example, a 16-QAM signal with 16 samples, each sample represents a vector state, 16-QAM has 16 states, and each 4-bit binary number specifies one of the 16 states, such as Figure 1 shown.

[0031] AM is a vector modulation that maps the input bits (generally using Gray code) onto a complex plane (constellation) to form complex modulation symbols. The I and Q components of the symbols (corresponding to the real and imaginary parts of the complex plane, that is, the horizontal and vertical directions) are then amplitude modulated and modulated onto two mutually orthogonal (time domain orthogonal) carriers (coswt and sinwt).

[0032] Constellation diagram, the distribution diagram of signal vector endpoints, is usually used to describe the signal space distribution state of QAM signal.

[0033] According to an embodiment of the present invention, an embodiment of a constellation diagram rotation estimation method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0034] The method embodiment provided in the first embodiment of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 2 FIG. 1 shows a hardware structure block diagram of a computer terminal for implementing a constellation diagram rotation estimation method. Figure 2 As shown, the computer terminal 20 may include one or more (illustrated by 202a, 202b, ..., 202n in the figure) processors (the processor may include but is not limited to a microprocessor MCU or a programmable logic device FPGA and other processing devices), a memory 204 for storing data. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It will be understood by those skilled in the art that Figure 2 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 2 More or fewer components than shown, or with Figure 2 Different configurations shown.

[0035] It should be noted that the one or more processors and / or other data processing circuits described above may generally be referred to herein as "data processing circuitry." The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuitry may be a single, independent processing module, or may be incorporated in whole or in part into any of the other components of the computer terminal 20. As described in the embodiments of the present application, the data processing circuitry serves as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0036] The memory 204 can be used to store software programs of application software and modules, such as program instructions / data storage means corresponding to the constellation rotation estimation method of the embodiments of the present application, and the processor executes various functional applications and data processing by running the software programs and modules stored in the memory 204, i.e. implements the constellation rotation estimation method of the application program as described above. The memory 204 can include a high-speed random access memory, and can also include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory 204 can further include a memory remotely arranged with respect to the processor, which can be connected to the computer terminal 20 through a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0037] The display can be, for example, a touch screen type liquid crystal display (LCD) that can enable a user to interact with the user interface of the computer terminal 20.

[0038] Figure 3 is a flowchart of the constellation rotation estimation method according to the embodiments of the present application, as shown in Figure 3 the method comprises the following steps:

[0039] Step S302, mapping the received signal into an original quadrature amplitude modulation (QAM) constellation in a complex plane, wherein the original QAM constellation includes a set of signal data points, and the complex plane uses I and Q components as coordinate components.

[0040] It should be noted that quadrature amplitude modulation (QAM) is a vector modulation method, and common forms of QAM include 4-QAM, 16-QAM, 64-QAM, etc. Taking 16-QAM as an example, a 16-QAM signal with 16 sample points represents a vector state for each sample point, and 16-QAM has 16 states, and each 4-bit binary number defines a state in the 16 states, and the constellation diagram is as shown in Figure 1 . Figure 1 is a schematic diagram of a 16-QAM constellation according to an optional embodiment of the present application, as shown in Figure 1 , Figure 1 is a schematic diagram of a non-normalized constellation, and 4-bit binary bits 0000 are mapped to coordinates (3, 3), and bits 0001 are mapped to coordinates (1, 3), and so on. When transmission power control is required, the I and Q component amplitudes of the mapping are multiplied by power control coefficients, respectively.

[0041] The original QAM constellation diagram can be a constellation diagram drawn based on a single symbol received signal, and the received signal is Y = [y0, y1, ..., y n ,...,y N-1 ], where N is the number of data points within a single symbol. During signal transmission, constellation rotation may occur between the transmitter and receiver due to frequency deviation. When the system has frequency deviation or frequency deviation fluctuation, the M-QAM system constellation diagram is reflected as a constellation rotation of a certain angle. This angle is the phase caused by the frequency deviation on different time domain symbols. Figure 4 FIG. 1 is a schematic diagram of a constellation diagram rotation caused by a frequency offset according to an optional embodiment of the present invention. Figure 4 As shown in the figure, the black solid dots represent the positions of the data points in the ideal QAM constellation diagram, while the white hollow dots represent the original QAM constellation diagram in which the constellation diagram is rotated due to frequency offset. Figure 4 The method provided in this application can be used to estimate the frequency deviation angle between the original QAM constellation and the ideal constellation.

[0042] Step S304 , performing rotation angle compensation on a group of signal data points using multiple rotation angles in sequence to obtain multiple groups of compensated data points, wherein each group of compensated data points corresponds to a rotated QAM constellation diagram in the complex plane.

[0043] In this step, the direction of the rotation angle used for angle compensation can be opposite to the frequency offset rotation direction of the original QAM constellation. For example, if the frequency offset causes the original QAM constellation to rotate clockwise, the rotation directions corresponding to the multiple rotation angles are all angular directions that rotate the original QAM constellation counterclockwise.

[0044] As an optional embodiment, the process of using multiple rotation angles in sequence to perform rotation angle compensation on a group of signal data points may include the following steps: determining the angle traversal step, the number of traversals and the initial value of the angle traversal; determining multiple rotation angles based on the angle traversal step, the number of traversals and the initial value of the angle traversal; using multiple rotation angles in sequence to perform rotation angle compensation on a group of signal data points to obtain multiple groups of compensated data points, wherein each group of compensated data points is obtained by compensating each data point in the signal data points according to the rotation angle.

[0045] Optionally, the angle traversal step size can be set to Δθ, the number of traversal times K and the angle traversal initial value θ0 can be set, and all data points in the current modulation symbol (i.e., all points in a group of signal data points in the received signal) can be compensated in sequence with the set angles to obtain multiple groups of compensated data points Y'. k∈{0,1,2,...,K-1} represents the kth compensation.

[0046] Step S306 , respectively calculating the graph distances between the plurality of rotated QAM constellation graphs corresponding to the plurality of groups of compensation data points and the theoretical QAM constellation graph to obtain a plurality of graph distance values.

[0047] In this step, the theoretical QAM constellation diagram represents the constellation diagram obtained by mapping the received signal in the absence of constellation diagram rotation caused by frequency offset. The coordinate point set of the theoretical QAM constellation diagram can be expressed as X = [x0, x1, ..., x m ,...,x M-1 ], M represents the order of M-QAM modulation.

[0048] It should be noted that the graph distance can represent the rotational deviation between two constellation diagrams. The better the overlap between the two constellation diagrams, the smaller their graph distance. As the rotation angle of one constellation diagram relative to the other increases, the graph distance between the two constellations also increases. For example, the original QAM constellation diagram is the theoretical QAM constellation diagram rotated by the rotation angle caused by frequency offset. If the rotation angle caused by frequency offset is 0°, the graph distance between the original QAM constellation diagram and the theoretical QAM constellation diagram is 0. As the rotation angle caused by frequency offset increases, the graph distance between the original QAM constellation diagram and the theoretical QAM constellation diagram also increases.

[0049] As an optional embodiment, taking any one target constellation diagram among multiple rotated QAM constellation diagrams as an example, the graph distance between the target constellation diagram and the theoretical QAM constellation diagram can be calculated in the following manner: first, determine multiple nearest data points in the theoretical QAM constellation diagram that correspond one-to-one to multiple target data points included in the target constellation diagram; determine multiple Euclidean distances that correspond one-to-one to the multiple nearest data points and the multiple target data points, wherein any one of the multiple Euclidean distances is the distance between the target data point and the corresponding nearest data point; sum the multiple Euclidean distances to obtain a target graph distance value between the target constellation diagram and the theoretical QAM constellation diagram, wherein the target graph distance value represents the graph distance between the target constellation diagram and the theoretical QAM constellation diagram.

[0050] Optionally, for any data point y' in the target constellation n First, find the data point y' in the theoretical QAM constellation diagram n The theoretical data point x with the closest Euclidean distance m(n) , where the subscript m(n) represents the mapping from n to m, n∈{0,1,...,N-1}, m∈{0,1,...,M-1}; 2) Calculate the data point y' n The Euclidean distance to the nearest data point Where real(·) represents the real part of the signal, and imag(·) represents the imaginary part of the signal. 3) The sum of the Euclidean distances between all data points in the current modulation symbol and their nearest data points is calculated, and the sum of the Euclidean distances is determined as the graph distance value between the target constellation and the theoretical QAM constellation, i.e., the target graph distance value.

[0051] In wireless communication systems, the baseband signal received by the demodulation module from the receiver is a signal that has undergone various stages of amplification and filtering. The receiver cannot know the coordinates of the theoretical data point corresponding to the coordinates (I, Q) of the current received data point. Therefore, the baseband signal must first be quantized to calculate the distance between the actual constellation diagram and the theoretical QAM constellation diagram on the same coordinate scale.

[0052] As an optional embodiment, the process of mapping the received signal into the original orthogonal amplitude modulation (QAM) constellation diagram in the complex plane may include the above-mentioned coordinate quantization processing, specifically including the following steps: determining a target number of data points in the original data points of the received signal, wherein the target number of data points are the target number of data points that rank highest when the received signal is sorted from large to small by amplitude; determining the standard value of the data point corresponding to the received signal based on the target number of data points; and using the data point standard value to quantize the original data points in sequence to obtain the signal data points included in the original QAM constellation diagram.

[0053] The target number is used to refer to the number of target data points that are ranked at the top when all data points in the received signal are sorted from large to small according to amplitude. For example, the received signal may include 1000 original data points. When the order of M-QAM is 16, the signal data points with larger amplitudes among the 1000 original data points are ideally mapped to Figure 1 The target number may be the number of original data points that should be mapped to the four data points (0011), (0000), (1111) and (1100) of the constellation diagram shown in . Alternatively, based on the baseband digital signal Y = [y0, y1, ..., y n ,...,y N-1 ], we can use the sorting algorithm to sort all the data points of the baseband digital signal Y from large to small according to the amplitude, and find the N points with the highest order from the sorted Y. max data points in, The N with the highest ranking in Y max The subscript index of the data point, where N max Indicates the number of targets, this N maxThe amplitude of any one of the data points is greater than that of other data points in the baseband digital signal Y.

[0054] As an optional embodiment, before determining the target number of data points in the original data points of the received signal, the target number can also be determined based on the number of original data points and the number of data points in the theoretical QAM constellation diagram. max =4·N / M to determine the target number, where N represents the number of original data points, M represents the number of data points in the theoretical QAM constellation diagram, and N max Indicates the number of targets.

[0055] Optionally, determining the standard value of the data point corresponding to the received signal based on the target number of data points can include the following steps: calculating the modulus of each of the target number of data points in turn; and taking the median of the modulus of each of the target number of data points as the standard value of the data point corresponding to the received signal.

[0056] The standard values ​​of data points can be used to quantize the data points in the original and ideal QAM constellations, also known as normalization. Before modulation, the source bits undergo a series of operations such as scrambling, interleaving, encoding, and rate matching. The goal is to ensure that the probability of the source bits "0" and "1" occurring is equal. Therefore, after modulation, the distribution of data points at different data points is essentially the same. Based on this universal condition, the following coordinate quantization process is used:

[0057] set up Where median(·) means finding the median, abs(·) means finding the modulus, A norm Indicates the standard value of the data point corresponding to the received signal this time; further, A norm For reference, each data point in the received signal can be quantified where Y norm It represents the signal data point obtained after quantizing each original data point in the received signal. The constellation diagram composed of the above signal data points is the original QAM constellation diagram in this application.

[0058] When calculating the graph distance, it is necessary to determine which theoretical data point in the theoretical QAM constellation has the closest Euclidean distance to any data point in the rotated QAM constellation. Optionally, the nearest data point can be found in the following way: Based on the constellation coordinate quantization step of the above optional embodiment, the amplitude distribution of the four vertices of the original QAM constellation corresponding to the received signal is in Similarly, the theoretical QAM constellation diagram corresponding to the symbol is quantized with the maximum amplitude as the reference, that is, Obtain a quantized theoretical QAM constellation. After quantizing the theoretical QAM constellation corresponding to the symbol modulation scheme at its maximum amplitude, the graph distance between the original QAM constellation and the quantized theoretical QAM constellation can be calculated. Alternatively, the graph distance between each of multiple rotated constellations obtained by rotating the original QAM constellation and the quantized theoretical QAM constellation can be calculated. The constellation rotation angle caused by the frequency offset can then be determined based on these graph distance values.

[0059] Optionally, in order to quickly find the coordinates of the theoretical data point in the quantized theoretical QAM constellation diagram that is closest to the coordinates of the signal data point in the rotated constellation diagram, the following method can be used: for any one of the multiple target data points included in the target constellation diagram, determine the first coordinate in the horizontal coordinate of the data point in the theoretical QAM constellation diagram that is closest to the horizontal coordinate of any one of the data points; determine the second coordinate in the vertical coordinate of the data point in the theoretical QAM constellation diagram that is closest to the vertical coordinate of any one of the data points; based on the first coordinate and the second coordinate, determine the nearest data point in the theoretical QAM constellation diagram corresponding to any one of the data points.

[0060] In order to quickly determine the multiple nearest data points in the theoretical QAM constellation diagram that correspond one-to-one to the multiple target data points included in the target constellation diagram, the following is a specific embodiment of finding the nearest data points:

[0061] Figure 5 This is a schematic diagram of the horizontal axis of the quantized 16-QAM constellation diagram provided according to an optional embodiment of the present invention. Taking the horizontal axis (I axis) of the constellation diagram after quantization of the 16-QAM amplitude maximum value as an example, the horizontal axis of the constellation diagram can be divided into three sections, respectively represented as zone0, zone1, and zone2. When the horizontal coordinate value of the signal data point in the rotated constellation diagram falls into zone0, the horizontal coordinate of the theoretical data point closest to the signal data point is determined to be -1; when the horizontal coordinate of the signal data point falls into zone2, the horizontal coordinate of the theoretical data point closest to the signal data point is 1; when the horizontal coordinate of the signal data point falls into zone1, taking the position of point P in the figure as an example, when the coordinate value of point P is greater than (1 / 3+1) / 2, the horizontal coordinate of the theoretical data point closest to the signal data point is determined to be 1, otherwise the horizontal coordinate of the nearest theoretical data point is determined to be 1 / 3. The same processing process is also applied to the vertical axis (Q axis). Based on the above method, the theoretical data point with the closest Euclidean distance to the signal data point in each rotated constellation diagram can be determined in sequence as the data point closest to both the horizontal and vertical axes.

[0062] In the above specific embodiment, the projections of the horizontal coordinates of the data points in the quantized theoretical QAM constellation diagram on the horizontal axis of the constellation diagram are "-1", "-1 / 3", "1 / 3" and "1" respectively. Therefore, for any target data point in the target constellation diagram, the horizontal coordinate of the arbitrary target data point can be compared with which horizontal coordinate of the data point in the theoretical QAM constellation diagram is closest, and the closest horizontal coordinate is marked as the first coordinate; the same method can be used to obtain the second coordinate that is closest to the vertical coordinate of the arbitrary target data point and the multiple vertical coordinates of the data points in the theoretical QAM constellation diagram. Based on the first coordinate and the second coordinate, a data point in the theoretical QAM constellation diagram can be determined, and the data point is recorded as the nearest data point corresponding to the arbitrary target data point in the theoretical QAM constellation diagram. Repeating the above process can determine the multiple nearest data points corresponding to multiple target data points in the theoretical QAM constellation diagram.

[0063] To further accelerate the aforementioned nearest data point search step, as an optional embodiment, the following method can be employed: amplitude scaling the target constellation diagram based on a scaling factor to obtain a first scaled diagram; amplitude scaling the theoretical QAM constellation diagram based on the scaling factor to obtain a second scaled diagram; and determining, based on the first scaled diagram and the second scaled diagram, a plurality of nearest data points in the theoretical QAM constellation diagram that correspond one-to-one to a plurality of target data points. As an optional embodiment, the scaling factor is determined using the following formula: α = (log2 M - 1) / 2, where α represents the scaling factor.

[0064] Scaling the quantized constellation diagram and the theoretical QAM constellation diagram after quantization and selecting the scaling factor α can avoid the Figure 5 The coordinate points of 1 / 3 in the embodiment reduce the redundant calculation of data processing when the computer executes the judgment program. The data point set corresponding to the first zoomed image after zooming based on the zoom factor α can be expressed as CY=[cy0,cy1,...cy N-1 ]=α·Y norm , the set of theoretical data points corresponding to the second scaled graph after scaling can be expressed as CX=[cx0,cx1,...cx M-1 ]=α·X norm At this time, the horizontal and vertical coordinates of all data points on the theoretical QAM constellation diagram are odd integer multiples of 1 / 2, so it is easy to determine which theoretical data point in the theoretical QAM constellation diagram is closest to the signal data point in the actual constellation diagram drawn based on the received signal after scaling on the coordinate axis.

[0065] Optionally, based on the scaling method, the method for finding the signal data point and the nearest data point can be defined as the SEARCH_NEAREST_CONS method, which is specifically expressed as:

[0066] For data point cy in data point CY n ,n∈{0,1,2,...N-1}, and cy n The horizontal coordinate of the theoretical data point x closest to the data point is:

[0067] If real(cy n )>α,real(cx m(n) )=α, otherwise

[0068] If real(cy n )<-α,real(cx m(n) )=-α, otherwise

[0069] real(cx m(n) )=floor(real(cy n ))+0.5;

[0070] Similarly, with cy n The ordinate of the theoretical data point x closest to the data point is:

[0071] If imag(cy n )>α,imag(cx m(n) )=α, otherwise

[0072] If imag(cy n )<-α,imag(cx m(n) )=-α, otherwise

[0073] imag(cx m(n) )=floor(imag(cy n ))+0.5;

[0074] Among them, cx m(n) ∈CX, floor(·) is the floor function.

[0075] Step S308 : determining, based on the multiple diagram distance values, the rotation angle corresponding to the constellation diagram closest to the theoretical QAM constellation diagram among the multiple rotated QAM constellations as the rotation angle of the original QAM constellation diagram caused by the frequency offset.

[0076] By the above steps, the received signal can be mapped to a raw quadrature amplitude modulation (QAM) constellation diagram in a complex plane, a plurality of rotation angles are used to compensate a group of signal data points in sequence, a plurality of groups of compensated data points are obtained, a plurality of graph distances between a plurality of rotated QAM constellation diagrams corresponding to the plurality of groups of compensated data points and a theoretical QAM constellation diagram are calculated, and a plurality of graph distance values are obtained. According to the plurality of graph distance values, a rotation angle corresponding to a constellation diagram closest to the theoretical QAM constellation diagram in the plurality of rotated QAM constellation diagrams is determined as a deflection angle of the raw QAM constellation diagram caused by frequency offset, so that the purpose of determining the rotation angle of the QAM constellation diagram caused by frequency offset is achieved, thereby realizing the technical effect of improving the estimation accuracy of the rotation angle of the QAM constellation diagram caused by frequency offset, and further solving the technical problem that there is a lack of reliable method for accurately estimating the frequency offset of the QAM signal.

[0077] Figure 6 is a flowchart of a frequency-offset-induced M-QAM constellation diagram rotation blind estimation method according to an optional embodiment of the present application, as shown in Figure 6 , the optional embodiment can include the following specific steps:

[0078] Step one: receiving a single-symbol baseband digital signal Y = [y0, y1,..., y N-1 ];

[0079] Step two: setting an angle traversal step size Δθ, a traversal number K, and an angle traversal initial value θ0, k = 0;

[0080] Step three: compensating the received signal Y

[0081] Step four: finding N max data points with the highest ranking in Y' when sorted by amplitude , where is the index of the N max data points with the highest ranking in Y';

[0082] Step five: normalizing the received signal: , where

[0083] Step six: scaling Y norm according to a scaling factor α = (log2M-1) / 2, that is:

[0084] CY = [cy0, cy1,..., cy N-1 ] = α·Y norm ;

[0085] Step 7: For each data point in CY, use the SEARCH_NEAREST_CONS method to find the nearest data point, and the resulting set is CX ref =[cx m(0) ,cx m(1) ,...,cx m(N-1) ];

[0086] Step 8: Calculate the data CY and set CX of the actual constellation diagram ref Graph distance:

[0087] Dis k =norm2(CY-CX ref ), norm2(·) is the 2-norm;

[0088] Step 9: k=k+1, if k<K, return to step 3, otherwise go to step 10;

[0089] Step 10: Search [Dis0, Dis1, ..., Dis K-1 ] corresponds to the subscript k0 of the minimum value, then the estimated value of the constellation rotation angle is θ est =θ0+Δθ·k0.

[0090] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should be aware that the present invention is not limited by the order of the actions described, because according to the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0091] Through the description of the above embodiments, those skilled in the art can clearly understand that the constellation diagram rotation estimation method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of various embodiments of the present invention.

[0092] According to an embodiment of the present invention, a constellation diagram rotation estimation device for implementing the above constellation diagram rotation estimation method is also provided. Figure 7 is a structural block diagram of a constellation diagram rotation estimation device provided according to an embodiment of the present invention, such as Figure 7As shown, the constellation rotation estimation device comprises a mapping module 72, a compensation module 74, a calculation module 76 and a determination module 78, which are described as follows.

[0093] The mapping module 72 is configured to map the received signal into an original quadrature amplitude modulation (QAM) constellation in a complex plane, wherein the original QAM constellation comprises a set of signal data points, and the complex plane adopts an I component and a Q component as coordinate components.

[0094] The compensation module 74 is connected to the mapping module 72 and configured to sequentially perform rotation angle compensation on the set of signal data points by using a plurality of rotation angles, so as to obtain a plurality of sets of compensated data points, wherein each set of compensated data points corresponds to a rotated QAM constellation in the complex plane.

[0095] The calculation module 76 is connected to the compensation module 74 and configured to respectively calculate a graph distance between the plurality of rotated QAM constellations and a theoretical QAM constellation, so as to obtain a plurality of graph distance values.

[0096] The determination module 78 is connected to the calculation module 76 and configured to determine, according to the plurality of graph distance values, a rotation angle corresponding to a constellation that is closest to the theoretical QAM constellation in the plurality of rotated QAM constellations as a rotation angle of the original QAM constellation caused by frequency offset.

[0097] It should be noted that the mapping module 72, the compensation module 74, the calculation module 76 and the determination module 78 correspond to steps S302 to S308 in the embodiment, and the plurality of modules have the same instances and application scenarios as the corresponding steps, but are not limited to the contents disclosed in the above embodiment.

[0098] The embodiment of the present application can provide a computer device, and optionally, in the embodiment, the computer device can be located in at least one network device of a plurality of network devices of a computer network. The computer device comprises a memory and a processor.

[0099] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the constellation diagram rotation estimation method and device in the embodiments of the present invention. The processor executes the software programs and modules stored in the memory to perform various functional applications and data processing, thereby implementing the above-mentioned constellation diagram rotation estimation method. The memory can include high-speed random access memory and can also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory can further include memory remotely located relative to the processor, and these remote memories can be connected to the computer terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0100] The processor can call information and applications stored in the memory through a transmission device to perform the following steps: mapping a received signal into an original quadrature amplitude modulation (QAM) constellation diagram in a complex plane, wherein the received signal is a baseband digital signal, the original QAM constellation diagram includes a group of signal data points, and the complex plane uses an I component and a Q component as coordinate components; sequentially using multiple rotation angles to perform rotation angle compensation on the group of signal data points to obtain multiple groups of compensated data points, wherein each group of compensated data points corresponds to a rotated QAM constellation diagram in the complex plane; calculating the graph distance between each of the multiple rotated QAM constellations corresponding to the multiple groups of compensated data points and a theoretical QAM constellation diagram to obtain multiple graph distance values; and determining, based on the multiple graph distance values, that the rotation angle corresponding to the constellation diagram that is closest to the theoretical QAM constellation diagram among the multiple rotated QAM constellations is the deflection angle of the original QAM constellation diagram caused by frequency offset.

[0101] A person skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a non-volatile storage medium, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0102] The embodiment of the present invention further provides a non-volatile storage medium. Optionally, in this embodiment, the non-volatile storage medium can be used to store the program code executed by the constellation diagram rotation estimation method provided in the above embodiment.

[0103] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0104] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for executing the following steps: mapping a received signal into an original quadrature amplitude modulation (QAM) constellation diagram in a complex plane, wherein the received signal is a baseband digital signal, the original QAM constellation diagram includes a group of signal data points, and the complex plane uses I component and Q component as coordinate components; sequentially performing rotation angle compensation on the group of signal data points using multiple rotation angles to obtain multiple groups of compensated data points, wherein each group of compensated data points corresponds to a rotated QAM constellation diagram in the complex plane; calculating the graph distance between each of the multiple rotated QAM constellations corresponding to the multiple groups of compensated data points and the theoretical QAM constellation diagram to obtain multiple graph distance values; and determining, based on the multiple graph distance values, the rotation angle corresponding to the constellation diagram that is closest to the theoretical QAM constellation diagram among the multiple rotated QAM constellations as the deflection angle of the original QAM constellation diagram caused by frequency offset.

[0105] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0106] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0107] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0108] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0109] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0110] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a non-volatile storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, and other media that can store program code.

[0111] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A constellation diagram rotation estimation method, characterized in that: include: Mapping a received signal into an original quadrature amplitude modulation (QAM) constellation in a complex plane, wherein the received signal is a baseband digital signal, the original QAM constellation includes a set of signal data points, and the complex plane uses an I component and a Q component as coordinate components; sequentially performing rotation angle compensation on the set of signal data points using a plurality of rotation angles to obtain a plurality of sets of compensated data points, wherein each set of compensated data points corresponds to a rotated QAM constellation diagram in the complex plane; Calculating the graph distance between each of the plurality of rotated QAM constellation graphs corresponding to the plurality of groups of compensation data points and the theoretical QAM constellation graph to obtain a plurality of graph distance values; According to the multiple diagram distance values, it is determined that the rotation angle corresponding to the constellation diagram closest to the theoretical QAM constellation diagram among the multiple rotated QAM constellation diagrams is the deflection angle of the original QAM constellation diagram caused by the frequency offset.

2. The method according to claim 1, characterized in that The method of sequentially performing rotation angle compensation on the set of signal data points using multiple rotation angles to obtain multiple sets of compensated data points includes: Determine the angle traversal step size, number of traversals and the initial value of the angle traversal; Determining a plurality of rotation angles according to the angle traversal step, the number of traversals, and the angle traversal initial value; The plurality of rotation angles are sequentially used to perform rotation angle compensation on the group of signal data points to obtain the plurality of groups of compensated data points, wherein each group of compensated data points is obtained by compensating each data point in the signal data points according to the rotation angle.

3. The method according to claim 1, characterized in that The calculating the graph distance between each of the plurality of rotated QAM constellation graphs corresponding to the plurality of groups of compensation data points and the theoretical QAM constellation graph to obtain a plurality of graph distance values ​​includes: Determine a target diagram distance value between a target constellation diagram among the multiple rotated QAM constellation diagrams and the theoretical QAM constellation diagram in the following manner, wherein the target constellation diagram is any one of the multiple rotated QAM constellation diagrams: Determine a plurality of nearest data points in the theoretical QAM constellation diagram that correspond one-to-one to a plurality of target data points included in the target constellation diagram; Determining a plurality of Euclidean distances between the plurality of closest data points and the plurality of target data points in one-to-one correspondence, wherein any one of the plurality of Euclidean distances is a distance between a target data point and a corresponding closest data point; The multiple Euclidean distances are summed to obtain a target diagram distance value between the target constellation diagram and the theoretical QAM constellation diagram, wherein the multiple diagram distance values ​​include the target diagram distance value.

4. The method according to claim 3, characterized in that Mapping the received signal into an original quadrature amplitude modulation (QAM) constellation in a complex plane includes: Determining a target number of data points among the original data points of the received signal, wherein the target number of data points is the target number of data points that are ranked highest when the received signal is sorted from largest to smallest by amplitude; Determining a standard value of a data point corresponding to the received signal according to the target number of data points; The original data points are quantized in sequence using the data point standard values ​​to obtain the signal data points included in the original QAM constellation diagram.

5. The method according to claim 4, characterized in that Before determining the target number of data points in the original data points of the received signal, the method further includes: The target number is determined according to the number of the original data points and the number of data points in the theoretical QAM constellation diagram.

6. The method according to claim 4, characterized in that The determining, based on the target number of data points, a standard value of the data point corresponding to the received signal includes: Calculating the modulus of each of the target number of data points in sequence; The median of the moduli of the target number of data points is used as the standard value of the data point corresponding to the received signal.

7. The method according to claim 3, characterized in that The determining of a plurality of nearest data points in the theoretical QAM constellation diagram corresponding one-to-one to a plurality of target data points included in the target constellation diagram comprises: Performing amplitude scaling on the target constellation diagram based on the scaling factor to obtain a first scaled diagram; Performing amplitude scaling on the theoretical QAM constellation diagram based on the scaling factor to obtain a second scaled diagram; The multiple nearest data points in the theoretical QAM constellation diagram corresponding one-to-one to the multiple target data points are determined according to the first scaling diagram and the second scaling diagram.

8. The method according to claim 3, characterized in that The determining of a plurality of nearest data points in the theoretical QAM constellation diagram corresponding one-to-one to a plurality of target data points included in the target constellation diagram comprises: For any one of the plurality of target data points included in the target constellation diagram, determining a first coordinate of the data points of the theoretical QAM constellation diagram that is closest to the abscissa of the any one of the data points; Determine a second coordinate among the ordinates of the data points of the theoretical QAM constellation diagram that is closest to the ordinate of the arbitrary data point; The nearest data point corresponding to the arbitrary data point in the theoretical QAM constellation diagram is determined according to the first coordinate and the second coordinate.

9. A non-volatile storage medium, characterized in that: The non-volatile storage medium includes a stored program, wherein when the program is running, the device where the non-volatile storage medium is located is controlled to execute the constellation diagram rotation estimation method according to any one of claims 1 to 8.

10. A computer device, characterized in that: The computer device includes a memory and a processor, the memory is used to store a program, and the processor is used to run the program stored in the memory, wherein the constellation diagram rotation estimation method according to any one of claims 1 to 8 is executed when the program is run.

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