WO2025010964A1 - Ofdm信号的解调方法、装置、计算机设备和存储介质 - Google Patents

Ofdm信号的解调方法、装置、计算机设备和存储介质 Download PDF

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WO2025010964A1
WO2025010964A1 PCT/CN2023/142030 CN2023142030W WO2025010964A1 WO 2025010964 A1 WO2025010964 A1 WO 2025010964A1 CN 2023142030 W CN2023142030 W CN 2023142030W WO 2025010964 A1 WO2025010964 A1 WO 2025010964A1
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target
constellation
signal
matrix
constellation diagram
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French (fr)
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袁超颖
白景鹏
沈军
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China Telecom Corp Ltd Technology Innovation Center
China Telecom Corp Ltd
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China Telecom Corp Ltd Technology Innovation Center
China Telecom Corp Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2697—Multicarrier modulation systems in combination with other modulation techniques
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2647—Arrangements specific to the receiver only
    • H04L27/2649—Demodulators

Definitions

  • the present application relates to the field of communications, and in particular to a demodulation method, apparatus, computer equipment and storage medium for OFDM signals.
  • OFDM Orthogonal Frequency Division Multiplexing
  • the receiving end performs an inverse Fourier transform on the received signal, and then demodulates the signal according to the frequency interval between each subcarrier to obtain the information transmitted on each subcarrier.
  • it is difficult to demodulate OFDM signals due to the interference of carrier frequency deviation and the inability to know the precise frequency interval between subcarriers.
  • the present application provides a demodulation method for an OFDM signal.
  • the method comprises:
  • any estimated value pair demodulating the target signal based on the estimated value pair to obtain a baseband signal corresponding to the target signal, the estimated value pair consisting of any of the frequency interval estimated value and any of the carrier frequency deviation estimated value;
  • any of the baseband signals construct a constellation diagram corresponding to the baseband signal, obtain matrix eigenvalues corresponding to the constellation diagram, and determine a target eigenvalue difference according to the matrix eigenvalues;
  • a target baseband signal is determined from each of the baseband signals according to the target characteristic value differences corresponding to each of the baseband signals.
  • the baseband signal is composed of a plurality of transmission values
  • the demodulating the target signal based on the estimated value pair to obtain the baseband signal corresponding to the target signal includes:
  • a sent value corresponding to the received value is determined according to the number of subcarriers and the estimated value pair.
  • constructing a constellation diagram corresponding to the baseband signal and obtaining matrix eigenvalues corresponding to the constellation diagram include:
  • connection edge weight For any two constellation points in the constellation diagram, constructing a connection edge weight between the two constellation points according to the coordinates of the two constellation points in the constellation diagram;
  • a Laplace matrix corresponding to the constellation diagram is constructed, and the eigenvalues of the Laplace matrix are used as the matrix eigenvalues.
  • connection edge weight between the two constellation points according to the coordinates of the two constellation points in the constellation graph includes:
  • connection edge weight between the two constellation points is constructed by a Gaussian kernel function.
  • determining a target eigenvalue difference according to the matrix eigenvalue comprises:
  • the difference between every two adjacent matrix eigenvalues in the eigenvalue queue is determined, and the largest difference among the differences is used as the target eigenvalue difference.
  • determining a target baseband signal from each of the baseband signals according to the target characteristic value difference corresponding to each of the baseband signals includes:
  • the baseband signal corresponding to the largest target eigenvalue difference among the target eigenvalue differences is used as the target baseband signal.
  • the present application also provides a demodulation device for an OFDM signal.
  • the device comprises:
  • a first determination module is used to determine a plurality of frequency interval estimated values and a plurality of carrier frequency deviation estimated values of each subcarrier of the target signal;
  • a demodulation module configured to demodulate the target signal based on any estimation pair to obtain a baseband signal corresponding to the target signal, wherein the estimation pair is composed of any first estimation pair and any second estimation pair;
  • a construction module used for constructing a constellation diagram corresponding to any of the baseband signals, obtaining matrix eigenvalues corresponding to the constellation diagram, and determining a target eigenvalue difference according to the matrix eigenvalues;
  • the second determination module is used to determine the target baseband signal from each of the baseband signals according to the target characteristic value difference corresponding to each of the baseband signals.
  • the baseband signal is composed of a plurality of transmission values
  • the demodulation module is further used for:
  • a sent value corresponding to the received value is determined according to the number of subcarriers and the estimated value pair.
  • the building block is further used to:
  • connection edge weight For any two constellation points in the constellation diagram, constructing a connection edge weight between the two constellation points according to the coordinates of the two constellation points in the constellation diagram;
  • a Laplace matrix corresponding to the constellation diagram is constructed, and the eigenvalues of the Laplace matrix are used as the matrix eigenvalues.
  • the building block is further used to:
  • connection edge weight between the two constellation points is constructed by a Gaussian kernel function.
  • the building block is further used to:
  • the difference between every two adjacent matrix eigenvalues in the eigenvalue queue is determined, and the largest difference among the differences is used as the target eigenvalue difference.
  • the second determining module is further used to:
  • the baseband signal corresponding to the largest target eigenvalue difference among the target eigenvalue differences is used as the target baseband signal.
  • the present application further provides a computer device.
  • the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor:
  • any estimated value pair demodulating the target signal based on the estimated value pair to obtain a baseband signal corresponding to the target signal, the estimated value pair consisting of any of the frequency interval estimated value and any of the carrier frequency deviation estimated value;
  • any of the baseband signals construct a constellation diagram corresponding to the baseband signal, obtain matrix eigenvalues corresponding to the constellation diagram, and determine a target eigenvalue difference according to the matrix eigenvalues;
  • a target baseband signal is determined from each of the baseband signals according to the target characteristic value differences corresponding to each of the baseband signals.
  • the baseband signal is composed of a plurality of transmission values
  • the demodulating the target signal based on the estimated value pair to obtain the baseband signal corresponding to the target signal includes:
  • a sent value corresponding to the received value is determined according to the number of subcarriers and the estimated value pair.
  • constructing a constellation diagram corresponding to the baseband signal and obtaining matrix eigenvalues corresponding to the constellation diagram include:
  • connection edge weight For any two constellation points in the constellation diagram, constructing a connection edge weight between the two constellation points according to the coordinates of the two constellation points in the constellation diagram;
  • a Laplace matrix corresponding to the constellation diagram is constructed, and the eigenvalues of the Laplace matrix are used as the matrix eigenvalues.
  • connection edge weight between the two constellation points according to the coordinates of the two constellation points in the constellation graph includes:
  • connection edge weight between the two constellation points is constructed by a Gaussian kernel function.
  • determining a target eigenvalue difference according to the matrix eigenvalue comprises:
  • the difference between every two adjacent matrix eigenvalues in the eigenvalue queue is determined, and the largest difference among the differences is used as the target eigenvalue difference.
  • determining a target baseband signal from each of the baseband signals according to the target characteristic value difference corresponding to each of the baseband signals includes:
  • the baseband signal corresponding to the largest target eigenvalue difference among the target eigenvalue differences is used as the target baseband signal.
  • the present application further provides a computer-readable storage medium.
  • the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor:
  • any estimated value pair demodulating the target signal based on the estimated value pair to obtain a baseband signal corresponding to the target signal, the estimated value pair consisting of any of the frequency interval estimated value and any of the carrier frequency deviation estimated value;
  • any of the baseband signals construct a constellation diagram corresponding to the baseband signal, obtain matrix eigenvalues corresponding to the constellation diagram, and determine a target eigenvalue difference according to the matrix eigenvalues;
  • a target baseband signal is determined from each of the baseband signals according to the target characteristic value differences corresponding to each of the baseband signals.
  • the baseband signal is composed of a plurality of transmission values
  • the demodulating the target signal based on the estimated value pair to obtain the baseband signal corresponding to the target signal includes:
  • a sent value corresponding to the received value is determined according to the number of subcarriers and the estimated value pair.
  • the constellation diagram corresponding to the baseband signal is constructed, and the constellation diagram corresponding to the baseband signal is obtained.
  • Matrix eigenvalues including:
  • connection edge weight For any two constellation points in the constellation diagram, constructing a connection edge weight between the two constellation points according to the coordinates of the two constellation points in the constellation diagram;
  • a Laplace matrix corresponding to the constellation diagram is constructed, and the eigenvalues of the Laplace matrix are used as the matrix eigenvalues.
  • connection edge weight between the two constellation points according to the coordinates of the two constellation points in the constellation graph includes:
  • connection edge weight between the two constellation points is constructed by a Gaussian kernel function.
  • determining a target eigenvalue difference according to the matrix eigenvalue comprises:
  • the difference between every two adjacent matrix eigenvalues in the eigenvalue queue is determined, and the largest difference among the differences is used as the target eigenvalue difference.
  • determining a target baseband signal from each of the baseband signals according to the target characteristic value difference corresponding to each of the baseband signals includes:
  • the baseband signal corresponding to the largest target eigenvalue difference among the target eigenvalue differences is used as the target baseband signal.
  • the present application further provides a computer program product.
  • the computer program product includes a computer program, which, when executed by a processor, causes the processor to:
  • any estimated value pair demodulating the target signal based on the estimated value pair to obtain a baseband signal corresponding to the target signal, the estimated value pair consisting of any of the frequency interval estimated value and any of the carrier frequency deviation estimated value;
  • any of the baseband signals construct a constellation diagram corresponding to the baseband signal, obtain matrix eigenvalues corresponding to the constellation diagram, and determine a target eigenvalue difference according to the matrix eigenvalues;
  • a target baseband signal is determined from each of the baseband signals according to the target characteristic value differences corresponding to each of the baseband signals.
  • the baseband signal is composed of a plurality of transmission values
  • the demodulating the target signal based on the estimated value pair to obtain the baseband signal corresponding to the target signal includes:
  • a sent value corresponding to the received value is determined according to the number of subcarriers and the estimated value pair.
  • constructing a constellation diagram corresponding to the baseband signal and obtaining matrix eigenvalues corresponding to the constellation diagram include:
  • connection edge weight For any two constellation points in the constellation diagram, constructing a connection edge weight between the two constellation points according to the coordinates of the two constellation points in the constellation diagram;
  • a Laplace matrix corresponding to the constellation diagram is constructed, and the eigenvalues of the Laplace matrix are used as the matrix eigenvalues.
  • connection edge weight between the two constellation points according to the coordinates of the two constellation points in the constellation graph includes:
  • connection edge weight between the two constellation points is constructed by a Gaussian kernel function.
  • determining a target eigenvalue difference according to the matrix eigenvalue comprises:
  • the difference between every two adjacent matrix eigenvalues in the eigenvalue queue is determined, and the largest difference among the differences is used as the target eigenvalue difference.
  • determining a target baseband signal from each of the baseband signals according to the target characteristic value difference corresponding to each of the baseband signals includes:
  • the baseband signal corresponding to the largest target eigenvalue difference among the target eigenvalue differences is used as the target baseband signal.
  • FIG1 is a schematic flow chart of a demodulation method for an OFDM signal in one embodiment
  • FIG2 is a schematic diagram of a constellation diagram in one embodiment
  • FIG3 is a schematic diagram of a flow chart of step 104 in one embodiment
  • FIG4 is a schematic diagram of a flow chart of step 106 in one embodiment
  • FIG5 is a schematic diagram of a flow chart of step 106 in one embodiment
  • FIG6 is a schematic diagram of a difference between two adjacent eigenvalues in one embodiment
  • FIG7 is a schematic flow chart of a demodulation method for an OFDM signal in one embodiment
  • FIG8 is a schematic diagram of a simulation experiment in one embodiment
  • FIG9 is a block diagram of a demodulation device for an OFDM signal in one embodiment
  • FIG. 10 is a diagram showing the internal structure of a computer device in one embodiment.
  • the carrier frequency deviation and frequency interval can be estimated through blind separation or cyclic prefix, and then the received signal can be demodulated according to the estimated carrier frequency deviation and frequency interval.
  • the average value of the phase difference is difficult to converge, and only a rough estimate of the carrier frequency deviation can be made; and the method based on cyclic prefix estimation assumes that the signal follows the IEEE802.16e protocol, but the signal in non-cooperative mode may not follow the IEEE related protocol or the received cyclic prefix is incomplete, resulting in inaccurate estimation and low accuracy of the demodulated signal.
  • a demodulation method for an OFDM signal is provided. This embodiment is illustrated by applying the method to a terminal. It is understandable that the method can also be applied to a server, or to a system including a terminal and a server, and is implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:
  • Step 102 determining a plurality of frequency interval estimates and a plurality of carrier frequency deviation estimates for each subcarrier of the target signal.
  • the target signal is a signal received by a terminal (the terminal may be a receiver of an OFDM signal).
  • An OFDM signal is formed by the superposition of multiple subcarriers, and the frequency difference between each subcarrier is the frequency interval.
  • the difference between the carrier frequency of the target signal and the carrier frequency sent by the transmitter due to interference and other factors is the carrier frequency deviation.
  • the embodiment of the present application does not specifically limit the method for estimating the estimated frequency interval value and the estimated carrier frequency deviation value, and any existing method for estimating the estimated frequency interval value and the estimated carrier frequency deviation value is applicable to the embodiment of the present application, such as the blind separation method, the estimation method based on the cyclic prefix, etc.
  • the estimated frequency interval or carrier frequency deviation is an interval
  • multiple values can be taken from the interval as the frequency interval estimated value or the carrier frequency deviation estimated value (hereinafter collectively referred to as the estimated value).
  • the estimated value can be taken from the interval at medium intervals as the estimated value, or starting from the center of the interval, gradually taking values at increasing intervals outward as the estimated value, etc., and the embodiments of the present application do not specifically limit this.
  • Step 104 for any estimation value pair, demodulate the target signal based on the estimation value pair to obtain a baseband signal corresponding to the target signal, the estimation value pair consisting of any frequency interval estimation value and any carrier frequency deviation estimation value.
  • any frequency interval estimated value and any carrier frequency deviation estimated value can be combined into an estimated value pair.
  • the frequency interval estimated value or the carrier frequency deviation estimated value in different estimated value pairs can be repeated, as long as each estimated value pair is different: for example, the frequency interval estimated value A and the carrier frequency deviation estimated value A can form an estimated value pair, and the frequency interval estimated value A and the carrier frequency deviation estimated value B can also form an estimated value pair.
  • the target signal can be demodulated once according to the frequency interval estimate and carrier frequency deviation estimate in the estimate pair to obtain the baseband signal corresponding to the estimate pair. After verifying the accuracy of the baseband signal based on the constellation diagram corresponding to the baseband signal, the target baseband signal with the highest accuracy can be obtained from each baseband signal.
  • Step 106 for any baseband signal, construct a constellation diagram corresponding to the baseband signal, obtain matrix eigenvalues corresponding to the constellation diagram, and determine the target eigenvalue difference according to the matrix eigenvalues.
  • the receiver when receiving a target signal, the receiver will oversample the target signal using a higher sampling frequency.
  • the received value obtained through one sampling can obtain a binary signal in the baseband signal, and then the binary signal can be mapped to the complex plane (I path and Q path are mapped to the horizontal axis and vertical axis respectively) to obtain a constellation point.
  • the constellation diagram corresponding to the baseband signal can be obtained.
  • the constellation diagram can be represented by a matrix.
  • each element in the matrix can represent the distance weight between the constellation point corresponding to the column where the element is located and the constellation point corresponding to the row where the element is located.
  • the element located in the i-th row and j-th column of the matrix represents the distance weight between the i-th constellation point and the j-th constellation point; at the same time, in order to make the distance weight of the constellation points closer to each other larger and facilitate subsequent calculations, the distance weight can be made inversely proportional to the actual distance between the constellation points.
  • the distance weight can be calculated based on the coordinates of the two constellation points in the constellation diagram.
  • the inverse of the straight-line distance between the two constellation points can be directly taken as the distance weight, or the noise parameter can be considered at the same time, and the distance weight is constructed by the noise parameter and the inverse of the straight-line distance between the constellation points, etc.
  • the embodiment of the present application does not make specific limitations on this.
  • the matrix eigenvalue is the eigenvalue corresponding to the matrix of the constellation diagram.
  • the definition of the target eigenvalue difference (eigengap, also called eigengap) is the largest value in the difference between two adjacent eigenvalues after arranging the eigenvalues of the matrix from large to small.
  • the target eigenvalue difference can reflect the stability of the clusters formed by each node in the graph.
  • a value that can characterize the degree of aggregation of each constellation point in the constellation diagram can be obtained, and then the value can be used to determine which constellation diagram has the best degree of aggregation of each constellation point, that is, which constellation diagram is the optimal constellation diagram.
  • Step 108 determining a target baseband signal from each baseband signal according to the target characteristic value difference corresponding to each baseband signal.
  • the received value obtained by sampling the target signal Since the modulation mode corresponding to the target signal is certain, the received value obtained by sampling the target signal The types of eigenvalues are limited, so only limited types of binary signal combinations can be demodulated according to the target signal. Therefore, after eliminating the carrier frequency deviation, multiple binary signals will show the aggregation shown in the right figure of Figure 2 in the constellation diagram. Since the target eigenvalue difference can reflect the aggregation degree of the constellation points in the constellation diagram, and the more the constellation points are aggregated, the better the true value of each binary signal is restored, and the closer the carrier frequency deviation and frequency interval are to the true value, the target baseband signal closest to the true value can be determined from each baseband signal according to the target eigenvalue difference.
  • the largest target eigenvalue difference (representing the best aggregation of constellation points in the constellation diagram) can be directly used as the target baseband signal.
  • the frequency interval estimate and the carrier frequency deviation estimate are an interval
  • an estimate pair corresponding to the largest target eigenvalue difference can be further obtained, and multiple frequency interval estimate values and multiple carrier frequency deviation estimate values are re-obtained from the frequency interval estimate and the carrier frequency deviation estimate of the estimate pair to construct a new estimate pair (for example, taking the frequency interval estimate as an example, a smaller distance interval can be preset, and with the frequency interval estimate as the center, a new frequency interval estimate value is taken every distance interval until the number of new frequency interval estimate values meets the requirement.
  • Similar operations can also be performed for the carrier frequency deviation estimate), and then the above process is repeated for each new estimate pair, and the baseband signal corresponding to each new estimate pair and the target eigenvalue difference corresponding to the baseband signal are obtained, and then the newly obtained target eigenvalue differences are compared with the original largest target eigenvalue difference, and the largest target eigenvalue difference is reselected; the above process can be repeated multiple times, and the preset distance interval is reduced each time, until the number of cycles reaches a threshold, or the largest target eigenvalue difference in the previous round is still the largest target eigenvalue difference in this round.
  • the demodulation method of OFDM signal obtained in the embodiment of the present application obtains multiple estimated carrier frequency deviations and frequency intervals, and infers the baseband signal according to each possible combination of carrier frequency deviations and frequency intervals, obtains the constellation diagram corresponding to the baseband signal, calculates the target eigenvalue difference expressed by the constellation diagram matrix, and then selects the target baseband signal according to the target eigenvalue difference.
  • the target eigenvalue difference can reflect the degree of aggregation of each constellation point cluster in the constellation diagram, and the degree of aggregation of the constellation point cluster is related to the accuracy of the estimated value
  • the target baseband signal is selected according to the eigenvalue difference, and the constellation point cluster that best meets the requirements, that is, the target baseband signal that is closest to the true value can be selected, so the accuracy of demodulating the OFDM signal can be improved when the carrier frequency deviation and frequency interval are unknown.
  • the baseband signal is composed of a plurality of transmission values.
  • the target signal is demodulated based on the estimated value to obtain a baseband signal corresponding to the target signal, including the following steps.
  • Step 302 Obtain reception values corresponding to the target signal at multiple time instants and the number of subcarriers corresponding to the target signal.
  • Step 304 for any received value, determine the sent value corresponding to the received value according to the number of subcarriers and the estimated value pair.
  • the transmission value is the binary signal in the aforementioned embodiment, and multiple binary signals are combined to form the information that the transmitter needs to send, that is, the baseband signal.
  • the receiver When receiving the target signal, the receiver will sample the target signal multiple times, and one sampling can obtain a received value.
  • the received value is essentially the result of superimposing multiple orthogonal subcarriers.
  • the carrier frequency deviation of the received value is eliminated by the carrier frequency deviation estimate in the estimate pair, and each subcarrier is decomposed according to the frequency interval estimate, so that the transmission value corresponding to the received value can be obtained.
  • the transmitted value can be inferred from the received value:
  • r k refers to the kth received value collected within a sampling period
  • h k is the channel impulse response of the channel
  • M is the number of subcarriers (obtained according to the ratio of the total bandwidth of the target signal to the estimated frequency interval)
  • s k is the transmitted value corresponding to r k
  • e j2 ⁇ is a representation of imaginary numbers
  • f 0 is the estimated carrier frequency deviation
  • f is the estimated frequency interval
  • T s is the sampling period
  • n k is the noise parameter.
  • the value of sk that is, the transmission value
  • the transmission value is inferred for all the collected receiving values, and the baseband signal corresponding to the target signal collected in this sampling period can be obtained.
  • the demodulation method of the OFDM signal determines the transmission value corresponding to each received value of the target signal according to the number of subcarriers corresponding to the target signal and the estimated value pair, thereby obtaining the baseband signal corresponding to the target signal. Then, a constellation diagram corresponding to the baseband signal can be constructed according to each transmission value and the target eigenvalue difference corresponding to the baseband signal can be obtained, and the target baseband signal can be selected according to the target eigenvalue difference, which can improve the accuracy of demodulating the OFDM signal when the carrier frequency deviation and frequency interval are unknown.
  • step 106 constructing a constellation diagram corresponding to the baseband signal and obtaining matrix eigenvalues corresponding to the constellation diagram include the following steps.
  • Step 402 construct a constellation diagram according to each transmission value corresponding to the target signal, where the constellation points in the constellation diagram correspond to the transmission values one by one.
  • Step 404 for any two constellation points in the constellation diagram, construct a connection edge weight between the two constellation points according to the coordinates of the two constellation points in the constellation diagram.
  • Step 406 construct a weight matrix corresponding to the constellation diagram according to the weights of the connection edges between the constellation points.
  • Step 408 construct a Laplace matrix corresponding to the constellation diagram according to the weight matrix, and use the eigenvalues of the Laplace matrix as matrix eigenvalues.
  • the transmission values of the target signal are projected onto the complex plane to obtain constellation points, and each constellation point constitutes a constellation diagram.
  • the constellation diagram can be represented by a Laplace matrix.
  • the Laplace matrix can be calculated based on the weight matrix of the constellation diagram.
  • the edge weights between the constellation points can be constructed based on the coordinates of the constellation points in the constellation diagram (when the constellation points are the same, the edge weights can be set to 0, that is, the diagonal elements of the weight matrix are all 0).
  • the edge weights are obtained by taking the inverse of the straight-line distance between the coordinates, or the distance weights are obtained by other methods of constructing distance weights based on the distance between the two points.
  • the weight matrix can be obtained by setting the element in the i-th row and j-th column of the weight matrix as the edge weight between the i-th constellation point and the j-th constellation point, and then the Laplace matrix of the constellation diagram can be calculated according to the following formula (II):
  • L represents the Laplace matrix
  • D is a diagonal matrix whose element in the i-th row and i-th column is equal to the sum of all elements in the i-th row of the weight matrix
  • W represents the weight matrix
  • the demodulation method of OFDM signal constructs a Laplace matrix corresponding to the constellation diagram, and obtains the matrix eigenvalue based on the Laplace matrix. Since the Laplace matrix can accurately express the distance and connection between the constellation points in the constellation diagram, using the Laplace matrix as the matrix corresponding to the constellation diagram can improve the reflection of the target eigenvalue difference on the degree of aggregation of the constellation points in the constellation diagram, thereby improving the determination accuracy of the target baseband signal.
  • step 404 constructing the connection edge weight between the two constellation points according to the coordinates of the two constellation points in the constellation graph includes the following steps.
  • connection edge weight between the two constellation points is constructed through the Gaussian kernel function.
  • a Gaussian kernel function can be used to construct the edge weight.
  • the Gaussian kernel function is a monotonically decreasing function of the Euclidean distance between two points, that is, the greater the distance between the two points, the smaller the edge weight calculated by the Gaussian kernel function; at the same time, the relationship between the Euclidean distance between the two points and the edge weight can be controlled by controlling the parameter ⁇ in the Gaussian kernel function.
  • the change of the Euclidean distance between the two points has little effect on the change of the edge weight, that is, it can achieve the effect of making the constellation points with a long distance be classified into one category, making the constellation diagram with loose clustering of constellation points also have a large target eigenvalue difference, reducing the accuracy requirements for the estimated value pairs, and improving the effect of obtaining the target baseband signal speed;
  • ⁇ is large, the change of the Euclidean distance between the two points has a greater effect on the change of the edge weight, that is, it can achieve the effect of making the constellation points with a short distance be classified into one category, improving the accuracy requirements for the estimated value pairs, and improving the accuracy of the target baseband signal.
  • ⁇ can be set to be positively correlated with the noise power parameter.
  • the specific relationship between ⁇ and the noise power parameter can be obtained from the literature. The technician sets it based on experience. It is necessary to select a suitable ⁇ value here, because when the ⁇ value is too small, the edge weights between the points will be relatively similar, making it difficult to distinguish points with different distances from each other; when the ⁇ value is too large, the edge weights will be sensitive to the noise in the constellation diagram, causing the noise to significantly interfere with the value of the edge weights.
  • the Scott rule or the Silverman rule can be used to calculate ⁇ . The method of calculating ⁇ by the Scott rule can be found in the following formula (III):
  • ⁇ is an estimate of ⁇
  • K is the total number of received values collected in one sampling period
  • IQR refers to the interquartile range of the signal.
  • connection edge weight obtained based on the Gaussian kernel function, the noise power parameter and the Euclidean distance of the coordinates of the constellation points can be shown as formula (III):
  • the demodulation method of OFDM signals constructs the connection edge weights through a Gaussian kernel function, and sets the parameter ⁇ in the Gaussian kernel function according to the noise power parameter.
  • the noise power parameter takes different values, the accuracy requirement for the target baseband signal can be adaptively adjusted accordingly to ensure that the determination speed of the target baseband signal is not too slow.
  • step 106 determining a target eigenvalue difference according to the matrix eigenvalue includes the following steps.
  • Step 502 sort the eigenvalues of each matrix from large to small to obtain an eigenvalue queue.
  • Step 504 determining the difference between every two adjacent matrix eigenvalues in the eigenvalue queue, and taking the largest difference among the differences as the target eigenvalue difference.
  • the target eigenvalue difference can be obtained by sorting the matrix eigenvalues to obtain an eigenvalue queue, and then the largest difference between the differences between two adjacent matrix eigenvalues in the eigenvalue queue is obtained.
  • FIG. 6 the result after sorting the eigenvalues of the Laplace matrix from large to small is shown. It can be seen that the difference between the eigenvalues in the area selected in the figure is the largest, so the difference is the target eigenvalue difference.
  • the demodulation method of OFDM signal arranges the eigenvalues from large to small and calculates the maximum value of the difference between two adjacent eigenvalues to obtain the target eigenvalue difference. Since the target eigenvalue difference can reflect the degree of aggregation of each constellation point cluster in the constellation diagram, and the degree of aggregation of the constellation point cluster is related to the accuracy of the estimated value, the target baseband signal can be selected according to the eigenvalue difference, and the constellation point cluster that best meets the requirements, that is, the target baseband signal that is closest to the true value, can be selected, so that the accuracy of demodulating the OFDM signal can be improved when the carrier frequency deviation and the frequency interval are unknown.
  • determining a target baseband signal from each baseband signal according to a target characteristic value difference corresponding to each baseband signal includes:
  • the baseband signal corresponding to the largest target eigenvalue difference among the target eigenvalue differences is taken as the target baseband signal.
  • the target eigenvalue difference when the target eigenvalue difference is the largest, it means that the clustering of the constellation points in the constellation diagram is the tightest, the rotation of the constellation points is eliminated, and the constellation points are closest to the true value; therefore, among the baseband signals, the baseband signal with the largest corresponding target eigenvalue difference is the baseband signal closest to the true value.
  • the baseband signal with the largest value is used as the target baseband signal, so as to obtain the result after demodulating the received OFDM signal.
  • the demodulation method of OFDM signal uses the baseband signal corresponding to the largest target eigenvalue difference as the target baseband signal. Since the baseband signal corresponding to the largest target eigenvalue difference is closest to the true value, the determination accuracy of the target baseband signal can be improved.
  • all possible frequency intervals and carrier frequency deviations can be traversed.
  • the intervals in which the frequency intervals and carrier frequency deviations may be located or the values that may correspond can be determined, from which the frequency interval estimates and carrier frequency deviation estimates that need to be traversed are selected, and all selected frequency interval estimates and carrier frequency deviation estimates are traversed: for example, a fixed frequency interval estimate can be selected first, and then the carrier frequency deviation estimate is selected and combined with the fixed frequency interval estimate, and the constellation diagram of the baseband signal demodulated based on the combination, the Laplace matrix of the constellation diagram, and the eigengap corresponding to the Laplace matrix are calculated.
  • the frequency interval estimate is reselected, and the above process is repeated until the frequency interval estimate is completely traversed.
  • the subcarrier frequency interval, carrier frequency deviation and demodulation result corresponding to the target signal can be obtained.
  • the method of obtaining the baseband signal, the method of constructing the Laplace matrix and the method of calculating the eigengap can refer to the description of the aforementioned embodiment, and the embodiments of the present application will not be repeated here.
  • the OFDM signal sent by the transmitter is set to have 4 subcarriers, each subcarrier is modulated by 4QAM (a quadrature amplitude modulation method), and the frequency interval between adjacent subcarriers is 1MHz.
  • the sampling period of the receiver is set to 1 ⁇ s, 1024 samples are sampled in each sampling period, the carrier frequency deviation is 0.055MHz, the channel is an AWGN channel, the channel impulse response is 30dB, and the ⁇ 2 in the Gaussian kernel function is 64 times the noise power parameter. Traversing each frequency interval estimate and carrier frequency deviation estimate, calculating various combinations of eigengap, the result shown in the upper part of FIG8 can be obtained.
  • the combination with the largest eigengap is selected. It can be seen that the estimated carrier frequency deviation corresponding to the maximum eigengap is 0.055MHz, which is exactly equal to the carrier frequency deviation set for the receiver in the simulation.
  • the constellation diagram before carrier frequency deviation recovery, the difference between two adjacent eigenvalues when the estimated carrier frequency deviation is 0.055MHz, and the constellation diagram after carrier frequency deviation recovery can be seen in the lower part of Figure 8.
  • the above method can be applied to the scenario of sensing the unauthorized use of spectrum.
  • information such as the frequency interval and carrier frequency deviation of the unauthorized use of spectrum can be obtained, and then the behavior of unauthorized use of spectrum within the coverage of the operator's private network can be sensed, which can help operators provide active perception security capability services for the wireless networks of private network customers and industry users, and avoid security threats such as eavesdropping, tampering, and interference to users' communications in the wireless network.
  • the demodulation method of OFDM signals provided in the embodiment of the present application can accurately estimate the frequency interval and carrier frequency deviation of the OFDM system. Theoretically, as long as a sufficient number of frequency interval estimation values and carrier frequency deviation estimation values are taken, the frequency interval estimation values and carrier frequency deviation estimation values can be made infinitely close to the true values of the frequency interval and carrier frequency deviation, thereby improving the estimation accuracy of the frequency interval and carrier frequency deviation, and further improving the accuracy of demodulating OFDM signals in a non-cooperative communication mode.
  • steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.
  • the embodiment of the present application also provides an OFDM signal for implementing the above-mentioned
  • the demodulation device of an OFDM signal according to the demodulation method is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of the demodulation device of one or more OFDM signals provided below can refer to the limitations of the demodulation method of OFDM signals above, and will not be repeated here.
  • a demodulation device 900 for an OFDM signal comprising: a first determination module 902, a demodulation module 904, a construction module 906, and a second determination module 908, wherein:
  • a first determination module 902 is used to determine a plurality of frequency interval estimated values and a plurality of carrier frequency deviation estimated values of each subcarrier of a target signal;
  • a demodulation module 904 is used to demodulate the target signal based on any estimation pair to obtain a baseband signal corresponding to the target signal, wherein the estimation pair is composed of any first estimation pair and any second estimation pair;
  • a construction module 906 is used to construct a constellation diagram corresponding to any of the baseband signals, obtain matrix eigenvalues corresponding to the constellation diagram, and determine a target eigenvalue difference according to the matrix eigenvalues;
  • the second determination module 908 is used to determine a target baseband signal from each of the baseband signals according to the target characteristic value difference corresponding to each of the baseband signals.
  • the demodulation device of OFDM signal obtained in the embodiment of the present application obtains multiple estimated carrier frequency deviations and frequency intervals, and infers the baseband signal according to each possible combination of carrier frequency deviations and frequency intervals, obtains the constellation diagram corresponding to the baseband signal, calculates the target eigenvalue difference expressed by the constellation diagram matrix, and then selects the target baseband signal according to the target eigenvalue difference.
  • the target eigenvalue difference can reflect the degree of aggregation of each constellation point cluster in the constellation diagram, and the degree of aggregation of the constellation point cluster is related to the accuracy of the estimated value
  • the target baseband signal is selected according to the eigenvalue difference, and the constellation point cluster that best meets the requirements, that is, the target baseband signal that is closest to the true value can be selected, so the accuracy of demodulating the OFDM signal can be improved when the carrier frequency deviation and frequency interval are unknown.
  • the baseband signal is composed of a plurality of transmission values
  • the demodulation module 904 is further configured to:
  • a sent value corresponding to the received value is determined according to the number of subcarriers and the estimated value pair.
  • the building module 906 is further configured to:
  • connection edge weight For any two constellation points in the constellation diagram, constructing a connection edge weight between the two constellation points according to the coordinates of the two constellation points in the constellation diagram;
  • a Laplace matrix corresponding to the constellation diagram is constructed, and the eigenvalues of the Laplace matrix are used as the matrix eigenvalues.
  • the building module 906 is further configured to:
  • connection edge weight between the two constellation points is constructed by a Gaussian kernel function.
  • the building module 906 is further configured to:
  • the difference between every two adjacent matrix eigenvalues in the eigenvalue queue is determined, and the largest difference among the differences is used as the target eigenvalue difference.
  • the second determining module 908 is further configured to:
  • the baseband signal corresponding to the largest target eigenvalue difference among the target eigenvalue differences is used as the target baseband signal.
  • Each module in the above-mentioned demodulation device of OFDM signal can be implemented in whole or in part by software, hardware and their combination.
  • Each module can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each module above.
  • a computer device which may be a server, and its internal structure diagram may be shown in FIG10.
  • the computer device includes a processor, a memory, and a network interface connected via a system bus.
  • the processor of the computer device is used to provide computing and control capabilities.
  • the memory of the computer device includes a non-volatile storage medium and an internal memory.
  • the non-volatile storage medium stores an operating system and a computer program.
  • the internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium.
  • the network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a demodulation method of an OFDM signal is implemented.
  • FIG. 10 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied.
  • the specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.
  • a computer device including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.
  • a computer-readable storage medium on which a computer program is stored.
  • the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.
  • a computer program product including a computer program, which implements the steps in the above method embodiments when executed by a processor.
  • user information including but not limited to user device information, user personal information, etc.
  • data including but not limited to data used for analysis, stored data, displayed data, etc.
  • any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory.
  • Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc.
  • Volatile memory can include random access memory (RAM) or external cache memory, etc.
  • RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).
  • SRAM static random access memory
  • DRAM dynamic random access memory
  • the database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database.
  • Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this.
  • the processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, etc., but are not limited to this.

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Abstract

本申请涉及一种OFDM信号的解调方法、装置、计算机设备和存储介质。所述方法包括：确定目标信号各子载波的多个频率间隔预估值、及多个载频偏差预估值（S102）；针对任一预估值对，基于预估值对对目标信号进行解调，得到目标信号对应的基带信号（S104）；针对任一基带信号，构建基带信号对应的星座图，获取星座图对应的矩阵特征值，并根据矩阵特征值确定目标特征值差值（S106）；根据各基带信号对应的目标特征值差值，从各基带信号中确定目标基带信号（S108）。

Description

OFDM信号的解调方法、装置、计算机设备和存储介质
相关申请
本申请要求2023年07月07日提交的，申请号为2023108298126，名称为“OFDM信号的解调方法、装置、计算机设备和存储介质”的中国专利申请的优先权，在此将其全文引入作为参考。
技术领域
本申请涉及通信领域，特别是涉及一种OFDM信号的解调方法、装置、计算机设备和存储介质。
背景技术
OFDM(Orthogonal Frequency Division Multiplexing，正交频分复用)技术是一种通过多个正交的子载波传递信息的技术，接收端通过对接收到的信号进行逆傅里叶变换，再根据各个子载波之间的频率间隔对信号进行解调得到在各个子载波上传递的信息。而在非协作通信的场景下，由于载频偏差的干扰以及无法得知子载波之间的精确频率间隔，对OFDM信号进行解调较为困难。
发明内容
第一方面，本申请提供了一种OFDM信号的解调方法。所述方法包括：
确定目标信号各子载波的多个频率间隔预估值、及多个载频偏差预估值；
针对任一预估值对，基于所述预估值对对所述目标信号进行解调，得到所述目标信号对应的基带信号，所述预估值对由任一所述频率间隔预估值及任一所述载频偏差预估值组成；
针对任一所述基带信号，构建所述基带信号对应的星座图，获取所述星座图对应的矩阵特征值，并根据所述矩阵特征值确定目标特征值差值；
根据各所述基带信号对应的所述目标特征值差值，从各所述基带信号中确定目标基带信号。
在其中一个实施例中，所述基带信号由多个发送值组成，所述基于所述预估值对对所述目标信号进行解调，得到所述目标信号对应的基带信号，包括：
获取所述目标信号在多个时刻对应的接收值、及获取所述目标信号对应的子载波数量；
针对任一所述接收值，根据所述子载波数量及所述预估值对，确定所述接收值对应的发送值。
在其中一个实施例中，所述构建所述基带信号对应的星座图，获取所述星座图对应的矩阵特征值，包括：
根据所述目标信号对应的各所述发送值构建星座图，所述星座图中的星座点与所述发送值一一对应；
针对所述星座图中的任意两个所述星座点，根据两个所述星座点在所述星座图中的坐标，构建两个所述星座点之间的连接边权重；
根据各所述星座点之间的连接边权重，构建所述星座图对应的权重矩阵；
根据所述权重矩阵，构建所述星座图对应的拉普拉斯矩阵，并将所述拉普拉斯矩阵的特征值作为所述矩阵特征值。
在其中一个实施例中，所述根据两个所述星座点在所述星座图中的坐标，构建两个所述星座点之间的连接边权重，包括：
基于两个所述星座点在所述星座图中的坐标及噪声功率参数，通过高斯核函数构建两个所述星座点之间的连接边权重。
在其中一个实施例中，所述根据所述矩阵特征值确定目标特征值差值，包括：
对各所述矩阵特征值由大至小进行排序，获得特征值队列；
确定所述特征值队列中每两个相邻的所述矩阵特征值之间的差值，并将各所述差值中，最大的所述差值作为所述目标特征值差值。
在其中一个实施例中，所述根据各所述基带信号对应的所述目标特征值差值，从各所述基带信号中确定目标基带信号，包括：
将各所述目标特征值差值中，最大的所述目标特征值差值对应的所述基带信号，作为所述目标基带信号。
第二方面，本申请还提供了一种OFDM信号的解调装置。所述装置包括：
第一确定模块，用于确定目标信号各子载波的多个频率间隔预估值、及多个载频偏差预估值；
解调模块，用于针对任一预估值对，基于所述预估值对对所述目标信号进行解调，得到所述目标信号对应的基带信号，所述预估值对由任一所述第一预估值及任一所述第二预估值组成；
构建模块，用于针对任一所述基带信号，构建所述基带信号对应的星座图，获取所述星座图对应的矩阵特征值，并根据所述矩阵特征值确定目标特征值差值；
第二确定模块，用于根据各所述基带信号对应的所述目标特征值差值，从各所述基带信号中确定目标基带信号。
在其中一个实施例中，所述基带信号由多个发送值组成，所述解调模块，还用于：
获取所述目标信号在多个时刻对应的接收值、及获取所述目标信号对应的子载波数量；
针对任一所述接收值，根据所述子载波数量及所述预估值对，确定所述接收值对应的发送值。
在其中一个实施例中，所述构建模块，还用于：
根据所述目标信号对应的各所述发送值构建星座图，所述星座图中的星座点与所述发送值一一对应；
针对所述星座图中的任意两个所述星座点，根据两个所述星座点在所述星座图中的坐标，构建两个所述星座点之间的连接边权重；
根据各所述星座点之间的连接边权重，构建所述星座图对应的权重矩阵；
根据所述权重矩阵，构建所述星座图对应的拉普拉斯矩阵，并将所述拉普拉斯矩阵的特征值作为所述矩阵特征值。
在其中一个实施例中，所述构建模块，还用于：
基于两个所述星座点在所述星座图中的坐标及噪声功率参数，通过高斯核函数构建两个所述星座点之间的连接边权重。
在其中一个实施例中，所述构建模块，还用于：
对各所述矩阵特征值由大至小进行排序，获得特征值队列；
确定所述特征值队列中每两个相邻的所述矩阵特征值之间的差值，并将各所述差值中，最大的所述差值作为所述目标特征值差值。
在其中一个实施例中，所述第二确定模块，还用于：
将各所述目标特征值差值中，最大的所述目标特征值差值对应的所述基带信号，作为所述目标基带信号。
第三方面，本申请还提供了一种计算机设备。所述计算机设备包括存储器和处理器，所述存储器存储有计算机程序，所述计算机程序在由所述处理器执行时，致使所述处理器：
确定目标信号各子载波的多个频率间隔预估值、及多个载频偏差预估值；
针对任一预估值对，基于所述预估值对对所述目标信号进行解调，得到所述目标信号对应的基带信号，所述预估值对由任一所述频率间隔预估值及任一所述载频偏差预估值组成；
针对任一所述基带信号，构建所述基带信号对应的星座图，获取所述星座图对应的矩阵特征值，并根据所述矩阵特征值确定目标特征值差值；
根据各所述基带信号对应的所述目标特征值差值，从各所述基带信号中确定目标基带信号。
在其中一个实施例中，所述基带信号由多个发送值组成，所述基于所述预估值对对所述目标信号进行解调，得到所述目标信号对应的基带信号，包括：
获取所述目标信号在多个时刻对应的接收值、及获取所述目标信号对应的子载波数量；
针对任一所述接收值，根据所述子载波数量及所述预估值对，确定所述接收值对应的发送值。
在其中一个实施例中，所述构建所述基带信号对应的星座图，获取所述星座图对应的矩阵特征值，包括：
根据所述目标信号对应的各所述发送值构建星座图，所述星座图中的星座点与所述发送值一一对应；
针对所述星座图中的任意两个所述星座点，根据两个所述星座点在所述星座图中的坐标，构建两个所述星座点之间的连接边权重；
根据各所述星座点之间的连接边权重，构建所述星座图对应的权重矩阵；
根据所述权重矩阵，构建所述星座图对应的拉普拉斯矩阵，并将所述拉普拉斯矩阵的特征值作为所述矩阵特征值。
在其中一个实施例中，所述根据两个所述星座点在所述星座图中的坐标，构建两个所述星座点之间的连接边权重，包括：
基于两个所述星座点在所述星座图中的坐标及噪声功率参数，通过高斯核函数构建两个所述星座点之间的连接边权重。
在其中一个实施例中，所述根据所述矩阵特征值确定目标特征值差值，包括：
对各所述矩阵特征值由大至小进行排序，获得特征值队列；
确定所述特征值队列中每两个相邻的所述矩阵特征值之间的差值，并将各所述差值中，最大的所述差值作为所述目标特征值差值。
在其中一个实施例中，所述根据各所述基带信号对应的所述目标特征值差值，从各所述基带信号中确定目标基带信号，包括：
将各所述目标特征值差值中，最大的所述目标特征值差值对应的所述基带信号，作为所述目标基带信号。
第四方面，本申请还提供了一种计算机可读存储介质。所述计算机可读存储介质，其上存储有计算机程序，所述计算机程序在由处理器执行时，致使所述处理器：
确定目标信号各子载波的多个频率间隔预估值、及多个载频偏差预估值；
针对任一预估值对，基于所述预估值对对所述目标信号进行解调，得到所述目标信号对应的基带信号，所述预估值对由任一所述频率间隔预估值及任一所述载频偏差预估值组成；
针对任一所述基带信号，构建所述基带信号对应的星座图，获取所述星座图对应的矩阵特征值，并根据所述矩阵特征值确定目标特征值差值；
根据各所述基带信号对应的所述目标特征值差值，从各所述基带信号中确定目标基带信号。
在其中一个实施例中，所述基带信号由多个发送值组成，所述基于所述预估值对对所述目标信号进行解调，得到所述目标信号对应的基带信号，包括：
获取所述目标信号在多个时刻对应的接收值、及获取所述目标信号对应的子载波数量；
针对任一所述接收值，根据所述子载波数量及所述预估值对，确定所述接收值对应的发送值。
在其中一个实施例中，所述构建所述基带信号对应的星座图，获取所述星座图对应的 矩阵特征值，包括：
根据所述目标信号对应的各所述发送值构建星座图，所述星座图中的星座点与所述发送值一一对应；
针对所述星座图中的任意两个所述星座点，根据两个所述星座点在所述星座图中的坐标，构建两个所述星座点之间的连接边权重；
根据各所述星座点之间的连接边权重，构建所述星座图对应的权重矩阵；
根据所述权重矩阵，构建所述星座图对应的拉普拉斯矩阵，并将所述拉普拉斯矩阵的特征值作为所述矩阵特征值。
在其中一个实施例中，所述根据两个所述星座点在所述星座图中的坐标，构建两个所述星座点之间的连接边权重，包括：
基于两个所述星座点在所述星座图中的坐标及噪声功率参数，通过高斯核函数构建两个所述星座点之间的连接边权重。
在其中一个实施例中，所述根据所述矩阵特征值确定目标特征值差值，包括：
对各所述矩阵特征值由大至小进行排序，获得特征值队列；
确定所述特征值队列中每两个相邻的所述矩阵特征值之间的差值，并将各所述差值中，最大的所述差值作为所述目标特征值差值。
在其中一个实施例中，所述根据各所述基带信号对应的所述目标特征值差值，从各所述基带信号中确定目标基带信号，包括：
将各所述目标特征值差值中，最大的所述目标特征值差值对应的所述基带信号，作为所述目标基带信号。
第五方面，本申请还提供了一种计算机程序产品。所述计算机程序产品，包括计算机程序，该计算机程序在由处理器执行时，致使所述处理器：
确定目标信号各子载波的多个频率间隔预估值、及多个载频偏差预估值；
针对任一预估值对，基于所述预估值对对所述目标信号进行解调，得到所述目标信号对应的基带信号，所述预估值对由任一所述频率间隔预估值及任一所述载频偏差预估值组成；
针对任一所述基带信号，构建所述基带信号对应的星座图，获取所述星座图对应的矩阵特征值，并根据所述矩阵特征值确定目标特征值差值；
根据各所述基带信号对应的所述目标特征值差值，从各所述基带信号中确定目标基带信号。
在其中一个实施例中，所述基带信号由多个发送值组成，所述基于所述预估值对对所述目标信号进行解调，得到所述目标信号对应的基带信号，包括：
获取所述目标信号在多个时刻对应的接收值、及获取所述目标信号对应的子载波数量；
针对任一所述接收值，根据所述子载波数量及所述预估值对，确定所述接收值对应的发送值。
在其中一个实施例中，所述构建所述基带信号对应的星座图，获取所述星座图对应的矩阵特征值，包括：
根据所述目标信号对应的各所述发送值构建星座图，所述星座图中的星座点与所述发送值一一对应；
针对所述星座图中的任意两个所述星座点，根据两个所述星座点在所述星座图中的坐标，构建两个所述星座点之间的连接边权重；
根据各所述星座点之间的连接边权重，构建所述星座图对应的权重矩阵；
根据所述权重矩阵，构建所述星座图对应的拉普拉斯矩阵，并将所述拉普拉斯矩阵的特征值作为所述矩阵特征值。
在其中一个实施例中，所述根据两个所述星座点在所述星座图中的坐标，构建两个所述星座点之间的连接边权重，包括：
基于两个所述星座点在所述星座图中的坐标及噪声功率参数，通过高斯核函数构建两个所述星座点之间的连接边权重。
在其中一个实施例中，所述根据所述矩阵特征值确定目标特征值差值，包括：
对各所述矩阵特征值由大至小进行排序，获得特征值队列；
确定所述特征值队列中每两个相邻的所述矩阵特征值之间的差值，并将各所述差值中，最大的所述差值作为所述目标特征值差值。
在其中一个实施例中，所述根据各所述基带信号对应的所述目标特征值差值，从各所述基带信号中确定目标基带信号，包括：
将各所述目标特征值差值中，最大的所述目标特征值差值对应的所述基带信号，作为所述目标基带信号。
本申请的一个或多个实施例的细节在下面的附图和描述中提出。本申请的其它特征、目的和优点将从说明书、附图以及权利要求书变得明显。
附图说明
为了更清楚地说明本申请实施例的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，下面描述中的附图仅仅是本申请的一些实施例，不构成对本申请披露内容和保护范围的限制。
图1为一个实施例中OFDM信号的解调方法的流程示意图；
图2为一个实施例中星座图的示意图；
图3为一个实施例中步骤104的流程示意图；
图4为一个实施例中步骤106的流程示意图；
图5为一个实施例中步骤106的流程示意图；
图6为一个实施例中相邻两个特征值的差值的示意图；
图7为一个实施例中OFDM信号的解调方法的流程示意图；
图8为一个实施例中仿真实验的示意图；
图9为一个实施例中OFDM信号的解调装置的结构框图；
图10为一个实施例中计算机设备的内部结构图。
具体实施方式
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
传统技术中，可以通过盲分离的方法或者通过循环前缀来估计载频偏差和频率间隔，进而根据估计出的载频偏差和频率间隔对接收到的信号进行解调。但是基于盲分离的方法由于相位差不稳定，相位差的平均值难以收敛，只能对载频偏差进行粗估计；而基于循环前缀估计的方法均假设信号遵循IEEE802.16e协议，但非合作模式下信号不一定遵循IEEE相关协议或者接收到的循环前缀不完整，造成估计不准确，导致解调得到的信号精度较低。
在一个实施例中，如图1所示，提供了一种OFDM信号的解调方法，本实施例以该方法应用于终端进行举例说明，可以理解的是，该方法也可以应用于服务器，还可以应用于包括终端和服务器的系统，并通过终端和服务器的交互实现。本实施例中，该方法包括以下步骤：
步骤102，确定目标信号各子载波的多个频率间隔预估值、及多个载频偏差预估值。
本申请实施例中，目标信号是终端(终端可以为OFDM信号的接收机)接收到的信号。OFDM信号由多个子载波叠加形成，各个子载波之间的频率差即频率间隔，而OFDM信号在传输过程中，因干扰等因素而造成的目标信号的载波频率与发送机发送出的载波频率之间的差即载频偏差。
由于在对OFDM信号解调时需要通过确定精确的载频偏差来消除载频偏差对信号质量的影响，同时也必须知道子载波之间的频率间隔，故而可以通过估计出多个频率间隔对应的频率间隔估计值，以及多个载频偏差对应的载频偏差估计值，再确定哪一个频率间隔估计值及哪一个载频偏差估计值最接近真实值来得到最精确的频率间隔及载频偏差。本申请实施例对于估计得到频率间隔预估值和载频偏差预估值的方式不作具体限定，任一现有的估计得到频率间隔预估值和载频偏差预估值的方式均适用于本申请实施例中，例如盲分离法、基于循环前缀的估计方法等。
需要说明的是，在估计得出的频率间隔或载频偏差是一个区间时，可以从区间中取多个数值作为频率间隔预估值或载频偏差预估值(以下统称为预估值)。例如可以从区间中等间隔取多个数值作为预估值，或者从区间的中心开始、向外逐渐以递增的间隔取数值作为预估值等，本申请实施例对此不作具体限定。
步骤104，针对任一预估值对，基于预估值对对目标信号进行解调，得到目标信号对应的基带信号，预估值对由任一频率间隔预估值及任一载频偏差预估值组成。
本申请实施例中，可以将任一频率间隔预估值及任一载频偏差预估值组成一个预估值对。需要说明的是，不同的预估值对中的频率间隔预估值或载频偏差预估值可以重复，只要各预估值对不同即可：例如频率间隔预估值A和载频偏差预估值A可以组成一个预估值对，频率间隔预估值A和载频偏差预估值B也可以组成一个预估值对。
针对每一个预估值对，都可以根据预估值对中的频率间隔预估值和载频偏差预估值对对目标信号进行一次解调，获得本预估值对对应的基带信号。基于基带信号对应的星座图验证基带信号的精确度后，即可从各基带信号中获得精确度最高的目标基带信号。
步骤106，针对任一基带信号，构建基带信号对应的星座图，获取星座图对应的矩阵特征值，并根据矩阵特征值确定目标特征值差值。
本申请实施例中，接收机在接收目标信号时会对目标信号使用较高的采样频率进行过采样，通过一次采样得到的接收值可以得到基带信号中的一个二进制信号，进而可以将该二进制信号映射至复平面中(I路和Q路分别映射到横轴和纵轴)得到一个星座点，将全部接收值对应的二进制信号映射完毕后可以得到基带信号对应的星座图。
星座图可以以矩阵来表示。为了使得矩阵可以反映星座点之间的距离远近，可以使得矩阵中的每一个元素都代表该元素所在列对应的星座点、以及该元素所在行对应的星座点之间的距离权重，例如位于矩阵第i行第j列的元素即代表第i个星座点和第j个星座点之间的距离权重；同时为了使得距离更近的星座点的距离权重更大，便于后续计算，可以使得距离权重与星座点之间的实际距离成反比。距离权重可以根据两个星座点在星座图中的坐标来计算，例如可以直接取两个星座点之间的直线距离的倒数作为距离权重，或者也可以同时考虑噪声参数，通过噪声参数和星座点之间的直线距离的倒数构建得到距离权重等，本申请实施例对此不作具体限定。
矩阵特征值即星座图的矩阵对应的特征值。目标特征值差值(eigengap，也称为本征间隙)的定义是将矩阵的特征值从大到小排列后，相邻的两个特征值之间的差中最大的数值。在矩阵是图的表示的情况下，目标特征值差值可以反映图中各个节点形成的聚类的稳定程度。因此计算星座图的矩阵的目标特征值差值，就可以得到一个可以表征星座图中各星座点聚集程度的值，进而可以通过该值确定哪一个星座图中各星座点的聚集程度最优、也即哪一个星座图是最优的星座图。
步骤108，根据各基带信号对应的目标特征值差值，从各基带信号中确定目标基带信号。
本申请实施例中，参见图2所示，在存在载频偏差的情况下，各星座点的相位会发生变化，也即相当于各点会围绕星座图的中心进行旋转；而消除载频偏差就相当于消除各点的旋转，将各点移动至其应当处于的位置上。
而由于在目标信号对应的调制方式一定的情况下，对目标信号进行采样得到的接收值 的类型是有限的，故而根据目标信号只能解调出有限类型的二进制信号组合，因此在消除载频偏差后，多个二进制信号在星座图中将呈现出图2右图中所示的聚集情况。由于目标特征值差值可以反映星座图中星座点的聚集程度，而星座点越聚集，则表明各二进制信号的真实值被恢复的越好、载频偏差和频率间隔越接近真实值，故而可以根据目标特征值差值从各基带信号中确定出最接近真实值的目标基带信号。
可以直接将最大的目标特征值差值(代表星座图中各星座点的聚集情况最佳)作为目标基带信号。或者，在频率间隔预估值和载频偏差预估值是一个区间的情况下，为了提升解调的精度，可以进一步获取最大的目标特征值差值对应的预估值对，从预估值对的频率间隔预估值及载频偏差预估值附近重新获取多个频率间隔预估值和多个载频偏差预估值构建新的预估值对(例如，以频率间隔预估值为例，可以预设一个较小的距离间隔，并以频率间隔预估值为中心，每隔距离间隔取一个新的频率间隔预估值，直至新的频率间隔预估值的数量满足要求为止。针对载频偏差预估值也可以进行类似操作)，再针对新的各预估值对重复上述流程，获取各新的预估值对对应的基带信号和基带信号对应的目标特征值差值，再将新得到的各目标特征值差值与原先最大的目标特征值差值进行比较，重新选取其中最大的目标特征值差值；可以多次重复上述过程，每一次都缩小预设的距离间隔，直至循环次数达到阈值，或者上一轮中最大的目标特征值差值仍是本轮中最大的目标特征值差值为止。
本申请实施例提供的OFDM信号的解调方法，得到多个估计的载频偏差和频率间隔，并根据每个可能的载频偏差和频率间隔的组合反推基带信号，获得基带信号对应的星座图，计算星座图矩阵表达的目标特征值差值，进而根据目标特征值差值选取目标基带信号。由于目标特征值差值可以反映星座图中各星座点簇的聚集程度，星座点簇的聚集程度又与预估值的精确度相关，故而根据特征值差值选取目标基带信号，可以选出星座点簇最符合要求、也即最接近真实值的目标基带信号，因此可以提高在载频偏差和频率间隔未知的情况下，对OFDM信号进行解调的精度。
在一个实施例中，如图3所示，基带信号由多个发送值组成，步骤104中，基于预估值对对目标信号进行解调，得到目标信号对应的基带信号，包括以下步骤。
步骤302，获取目标信号在多个时刻对应的接收值、及目标信号对应的子载波数量。
步骤304，针对任一接收值，根据子载波数量及预估值对，确定接收值对应的发送值。
本申请实施例中，发送值也即前述实施例中的二进制信号，多个二进制信号组合形成发送机需要发送的信息，也即基带信号。接收机在接收目标信号时将对目标信号进行多次采样，一次采样可以得到一个接收值。接收值实质上是多个正交的子载波叠加得到的结果，通过预估值对中的载频偏差预估值消除接收值的载频偏差，并根据频率间隔预估值对各子载波进行分解，可以得到接收值对应的发送值。
示例性的，由于接收值可以通过发送值在每个子载波上的值叠加得到，而每个子载波上的值又可以根据接收机的采样周期、接收机接收目标信号使用的信道的信道冲激响应、噪声参数(可由本领域技术人员根据经验确定)及载频偏差预估值和频率间隔预估值计算得到(参见公式(一))，故而可以根据接收值反推发送值：
其中，rk指在一个采样周期内采集到的第k个接收值，hk是信道的信道冲激响应，M是子载波数量(根据目标信号的总带宽与频率间隔预估值的比值得到)，sk是rk对应的发送值，ej2π是虚数的一种表示方式，f0是载频偏差预估值，f是频率间隔预估值，Ts是采样周期，nk是噪声参数。
根据公式(一)可以反推出sk的值也即发送值。针对所有采集到的接收值均反推出发送值，即可得到本采样周期内采集到的目标信号对应的基带信号。
本申请实施例提供的OFDM信号的解调方法，根据目标信号对应的子载波数量及预估值对，确定目标信号每一个接收值对应的发送值，以此得到目标信号对应的基带信号。进而可以根据各发送值构建基带信号对应的星座图并获得基带信号对应的目标特征值差值，并根据目标特征值差值选出目标基带信号，可以提高在载频偏差和频率间隔未知的情况下，对OFDM信号进行解调的精度。
在一个实施例中，如图4所示，步骤106中，构建基带信号对应的星座图，获取星座图对应的矩阵特征值，包括以下步骤。
步骤402，根据目标信号对应的各发送值构建星座图，星座图中的星座点与发送值一一对应。
步骤404，针对星座图中的任意两个星座点，根据两个星座点在星座图中的坐标，构建两个星座点之间的连接边权重。
步骤406，根据各星座点之间的连接边权重，构建星座图对应的权重矩阵。
步骤408，根据权重矩阵，构建星座图对应的拉普拉斯矩阵，并将拉普拉斯矩阵的特征值作为矩阵特征值。
本申请实施例中，将目标信号的发送值均投影到复平面中可以得到星座点，各星座点组成星座图。可以用拉普拉斯矩阵来表征星座图。拉普拉斯矩阵可以根据星座图的权重矩阵计算得到。
针对任意两个星座点，可以根据星座点在星座图中的坐标来构建星座点之间的连接边权重(在星座点相同时可以将连接边权重设置为0，也即权重矩阵的对角线元素均为0)。例如取坐标之间的直线距离的倒数获得连接边权重，或者通过其他基于两点之间距离构建距离权重的方式获得距离权重等。将权重矩阵第i行第j列的元素设置为第i个星座点和第j个星座点之间的连接边权重，可以得到权重矩阵，进而可以根据下述公式(二)计算星座图的拉普拉斯矩阵：
其中，L代表拉普拉斯矩阵，D是一个对角矩阵，其第i行第i列的元素等于权重矩阵第i行所有元素之和，W代表权重矩阵。
计算拉普拉斯矩阵的各特征值，可以得到星座图对应的各矩阵特征值。
本申请实施例提供的OFDM信号的解调方法，构建星座图对应的拉普拉斯矩阵，并基于拉普拉斯矩阵获得矩阵特征值。由于拉普拉斯矩阵可以准确表达星座图中各星座点之间的距离及连接情况，故而采用拉普拉斯矩阵作为星座图对应的矩阵可以提高目标特征值差值对于星座图中各星座点聚集程度的反映情况，进而提高确定目标基带信号的确定精度。
在一个实施例中，步骤404中，根据两个星座点在星座图中的坐标，构建两个星座点之间的连接边权重，包括以下步骤。
基于两个星座点在星座图中的坐标及噪声功率参数，通过高斯核函数构建两个星座点之间的连接边权重。
本申请实施例中，可以采用高斯核函数构建连接边权重。高斯核函数是关于两点之间的欧式距离的单调递减函数，也即两点之间距离越大、通过高斯核函数计算出的连接边权重就越小；同时还可以通过控制高斯核函数中的参数σ来控制两点之间欧式距离与连接边权重之间的关系，在σ较小时，两点之间欧式距离的变化对连接边权重的变化影响较小，也即可以达到使得距离较远的星座点也能被归为一类、使得星座点聚类并不紧密的星座图也可以拥有较大的目标特征值差值、降低对预估值对的精度要求，提升获取目标基带信号速度的效果；在σ较大时，两点之间欧式距离的变化对连接边权重的变化影响较大，也即可以达到使得距离较近的星座点才能被归为一类、提高对预估值对的精度要求，提升目标基带信号的精度的效果。
可以将σ设置为与噪声功率参数正相关，σ与噪声功率参数的具体关系可以由本领域 技术人员根据经验设定。此处需要选取合适的σ取值，因为在σ取值过小时，会导致各点之间的连接边权重都较为近似、难以区分互相之间距离不同的点；而在σ取值过大时，会导致连接边权重对星座图中的噪声敏感，令噪声对连接边权重的取值造成明显的干扰。示例性的，可以采用Scott规则或Silverman规则计算σ。通过Scott规则计算σ的方式可参见下述公式(三)：
其中，是对σ的估计量，K为一个采样周期内采集到的接收值总数。
通过Silverman规则计算σ的方式可参见下述公式(四)：
其中，是对σ的估计量，K为一个采样周期内采集到的接收值总数，IQR指信号的四分位距(interquartile range)。
示例性的，基于高斯核函数、噪声功率参数和星座点的坐标的欧式距离得到的连接边权重可以如公式(三)所示：
其中，为星座点和之间的连接边权重，是星座点和之间的欧式距离，根据和的坐标计算。
本申请实施例提供的OFDM信号的解调方法，通过高斯核函数构建连接边权重，并根据噪声功率参数设置高斯核函数中的参数σ，可以在噪声功率参数取值不同时，相应自适应调整对目标基带信号的精确度要求，确保目标基带信号的确定速度不会过慢。
在一个实施例中，如图5所示，步骤106中，根据矩阵特征值确定目标特征值差值，包括以下步骤。
步骤502，对各矩阵特征值由大至小进行排序，获得特征值队列。
步骤504，确定特征值队列中每两个相邻的矩阵特征值之间的差值，并将各差值中，最大的差值作为目标特征值差值。
本申请实施例中，目标特征值差值可以通过对矩阵特征值进行排序得到特征值队列，再根据特征值队列相邻的两个矩阵特征值之间的差值中最大的差值得到。参照图6所示，为将拉普拉斯矩阵的各特征值从大到小进行排序后的结果。可见图中框选的区域中特征值之间的差值最大，因此该差值即为目标特征值差值。
本申请实施例提供的OFDM信号的解调方法，通过将特征值由大至小进行排列，并计算两个相邻特征值的差值的最大值得到目标特征值差值。由于目标特征值差值可以反映星座图中各星座点簇的聚集程度，星座点簇的聚集程度又与预估值的精确度相关，故而根据特征值差值选取目标基带信号，可以选出星座点簇最符合要求、也即最接近真实值的目标基带信号，因此可以提高在载频偏差和频率间隔未知的情况下，对OFDM信号进行解调的精度。
在一个实施例中，步骤108中，根据各基带信号对应的目标特征值差值，从各基带信号中确定目标基带信号，包括：
将各目标特征值差值中，最大的目标特征值差值对应的基带信号，作为目标基带信号。
本申请实施例中，由于在目标特征值差值最大时，代表星座图中各星座点的聚类最紧密，各星座点的旋转均被消除，星座点最贴近真实值；因此各基带信号中，对应的目标特征值差值最大的基带信号就是最贴近真实值的基带信号。故而可以将对应的目标特征值差 值最大的基带信号作为目标基带信号，以此得到对接收到的OFDM信号进行解调后的结果。
本申请实施例提供的OFDM信号的解调方法，将最大的目标特征值差值对应的基带信号作为目标基带信号。由于最大的目标特征值差值对应的基带信号最接近真实值，因此可以提高目标基带信号的确定精度。
为使本领域技术人员更好的理解本申请实施例，以下通过具体示例对本申请实施例加以说明。
参照图7所示，示出了一种OFDM信号的解调方法的流程图。
本申请实施例中，可以针对所有可能的频率间隔和载频偏差进行遍历。例如可以确定频率间隔及载频偏差可能位于的区间或可能对应的值，从中选取出需要遍历的频率间隔预估值和载频偏差预估值，并对选出的全部频率间隔预估值和载频偏差预估值进行遍历：例如可以首先选取出一个固定的频率间隔预估值，进而选取出载频偏差预估值与该固定的频率间隔预估值进行组合，计算出基于该组合解调出的基带信号的星座图、星座图的拉普拉斯矩阵及拉普拉斯矩阵对应的eigengap。在将所有载频偏差预估值均与该固定的频率间隔预估值进行组合后，重新选取频率间隔预估值，重复上述过程，直至频率间隔预估值被遍历完毕为止。将所有组合对应的eigengap进行比较，将其中最大的eigengap对应的频率间隔预估值和载频偏差预估值作为实际的估计值，并将最大的eigengap对应的基带信号作为最终解调得到的基带信号，可以获得目标信号对应的子载波频率间隔、载频偏差及解调结果。其中，得到基带信号的方式、拉普拉斯矩阵的构建方式和eigengap的计算方式可参见前述实施例的描述，本申请实施例在此不再赘述。
以下以仿真实验说明本申请实施例的效果。参见图8所示，设置发送机发送的OFDM信号共有4个子载波，每个子载波均通过4QAM(一种正交振幅调制方法)方式进行调制，相邻子载波的频率间隔为1MHz。设置接收机的采样周期为1μs，每个采样周期内采样1024次，载频偏差为0.055MHz，信道为AWGN信道，信道冲激响应为30dB，高斯核函数中的σ2为噪声功率参数的64倍。遍历各频率间隔预估值和载频偏差预估值，计算各种组合的eigengap，可得到如图8上方的结果。
从中选取eigengap最大的组合。可见eigengap最大时对应的载频偏差预估值为0.055MHz，恰好等于仿真中针对接收机设置的载频偏差。载频偏差恢复前的星座图、载频偏差预估值为0.055MHz时相邻两个特征值之间的差值、以及载频偏差恢复后的星座图可参见图8下方所示。
上述方法可以应用于对非授权使用频谱进行感知的场景中。采用上述方法针对在非授权使用频谱中传输的无线信号进行分析，可以获得非授权使用频谱的频率间隔和载频偏差等信息，进而能够对运营商专网覆盖范围内非授权使用频谱的行为进行感知，可以帮助运营商给专网客户和行业用户的无线网络提供主动感知安全能力的服务，避免用户在无线网络内的通信受到窃听、篡改、干扰等安全威胁。
本申请实施例提供的OFDM信号的解调方法，可以对OFDM系统的频率间隔和载频偏差进行精确估计，理论上只要取足够多的频率间隔估计值和载频偏差估计值，便可以使频率间隔估计值和载频偏差估计值无限逼近频率间隔和载频偏差的真实值，提高频率间隔和载频偏差的估计精度，进而提高在非协作通信模式下对OFDM信号进行解调的精度。
应该理解的是，虽然如上所述的各实施例所涉及的流程图中的各个步骤按照箭头的指示依次显示，但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，如上所述的各实施例所涉及的流程图中的至少一部分步骤可以包括多个步骤或者多个阶段，这些步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些步骤或者阶段的执行顺序也不必然是依次进行，而是可以与其它步骤或者其它步骤中的步骤或者阶段的至少一部分轮流或者交替地执行。
基于同样的发明构思，本申请实施例还提供了一种用于实现上述所涉及的OFDM信号 的解调方法的OFDM信号的解调装置。该装置所提供的解决问题的实现方案与上述方法中所记载的实现方案相似，故下面所提供的一个或多个OFDM信号的解调装置实施例中的具体限定可以参见上文中对于OFDM信号的解调方法的限定，在此不再赘述。
在一个实施例中，如图9所示，提供了一种OFDM信号的解调装置900，包括：第一确定模块902、解调模块904、构建模块906、第二确定模块908，其中：
第一确定模块902，用于确定目标信号各子载波的多个频率间隔预估值、及多个载频偏差预估值；
解调模块904，用于针对任一预估值对，基于所述预估值对对所述目标信号进行解调，得到所述目标信号对应的基带信号，所述预估值对由任一所述第一预估值及任一所述第二预估值组成；
构建模块906，用于针对任一所述基带信号，构建所述基带信号对应的星座图，获取所述星座图对应的矩阵特征值，并根据所述矩阵特征值确定目标特征值差值；
第二确定模块908，用于根据各所述基带信号对应的所述目标特征值差值，从各所述基带信号中确定目标基带信号。
本申请实施例提供的OFDM信号的解调装置，得到多个估计的载频偏差和频率间隔，并根据每个可能的载频偏差和频率间隔的组合反推基带信号，获得基带信号对应的星座图，计算星座图矩阵表达的目标特征值差值，进而根据目标特征值差值选取目标基带信号。由于目标特征值差值可以反映星座图中各星座点簇的聚集程度，星座点簇的聚集程度又与预估值的精确度相关，故而根据特征值差值选取目标基带信号，可以选出星座点簇最符合要求、也即最接近真实值的目标基带信号，因此可以提高在载频偏差和频率间隔未知的情况下，对OFDM信号进行解调的精度。
在其中一个实施例中，所述基带信号由多个发送值组成，所述解调模块904，还用于：
获取所述目标信号在多个时刻对应的接收值、及获取所述目标信号对应的子载波数量；
针对任一所述接收值，根据所述子载波数量及所述预估值对，确定所述接收值对应的发送值。
在其中一个实施例中，所述构建模块906，还用于：
根据所述目标信号对应的各所述发送值构建星座图，所述星座图中的星座点与所述发送值一一对应；
针对所述星座图中的任意两个所述星座点，根据两个所述星座点在所述星座图中的坐标，构建两个所述星座点之间的连接边权重；
根据各所述星座点之间的连接边权重，构建所述星座图对应的权重矩阵；
根据所述权重矩阵，构建所述星座图对应的拉普拉斯矩阵，并将所述拉普拉斯矩阵的特征值作为所述矩阵特征值。
在其中一个实施例中，所述构建模块906，还用于：
基于两个所述星座点在所述星座图中的坐标及噪声功率参数，通过高斯核函数构建两个所述星座点之间的连接边权重。
在其中一个实施例中，所述构建模块906，还用于：
对各所述矩阵特征值由大至小进行排序，获得特征值队列；
确定所述特征值队列中每两个相邻的所述矩阵特征值之间的差值，并将各所述差值中，最大的所述差值作为所述目标特征值差值。
在其中一个实施例中，所述第二确定模块908，还用于：
将各所述目标特征值差值中，最大的所述目标特征值差值对应的所述基带信号，作为所述目标基带信号。
上述OFDM信号的解调装置中的各个模块可全部或部分通过软件、硬件及其组合来实现。上述各模块可以硬件形式内嵌于或独立于计算机设备中的处理器中，也可以以软件形式存储于计算机设备中的存储器中，以便于处理器调用执行以上各个模块对应的操作。
在一个实施例中，提供了一种计算机设备，该计算机设备可以是服务器，其内部结构图可以如图10所示。该计算机设备包括通过系统总线连接的处理器、存储器和网络接口。其中，该计算机设备的处理器用于提供计算和控制能力。该计算机设备的存储器包括非易失性存储介质和内存储器。该非易失性存储介质存储有操作系统和计算机程序。该内存储器为非易失性存储介质中的操作系统和计算机程序的运行提供环境。该计算机设备的网络接口用于与外部的终端通过网络连接通信。该计算机程序被处理器执行时以实现一种OFDM信号的解调方法。
本领域技术人员可以理解，图10中示出的结构，仅仅是与本申请方案相关的部分结构的框图，并不构成对本申请方案所应用于其上的计算机设备的限定，具体的计算机设备可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
在一个实施例中，提供了一种计算机设备，包括存储器和处理器，存储器中存储有计算机程序，该处理器执行计算机程序时实现上述各方法实施例中的步骤。
在一个实施例中，提供了一种计算机可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现上述各方法实施例中的步骤。
在一个实施例中，提供了一种计算机程序产品，包括计算机程序，该计算机程序被处理器执行时实现上述各方法实施例中的步骤。
需要说明的是，本申请所涉及的用户信息(包括但不限于用户设备信息、用户个人信息等)和数据(包括但不限于用于分析的数据、存储的数据、展示的数据等)，均为经用户授权或者经过各方充分授权的信息和数据。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机程序来指令相关的硬件来完成，所述的计算机程序可存储于一非易失性计算机可读取存储介质中，该计算机程序在执行时，可包括如上述各方法的实施例的流程。其中，本申请所提供的各实施例中所使用的对存储器、数据库或其它介质的任何引用，均可包括非易失性和易失性存储器中的至少一种。非易失性存储器可包括只读存储器(Read-Only Memory，ROM)、磁带、软盘、闪存、光存储器、高密度嵌入式非易失性存储器、阻变存储器(ReRAM)、磁变存储器(Magnetoresistive Random Access Memory，MRAM)、铁电存储器(Ferroelectric Random Access Memory，FRAM)、相变存储器(Phase Change Memory，PCM)、石墨烯存储器等。易失性存储器可包括随机存取存储器(Random Access Memory，RAM)或外部高速缓冲存储器等。作为说明而非局限，RAM可以是多种形式，比如静态随机存取存储器(Static Random Access Memory，SRAM)或动态随机存取存储器(Dynamic Random Access Memory，DRAM)等。本申请所提供的各实施例中所涉及的数据库可包括关系型数据库和非关系型数据库中至少一种。非关系型数据库可包括基于区块链的分布式数据库等，不限于此。本申请所提供的各实施例中所涉及的处理器可为通用处理器、中央处理器、图形处理器、数字信号处理器、可编程逻辑器、基于量子计算的数据处理逻辑器等，不限于此。
以上所述实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对申请专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。

Claims (15)

  1. 一种OFDM信号的解调方法，所述方法包括：
    确定目标信号各子载波的多个频率间隔预估值、及多个载频偏差预估值；
    针对任一预估值对，基于所述预估值对对所述目标信号进行解调，得到所述目标信号对应的基带信号，所述预估值对由任一所述频率间隔预估值及任一所述载频偏差预估值组成；
    针对任一所述基带信号，构建所述基带信号对应的星座图，获取所述星座图对应的矩阵特征值，并根据所述矩阵特征值确定目标特征值差值；
    根据各所述基带信号对应的所述目标特征值差值，从各所述基带信号中确定目标基带信号。
  2. 根据权利要求1所述的方法，其中，所述基带信号由多个发送值组成，所述基于所述预估值对对所述目标信号进行解调，得到所述目标信号对应的基带信号，包括：
    获取所述目标信号在多个时刻对应的接收值、及获取所述目标信号对应的子载波数量；
    针对任一所述接收值，根据所述子载波数量及所述预估值对，确定所述接收值对应的发送值。
  3. 根据权利要求2所述的方法，其中，所述构建所述基带信号对应的星座图，获取所述星座图对应的矩阵特征值，包括：
    根据所述目标信号对应的各所述发送值构建星座图，所述星座图中的星座点与所述发送值一一对应；
    针对所述星座图中的任意两个所述星座点，根据两个所述星座点在所述星座图中的坐标，构建两个所述星座点之间的连接边权重；
    根据各所述星座点之间的连接边权重，构建所述星座图对应的权重矩阵；
    根据所述权重矩阵，构建所述星座图对应的拉普拉斯矩阵，并将所述拉普拉斯矩阵的特征值作为所述矩阵特征值。
  4. 根据权利要求3所述的方法，其中，所述根据两个所述星座点在所述星座图中的坐标，构建两个所述星座点之间的连接边权重，包括：
    基于两个所述星座点在所述星座图中的坐标及噪声功率参数，通过高斯核函数构建两个所述星座点之间的连接边权重。
  5. 根据权利要求1所述的方法，其中，所述根据所述矩阵特征值确定目标特征值差值，包括：
    对各所述矩阵特征值由大至小进行排序，获得特征值队列；
    确定所述特征值队列中每两个相邻的所述矩阵特征值之间的差值，并将各所述差值中，最大的所述差值作为所述目标特征值差值。
  6. 根据权利要求1所述的方法，其中，所述根据各所述基带信号对应的所述目标特征值差值，从各所述基带信号中确定目标基带信号，包括：
    将各所述目标特征值差值中，最大的所述目标特征值差值对应的所述基带信号，作为所述目标基带信号。
  7. 一种OFDM信号的解调装置，所述装置包括：
    第一确定模块，用于确定目标信号各子载波的多个频率间隔预估值、及多个载频偏差预估值；
    解调模块，用于针对任一预估值对，基于所述预估值对对所述目标信号进行解调，得到所述目标信号对应的基带信号，所述预估值对由任一所述第一预估值及任一所述第二预估值组成；
    构建模块，用于针对任一所述基带信号，构建所述基带信号对应的星座图，获取所述星座图对应的矩阵特征值，并根据所述矩阵特征值确定目标特征值差值；
    第二确定模块，用于根据各所述基带信号对应的所述目标特征值差值，从各所述基带信号中确定目标基带信号。
  8. 根据权利要求7所述的装置，其中所述基带信号由多个发送值组成，所述解调模块还用于：
    获取所述目标信号在多个时刻对应的接收值、及获取所述目标信号对应的子载波数量；
    针对任一所述接收值，根据所述子载波数量及所述预估值对，确定所述接收值对应的发送值。
  9. 根据权利要求8所述的装置，其中所述构建模块还用于：
    根据所述目标信号对应的各所述发送值构建星座图，所述星座图中的星座点与所述发送值一一对应；
    针对所述星座图中的任意两个所述星座点，根据两个所述星座点在所述星座图中的坐标，构建两个所述星座点之间的连接边权重；
    根据各所述星座点之间的连接边权重，构建所述星座图对应的权重矩阵；
    根据所述权重矩阵，构建所述星座图对应的拉普拉斯矩阵，并将所述拉普拉斯矩阵的特征值作为所述矩阵特征值。
  10. 根据权利要求9所述的装置，其中所述构建模块还用于：
    基于两个所述星座点在所述星座图中的坐标及噪声功率参数，通过高斯核函数构建两个所述星座点之间的连接边权重。
  11. 根据权利要求7所述的装置，其中所述构建模块还用于：
    对各所述矩阵特征值由大至小进行排序，获得特征值队列；
    确定所述特征值队列中每两个相邻的所述矩阵特征值之间的差值，并将各所述差值中，最大的所述差值作为所述目标特征值差值。
  12. 根据权利要求7所述的装置，其中所述第二确定模块还用于：
    将各所述目标特征值差值中，最大的所述目标特征值差值对应的所述基带信号，作为所述目标基带信号。
  13. 一种计算机设备，包括存储器和处理器，所述存储器存储有计算机程序，其中，所述处理器执行所述计算机程序时实现权利要求1至6中任一项所述的方法的步骤。
  14. 一种计算机可读存储介质，其上存储有计算机程序，其中，所述计算机程序被处理器执行时实现权利要求1至6中任一项所述的方法的步骤。
  15. 一种计算机程序产品，包括计算机程序，其中，该计算机程序被处理器执行时实现权利要求1至6中任一项所述的方法的步骤。
PCT/CN2023/142030 2023-07-07 2023-12-26 Ofdm信号的解调方法、装置、计算机设备和存储介质 Ceased WO2025010964A1 (zh)

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