Method and device for determining signal quality

Abstract

The invention provides a method and device for determining signal quality, and the method comprises the steps: serially inputting a constellation diagram of a target signal into each stage of node of a digital front-end link, and obtaining a first baseband signal outputted by each stage of node; sampling first baseband signals output by at least one level of node in sequence to obtain a first target sampling point in each first baseband signal; determining a first error vector amplitude of each first baseband signal according to a first target sampling point in each first baseband signal; performing phase rotation on each first baseband signal to obtain each second baseband signal, and determining a second error vector amplitude of each second baseband signal; and determining the quality of the target signal according to each first error vector amplitude and each second error vector amplitude, thereby integrating the first error vector amplitude of the at least one first baseband signal and the second error vector amplitude of the at least one second baseband signal to determine the quality of the target signal, and improving the accuracy of determining the quality of the target signal.

Description

Technical Field

[0001] The present disclosure relates to the field of wireless communication technology, and in particular to a method and device for determining signal quality. Background Art

[0002] In wireless communications, the quality of the signal directly affects the performance of the communication system. By determining the signal quality of wireless communications, we can understand the quality of the signal and take corresponding measures to improve the signal quality when the signal quality is poor, thereby effectively improving the transmission quality and stability of the communication system, and thus improving the communication quality.

[0003] Currently, the quality of a wireless signal may be determined in the following manner: performing matched filtering on the wireless signal, and then determining the quality of the wireless signal based on the signal obtained by the matched filtering. However, the above manner may result in low accuracy in determining the quality of the wireless signal. Summary of the invention

[0004] The present disclosure aims to solve one of the technical problems in the related art at least to some extent.

[0005] To this end, the present disclosure proposes a method and device for determining signal quality, by determining a first error vector amplitude of each first baseband signal by sampling a first target sampling point in each first baseband signal output by at least one primary node of a digital front-end link, and determining a second error vector amplitude of a second baseband signal obtained by phase rotation of each first baseband signal, thereby determining the quality of the target signal according to each first error vector amplitude and each second error vector amplitude, achieving the determination of the quality of the target signal by integrating the first error vector amplitude of at least one first baseband signal output in the digital front-end link and the second error vector amplitude of at least one second baseband signal after the phase rotation of at least one first baseband signal, thereby improving the accuracy of determining the quality of the target signal.

[0006] The first aspect of the present disclosure provides a method for determining signal quality, including: encoding a target signal to obtain encoded data, and performing constellation mapping on the encoded data to obtain a constellation diagram of the target signal; serially inputting the constellation diagram into nodes at various levels of a digital front-end link to obtain first baseband signals output by nodes at various levels; sequentially sampling the first baseband signals output by at least one level of the nodes to obtain first target sampling points in each of the first baseband signals; determining a first error vector magnitude (Error Vector Magnitude, EVM for short) of each of the first baseband signals based on the first target sampling points in each of the first baseband signals; performing phase rotation on each of the first baseband signals to obtain each second baseband signal, and determining a second error vector magnitude of each of the second baseband signals; and determining the quality of the target signal based on each of the first error vector magnitudes and each of the second error vector magnitudes.

[0007] The method for determining the signal quality of the embodiment of the present disclosure encodes the target signal to obtain encoded data, performs constellation mapping on the encoded data to obtain a constellation diagram of the target signal; serially inputs the constellation diagram into nodes of each level of the digital front-end link to obtain first baseband signals output by the nodes of each level; sequentially samples the first baseband signals output by at least one level of the node to obtain first target sampling points in each of the first baseband signals; determines the first error vector magnitude of each of the first baseband signals according to the first target sampling points in each of the first baseband signals; performs phase rotation on each of the first baseband signals to obtain each second baseband signal, and determines the second error vector magnitude of each of the second baseband signals; determines the quality of the target signal according to each of the first error vector magnitudes and each of the second error vector magnitudes, thereby determining the quality of the target signal by combining the first error vector magnitude of at least one first baseband signal output in the digital front-end link and the second error vector magnitude of at least one second baseband signal after the phase rotation of at least one first baseband signal, thereby improving the accuracy of determining the quality of the target signal.

[0008] The second aspect of the present disclosure provides a signal quality determination device, including: an acquisition module, used to encode a target signal to obtain encoded data, and constellation mapping the encoded data to obtain a constellation diagram of the target signal; the acquisition module is also used to serially input the constellation diagram into nodes at various levels of a digital front-end link to obtain first baseband signals output by nodes at various levels; a sampling module, used to sequentially sample the first baseband signals output by at least one level of the nodes to obtain a first target sampling point in each of the first baseband signals; a first determination module, used to determine a first error vector amplitude of each of the first baseband signals based on the first target sampling point in each of the first baseband signals; a second determination module, used to phase rotate each of the first baseband signals to obtain each second baseband signal, and determine a second error vector amplitude of each of the second baseband signals; and a third determination module, used to determine the quality of the target signal based on each of the first error vector amplitudes and each of the second error vector amplitudes.

[0009] The third aspect embodiment of the present disclosure proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method for determining signal quality as described in the first aspect embodiment of the present disclosure is implemented.

[0010] The fourth aspect embodiment of the present disclosure proposes a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method for determining signal quality as described in the first aspect embodiment of the present disclosure is implemented.

[0011] The fifth aspect embodiment of the present disclosure proposes a computer program product. When the instruction processor in the computer program product executes, the method for determining signal quality as described in the first aspect embodiment of the present disclosure is implemented.

[0012] Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description or learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The above and / or additional aspects and advantages of the present disclosure will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0014] Figure 1 A flow chart of a method for determining signal quality provided by an embodiment of the present disclosure;

[0015] Figure 2 A schematic diagram of a process of serially inputting a constellation diagram provided by an embodiment of the present disclosure to nodes at various levels in a digital front-end link;

[0016] Figure 3 A flowchart of another method for determining signal quality provided by an embodiment of the present disclosure;

[0017] Figure 4 A flowchart of another method for determining signal quality provided by an embodiment of the present disclosure;

[0018] Figure 5 A flowchart of another method for determining signal quality provided by an embodiment of the present disclosure;

[0019] Figure 6 A schematic diagram of an EVM analysis process provided by an embodiment of the present disclosure;

[0020] Figure 7 A schematic diagram of the structure of a device for determining signal quality provided by an embodiment of the present disclosure;

[0021] Figure 8 It is a block diagram of an electronic device for determining signal quality according to an exemplary embodiment. DETAILED DESCRIPTION

[0022] Embodiments of the present disclosure are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0023] It should be understood that the quality of the wireless signal can be determined according to the EVM value, and the EVM value is negatively correlated with the quality of the wireless signal. For example, the smaller the EVM value, the better the quality of the wireless signal, and the larger the EVM value, the worse the quality of the wireless signal. Among them, the EVM analysis methods are currently mainly divided into two categories: direct extraction and data interpolation based on timing synchronization. The direct extraction method is to extract the best sampling point from the received data to be analyzed after matched filtering, and determine the EVM value based on the best sampling point; the data interpolation method based on timing synchronization is to calculate the best sampling point and minimum sampling point of the signal after matched filtering of the received data to be analyzed. The interpolation factor is calculated and the signal is interpolated. The EVM value is determined based on the interpolated signal. However, in the direct extraction method, when the optimal sampling point of the signal does not appear at the sampling point, the convergence of the signal constellation diagram is not high, which can easily lead to large measurement errors. The data interpolation method based on timing synchronization needs to use a parameter estimation method to estimate the position of the optimal sampling point, and then use an interpolation method to interpolate the signal according to the integer sequence number and the decimal interpolation factor. The parameter estimation method is complex to calculate and is affected by the sample size and sample code distribution. There is usually a large error jitter. The interpolation method does not make full use of the data and the interpolation coefficient estimation deviation leads to a large EVM calculation error.

[0024] In view of the above problems, the present disclosure proposes a method and device for determining signal quality.

[0025] The following describes a method and apparatus for determining signal quality according to an embodiment of the present disclosure with reference to the accompanying drawings.

[0026] Figure 1 A flowchart of a method for determining signal quality provided by an embodiment of the present disclosure is provided.

[0027] like Figure 1 As shown, the method for determining the signal quality may include the following steps:

[0028] Step 101, encode the target signal to obtain encoded data, and perform constellation mapping on the encoded data to obtain a constellation diagram of the target signal.

[0029] In order to improve the accuracy of determining the quality of wireless signals, as a possible implementation, a constellation diagram of the wireless signal may be integrated into a first baseband signal output by at least one node in a digital front end (DFE) link.

[0030] As an example, the constellation diagram of the target signal (eg, wireless signal) may be first obtained, such as by encoding the target signal to obtain encoded data, and then constellation mapping may be performed on the encoded data to obtain the constellation diagram of the target signal.

[0031] Step 102, the constellation diagram is serially input into nodes of each level of the digital front-end link to obtain a first baseband signal output by each level of the nodes.

[0032] As a possible implementation manner, as an example, the constellation diagram of the target signal is serially input into each node of the digital front-end link to obtain the first baseband signal output by each node of the digital front-end link.

[0033] Among them, Figure 2As shown, the digital front-end link may include an uplink and a downlink, and the nodes at each level of the digital front-end link may include but are not limited to a shaping filter node and a sampling node, wherein, in order to reduce inter-code interference, the filtering parameters of the shaping filter node are determined according to the sampling rate of the sampling node. For example, if the sampling rate of the sampling node is higher than the set threshold, the filtering parameter of the shaping filter node can be configured as parameter 1, and the baseband signal with a high sampling rate does not need to be filtered by a high-order matched filter, and EVM analysis can be performed directly. If the sampling rate of the sampling node is lower than the set threshold, the filtering parameter of the shaping filter node can be configured as parameter 2, and the baseband signal with a low sampling rate needs to be filtered by a matched filter, and the filtered data can be subjected to EVM analysis, wherein parameter 1 can be used to indicate a raised cosine filter, and parameter 2 can be used to indicate a root raised cosine filter.

[0034] Step 103: sequentially sample the first baseband signals output by at least one level of nodes to obtain first target sampling points in each first baseband signal.

[0035] In order to reduce the complexity of signal analysis, as an example, the first baseband signals output by at least one level of nodes may be sampled respectively to obtain the first target sampling points in each first baseband signal.

[0036] Step 104: Determine a first error vector magnitude of each first baseband signal according to a first target sampling point in each first baseband signal.

[0037] As an example, an expected constellation point corresponding to a first target sampling point in each first baseband signal may be obtained, and then, based on a difference between the first target sampling point in each first baseband signal and the corresponding expected constellation point, a first error vector amplitude of each first baseband signal may be determined.

[0038] Step 105: Perform phase rotation on each first baseband signal to obtain each second baseband signal, and determine a second error vector magnitude of each second baseband signal.

[0039] In order to avoid the sampling points in the first baseband signal being located on the coordinate axes of the standard coordinate system, which makes it impossible to accurately determine the quality of the target signal, as a possible implementation method, each first baseband signal can be phase rotated to obtain each second baseband signal, thereby sampling each second baseband signal in turn to obtain the second target sampling point of each second baseband signal, and then, based on the second target sampling point in each second baseband signal, the second error vector amplitude of each second baseband signal is determined.

[0040] Step 106: Determine the quality of the target signal according to each first error vector magnitude and each second error vector magnitude.

[0041] In order to improve the accuracy of determining the quality of the target signal, as a possible implementation manner, each first error vector magnitude and each second error vector magnitude may be combined to determine the quality of the target signal.

[0042] In summary, the target signal is encoded to obtain encoded data, and the encoded data is constellation mapped to obtain a constellation diagram of the target signal; the constellation diagram is sequentially input into nodes of each level of the digital front-end link to obtain first baseband signals output by nodes of each level; the first baseband signals output by at least one level of nodes are sampled sequentially to obtain first target sampling points in each first baseband signal; the first error vector amplitude of each first baseband signal is determined according to the first target sampling points in each first baseband signal; each first baseband signal is phase rotated to obtain each second baseband signal, and the second error vector amplitude of each second baseband signal is determined; the target signal is determined according to each first error vector amplitude and each second error vector amplitude. The quality of the target signal is determined by sampling the first baseband signal output by at least one level node of the digital front-end link to obtain the first target sampling point in each first baseband signal, and determining the second error vector amplitude of the second baseband signal obtained by phase rotation of each first baseband signal, thereby determining the quality of the target signal according to each first error vector amplitude and each second error vector amplitude, realizing the first error vector amplitude of at least one first baseband signal output in the integrated digital front-end link and the second error vector amplitude of at least one second baseband signal after the phase rotation of at least one first baseband signal, and improving the accuracy of determining the quality of the target signal.

[0043] In order to clearly explain how the first baseband signals output by at least one level of nodes are sampled in sequence in the above embodiment to obtain the first target sampling point in each first baseband signal, the present disclosure proposes another method for determining signal quality.

[0044] Figure 3 A flowchart of another method for determining signal quality provided by an embodiment of the present disclosure.

[0045] like Figure 3 As shown, the method for determining the signal quality may include the following steps:

[0046] Step 301, encode the target signal to obtain encoded data, perform constellation mapping on the encoded data to obtain a constellation diagram of the target signal, and serially input the constellation diagram into nodes at various levels of the digital front-end link to obtain a first baseband signal output by the nodes at various levels.

[0047] Step 302: for any first baseband signal among the first baseband signals output by at least one level of node, determine a sampling interval of any first baseband signal according to a symbol rate of each data symbol and a sampling rate of each data symbol in any first baseband signal.

[0048] In order to completely retain the original information in the target signal while reducing the complexity of signal analysis, as a possible implementation method, any first baseband signal can be sampled at equal intervals. Therefore, the sampling interval of any first baseband signal can be determined first, and according to the sampling interval, the equal interval sampling of any first baseband signal can be implemented. Among them, the symbol rate of each data symbol in any first baseband signal is the same and the sampling rate of each data symbol is also the same, for example, the sampling interval Winlen = ceil (Fs / Rs), ceil () indicates rounding up, Fs indicates the symbol rate, and Rs indicates the sampling rate.

[0049] Step 303: interpolate, scale and filter any first baseband signal in sequence according to the sampling interval of any first baseband signal to obtain a third baseband signal corresponding to any first baseband signal.

[0050] Since the original information in the target signal may not be fully retained when the first baseband signal with a lower sampling rate is sampled at equal intervals, in order to avoid the situation where the original information in the target signal cannot be fully retained when the first baseband signal is sampled at equal intervals, and at the same time avoid the first target sampling point not being located at the sampling point of the first baseband signal, as a possible implementation method, based on the sampling interval of any first baseband signal, any first baseband signal may be interpolated, scaled and filtered in sequence to obtain a third baseband signal corresponding to any first baseband signal.

[0051] As an example, the interpolation interval of any first baseband signal is determined according to the sampling interval of any first baseband signal; according to the interpolation interval of any first baseband signal, any first baseband signal is interpolated to obtain any first baseband signal after interpolation; using the sampling interval of any first baseband signal, any first baseband signal after interpolation is scaled to obtain any first baseband signal after scaling; any first baseband signal after scaling is filtered to obtain a third baseband signal corresponding to any first baseband signal.

[0052] For example, the sampling interval of any first baseband signal is Winlen, and the interpolation interval of any first baseband signal can be Winlen-1, that is, 0 is padded at every Winlen-1 point in any first baseband signal, and any first baseband signal after interpolation is amplified by Winlen times, and the amplified first baseband signal is filtered to obtain a third baseband signal corresponding to any first baseband signal.

[0053] Step 304: Determine a first sampling position of any first baseband signal according to a sampling interval of any first baseband signal.

[0054] In order to completely preserve the original information in the target signal, as an example, the first sampling position of any first baseband signal can be determined first, wherein the first sampling position can be smaller than the sampling interval corresponding to the first baseband signal. For example, the first sampling position is k, and the sampling interval corresponding to the first baseband signal is Winlen, and k is between [1, Winlen].

[0055] Step 305 , sampling the third baseband signal corresponding to any first baseband signal at equal intervals according to the sampling interval and the first sampling position of any first baseband signal, so as to obtain a first target sampling point in any first baseband signal.

[0056] As a possible implementation method, the sampling positions of the third baseband signal corresponding to any first baseband signal can be determined according to the sampling interval and the first sampling position of any first baseband signal, and the third baseband signal can be sampled at each sampling position to obtain the first target sampling point in any first baseband signal.

[0057] Step 306: Determine a first error vector magnitude of each first baseband signal according to a first target sampling point in each first baseband signal.

[0058] Step 307: Perform phase rotation on each first baseband signal to obtain each second baseband signal, and determine a second error vector magnitude of each second baseband signal.

[0059] As a possible implementation method, each second baseband signal can be obtained by performing phase rotation on each first baseband signal. Then, based on steps 302 to 305 in the embodiment of the present disclosure, each second baseband signal is sampled to obtain a second target sampling point in each second baseband signal. According to the second target sampling point in each second baseband signal, the second error vector amplitude of each second baseband signal is determined.

[0060] As another possible implementation manner, phase rotation is performed on the third baseband signal corresponding to each first baseband signal to obtain each second baseband signal, and then, based on steps 304 to 305 in the embodiment of the present disclosure, each second baseband signal is sampled to obtain a second target sampling point in each second baseband signal, and a second error vector amplitude of each second baseband signal is determined according to the second target sampling point in each second baseband signal.

[0061] Step 308: Determine the quality of the target signal according to each first error vector magnitude and each second error vector magnitude.

[0062] It should be noted that the execution process of step 301 and step 308 can be implemented in any way in the embodiments of the present disclosure, and the embodiments of the present disclosure do not limit this and will not be described in detail.

[0063] In summary, for any first baseband signal among the first baseband signals output by at least one first-level node, according to the symbol rate of each data symbol and the sampling rate of each data symbol in any first baseband signal, the sampling interval of any first baseband signal is determined; according to the sampling interval of any first baseband signal, any first baseband signal is interpolated, scaled and filtered in sequence to obtain a third baseband signal corresponding to any first baseband signal; according to the sampling interval of any first baseband signal, the first sampling position of any first baseband signal is determined; according to the sampling interval and the first sampling position of any first baseband signal, the third baseband signal corresponding to any first baseband signal is sampled at equal intervals to obtain a first target sampling point in any first baseband signal, thereby, sampling can be accurately performed from each first baseband signal to obtain a first target sampling point in the first baseband signal, the first target sampling point can completely retain the original information in the target signal, and the first error vector magnitude of each first baseband signal is determined based on the first target sampling point in each first baseband signal, thereby improving the accuracy of the first error vector magnitude.

[0064] In order to clearly explain how the first error vector magnitude of each first baseband signal is determined according to the first target sampling point in each first baseband signal in the above embodiment, the present disclosure proposes another method for determining signal quality.

[0065] Figure 4 A flowchart of another method for determining signal quality provided by an embodiment of the present disclosure.

[0066] like Figure 4 As shown, the method for determining the signal quality may include the following steps:

[0067] Step 401, encode the target signal to obtain encoded data, perform constellation mapping on the encoded data to obtain a constellation diagram of the target signal, and serially input the constellation diagram into nodes at various levels of the digital front-end link to obtain a first baseband signal output by the nodes at various levels.

[0068] Step 402: sequentially sample the first baseband signals output by at least one level of nodes to obtain first target sampling points in each first baseband signal.

[0069] Step 403 : normalize the amplitude of the first target sampling point in each first baseband signal to obtain the normalized first target sampling point of each first baseband signal.

[0070] In order to make the amplitude of the signal within a certain range to facilitate subsequent processing and operation, as an example, the first target sampling points in the first baseband signal can be amplitude normalized to obtain the normalized first target sampling points of each first baseband signal.

[0071] For example, the mean of the sampling values ​​of each first target sampling point in any first baseband signal can be determined, and the sampling values ​​of each first target sampling point in any first baseband signal can be compared with the corresponding mean to achieve amplitude normalization of the first target sampling point. The sampling values ​​of each first target sampling point can be in complex form.

[0072] Step 404: for any first baseband signal, according to the modulation type of the digital front-end link where any first baseband signal is located, query and set the constellation table to obtain a plurality of expected constellation points corresponding to any first baseband signal.

[0073] The constellation table is set to include a mapping relationship between modulation types and expected constellation points.

[0074] As a possible implementation of the embodiment of the present disclosure, for any first baseband signal, a first error vector magnitude of the first baseband signal may be determined according to a difference between a first target sampling point in the first baseband signal and an expected constellation point. Therefore, as an example, a set constellation table may be obtained, wherein the set constellation table includes a mapping relationship between a modulation type and an expected constellation point, and according to the modulation type of a digital front-end link where any first baseband signal is located, the set constellation table may be queried to obtain a plurality of expected constellation points corresponding to any first baseband signal.

[0075] Wherein, taking the modulation type of the digital front-end link where any first baseband signal is located as Quadrature Phase Shift Keying (QPSK) as an example, the constellation table can be set as shown in Table 1.

[0076] Table 1 Mapping relationship between modulation type and expected constellation points

[0077] Binary Sequence Expected constellation point 00 exp(1*sqrt(-1)*pi / 4) 01 exp(3*sqrt(-1)*pi / 4) 10 exp(-1*sqrt(-1)*pi / 4) 11 exp(-3*sqrt(-1)*pi / 4)

[0078] Step 405: Determine a target expected constellation point from a plurality of expected constellation points according to any normalized first target sampling point.

[0079] The distance between the target desired constellation point and any normalized first target sampling point is the smallest.

[0080] It should be understood that the expected constellation point is a predefined standard point with a fixed position and characteristics, and can be used as a reference standard for signal quality. As a possible implementation method, the difference between any normalized first target sampling point and the nearest expected constellation point among multiple expected constellation points can be determined. Therefore, the target expected constellation point corresponding to any normalized first target sampling point can be obtained from the multiple expected constellation points, that is, the expected constellation point with the smallest distance from any normalized first target sampling point.

[0081] Step 406: Determine a first error vector magnitude of any first baseband signal according to a difference between each normalized first target sampling point and a corresponding target expected constellation point in any first baseband signal.

[0082] For example, the first error vector magnitude EWM = sqrt(A), where

[0083] A=X_1+X_2+...+X_(s+1);

[0084] X_1=abs(power((rbstar′(1)-rbstar_ideal(1)) / rbstar_ideal(1),2));

[0085] X_2=abs(power((rbstar′(2)-rbstar_ideal(2)) / rbstar_ideal(2),2))…

[0086] X_(s+1)=abs(power((rbstar′(s+1)-rbstar_ideal(s+1)) / rbstar_ideal(s+1),2));

[0087] Among them, rbstar′(1), rbstar′(2),…,rbstar′(s+1) represent the normalized first target sampling points in any first baseband signal, and rbstar_ideal(1), rbstar_ideal(2)…,rbstar_ideal(s+1) represent the target expected constellation points corresponding to the normalized first target sampling points.

[0088] Step 407: Perform phase rotation on each first baseband signal to obtain each second baseband signal, and determine a second error vector magnitude of each second baseband signal.

[0089] In order to avoid the sampling points in the first baseband signal being located on the coordinate axis of the standard coordinate system, and the quality of the target signal cannot be accurately determined, as a possible implementation method, each first baseband signal can be phase rotated. As an example, the rotation angle and rotation direction of each first baseband signal can be determined, and the corresponding first baseband signal can be phase rotated based on the rotation angle and rotation direction to obtain the second baseband signal corresponding to each first baseband signal. The rotation angle of each first baseband signal can be determined according to the angle formed by the line connecting any two expected constellation points in the set constellation table and the origin of the standard coordinate system. For example, the rotation angle of each first baseband signal can be half of the minimum value of the angle formed by the line connecting any two expected constellation points in the set constellation table and the origin of the standard coordinate system.

[0090] As a possible implementation manner, the manner of determining the second error vector magnitude of each second baseband signal may refer to the above steps 402 to 406, which will not be described in detail in this disclosure.

[0091] Step 408: Determine the quality of the target signal according to each first error vector magnitude and each second error vector magnitude.

[0092] It should be noted that the execution process of steps 401 to 402 and step 408 can be implemented in any manner in the embodiments of the present disclosure, and the embodiments of the present disclosure do not limit this and will not be described in detail.

[0093] In summary, the first target sampling points in each first baseband signal are amplitude normalized to obtain the normalized first target sampling points of each first baseband signal; for any first baseband signal, according to the modulation type of the digital front-end link where any first baseband signal is located, the constellation table is queried and set to obtain multiple expected constellation points corresponding to any first baseband signal; according to any normalized first target sampling point, a target expected constellation point is determined from multiple expected constellation points; according to the difference between each normalized first target sampling point in any first baseband signal and the corresponding target expected constellation point, the first error vector amplitude of any first baseband signal is determined, thereby, according to the first target sampling point in each first baseband signal and the corresponding expected constellation point, the first error vector amplitude of each first baseband signal can be accurately determined.

[0094] In order to clearly explain how the quality of the target signal is determined according to each first error vector magnitude and each second error vector magnitude in the above embodiments, the present disclosure proposes another method for determining signal quality.

[0095] Figure 5 A flowchart of another method for determining signal quality provided by an embodiment of the present disclosure.

[0096] like Figure 5 As shown, the method for determining the signal quality may include the following steps:

[0097] Step 501, encode the target signal to obtain encoded data, perform constellation mapping on the encoded data to obtain a constellation diagram of the target signal, and serially input the constellation diagram into nodes at various levels of the digital front-end link to obtain a first baseband signal output by the nodes at various levels.

[0098] Step 502: sequentially sample the first baseband signals output by at least one level of nodes to obtain first target sampling points in each first baseband signal.

[0099] Step 503: Determine a first error vector magnitude of each first baseband signal according to a first target sampling point in each first baseband signal.

[0100] Step 504: perform phase rotation on each first baseband signal to obtain each second baseband signal, and determine a second error vector magnitude of each second baseband signal.

[0101] Step 505: Determine a third error vector magnitude with the smallest value from among the first error vector magnitudes.

[0102] As an example, the first error vector magnitudes are arranged in ascending order to obtain a first arrangement sequence, and the first error vector magnitude that is ranked first in the first arrangement sequence is the third error vector magnitude with the smallest value.

[0103] Step 506: Determine a fourth error vector magnitude with the smallest value from among the second error vector magnitudes.

[0104] As an example, the first error vector magnitudes are arranged in ascending order to obtain a second arrangement order, and the second error vector magnitude that is ranked first in the second arrangement order is the fourth error vector magnitude with the smallest value.

[0105] Step 507: Determine the quality of the target signal according to the minimum value of the third error vector magnitude and the fourth error vector magnitude.

[0106] As a possible implementation method of the embodiment of the present disclosure, the third error vector amplitude and the fourth error vector amplitude are compared. When the third error vector amplitude is greater than the fourth error vector amplitude, the quality of the target signal is determined based on the fourth error vector amplitude, wherein the fourth error vector amplitude is negatively correlated with the quality of the target signal; when the third error vector amplitude is less than or equal to the fourth error vector amplitude, the quality of the target signal is determined based on the third error vector amplitude, wherein the third error vector amplitude is negatively correlated with the quality of the target signal.

[0107] It should be noted that the execution process of steps 501 to 504 can be implemented in any way in the embodiments of the present disclosure, and the embodiments of the present disclosure do not limit this and will not be described in detail.

[0108] In summary, by determining the third error vector amplitude with the smallest value from each first error vector amplitude; determining the fourth error vector amplitude with the smallest value from each second error vector amplitude; and determining the quality of the target signal according to the minimum value of the third error vector amplitude and the fourth error vector amplitude, the quality of the target signal is determined by comprehensively considering the minimum value of the first error vector amplitude of each first baseband signal and the second error vector amplitude of each second baseband signal, thereby improving the accuracy of determining the quality of the target signal.

[0109] Based on any embodiment of the present disclosure, the implementation process of the present disclosure mainly includes the following steps:

[0110] 1. Obtain the target data required for EVM analysis:

[0111] (1) Select the EVM analysis point. The point should be selected where the passband is flat. For the point where the passband is uneven, the point should be selected after the unevenness is compensated. The point selection includes not only the total output of the DFE uplink and the total output of the DFE downlink, but also the output of each level in the DFE uplink and the output of each level in the DFE downlink.

[0112] (2) For sites with higher sampling rates, the shaping filter parameters can be configured as configuration 1, and for sites with lower sampling rates, the shaping filter parameters can be configured as configuration 2; wherein, configuration 1 is used to indicate raised cosine, and configuration 2 is used to indicate root raised cosine; for example, the signal symbol rate is assumed to be 20ksps, and the signal sampling rate of the uplink DFE output is 25.6MHz. In order to analyze the EVM performance of the uplink DFE, since the ratio of the uplink DFE sampling rate to the symbol rate is 1280, the shaping filter parameters can be set to configuration 1, that is, set to a raised cosine filter; the signal symbol rate is assumed to be 20ksps, the signal sampling rate of the uplink DFE output is 25.6MHz, and the signal sampling rate of the downlink DFE output is 80kHz. In order to analyze the EVM performance of the downlink DFE, since the ratio of the downlink DFE sampling rate to the symbol rate is 4, the shaping filter parameters can be set to configuration 2, that is, set to a root raised cosine filter.

[0113] (3) If the shaping filter parameter is configuration 1, the data is passed directly. If the shaping filter parameter is configuration 2, a matched filter is used to match the data. The matched filter is determined based on the relative relationship between the sampling rate and the symbol rate. The data after matched filtering is represented as: r = {r_1, r_2, ..., r_N};

[0114] 2. If Figure 6As shown, EVM analysis includes the following steps:

[0115] (1) Determine the sliding window length (sampling interval) Winlen and the ideal constellation point, interpolate and filter the data;

[0116] For example, the search window length (sampling interval) Winlen = ceil(Fs / Rs) is determined based on the relative relationship between the symbol rate (Rs) and the sampling rate (Fs) of the signal r (baseband signal), where ceil() represents rounding up. When interpolating the signal r, 0 can be added to every (Winlen-1) points, and the whole signal can be amplified by Winlen times, so that ra = {Winlen*r_1, 0, ..., 0, Winlen*r_2, 0, ..., 0, ..., Winlen*r_(N-1), 0, ..., 0, Winlen*r_N}. According to the modulation type of the digital front-end link and the constellation mapping relationship, the ideal constellation point is determined as star = {s_1,...,s_n}; then, the interpolation filter coe is used to filter ra to obtain the output rb = {rb_1,rb_2,...,rb_N1} of this step; where the interpolation filter coe, the passband cutoff frequency should include the main lobe of the signal, usually set to fpass = Rs*(1+alpha)*0.5, alpha is the roll-off coefficient, the value is between [0,1], and the stopband cutoff frequency should not exceed half of the signal sampling rate before upsampling, that is, less than Fs / 2. The passband ripple and stopband suppression values ​​should comprehensively consider the filter order and test accuracy requirements, and the typical values ​​can be 0.01dB and 80dB. The filter designed considering the above parameters should be normalized, that is, if the original filter coefficient is coe01 = [coe0_1, ..., coe0_m], then the coefficient of the interpolation filter coe should be normalized to: coe01 = [coe0_1 / x, ..., coe0_m / x], x = coe0_1 + ... + coe0_m.

[0117] (2) For the starting point of each window, extract data at equal intervals from the data as the optimal sampling points;

[0118] For each rb, determine the sliding window point k, k is between [1, Winlen], take the sampling point rbstar = {rb_k, rb_(k+Winlen),..., rb_(k+s*Winlen)}, s should be selected so that k+s*Winlen does not exceed N1 and is closest to N1. In the following, rbstar is abbreviated as rbstar = {x_1,...,x_(s+1)};

[0119] (3) Normalize the optimal sampling point data, compare it with the ideal constellation point, and calculate the EVM vector value;

[0120] Calculate the average amplitude mean_amp of rbstar = (abs(x_1)+...+abs(x_(s+1))) / (s+1), where abs() means taking the absolute value. Normalize rbstar to rbstar′ = {a*x_1 / mean_amp,...,a*x_(s+1) / mean_amp}. Where a represents the average amplitude of the ideal constellation point. Determine each value rbstar_ideal(i) of the ideal constellation point rbstar_ideal and select the one closest to rbstar′(i) in star. Single EVM value calculation, that is, comparing the difference between rbstar′(i) and rbstar_ideal, the calculation method is: EVM = sqrt(A), A = X_1+X_2+...+X_(s+1), X_1 = abs(power((rbstar′(1)-rbstar_ideal(1)) / rbstar_ideal(1),2));

[0121] X_2=abs(power((rbstar′(2)-rbstar_ideal(2)) / rbstar_ideal(2),2))…

[0122] X_(s+1)=abs(power((rbstar′(s+1)-rbstar_ideal(s+1)) / rbstar_ideal(s+1),2));

[0123] (4) Take the minimum value EVM1 among the EVM vector values;

[0124] Minimize all components of the EVM vector to get EVM1;

[0125] (5) Perform phase rotation on the input data (all baseband signals), and repeat steps (2) to (4) in step 2 to obtain EVM2;

[0126] The phase rotation angle value may be set to half of the minimum angle between two ideal constellation points.

[0127] (6) Select the minimum of EVM1 and EVM2, EVM_min, which is the EVM measurement value of the input data;

[0128] It should be noted that the method for determining the EVM measurement value of the embodiment of the present invention has been verified through a large number of simulations and is more accurate than the timing synchronized data interpolation method in the related art. In addition, at high sampling rates, the shaping filter parameters are configured as raised cosine, which reduces the high-order matched filtering when analyzing EVM, making the EVM analysis results more accurate.

[0129] (7) Based on the EVM measurement, determine the signal quality.

[0130] In order to implement the above embodiment, the present disclosure also proposes a device for determining signal quality.

[0131] Figure 7 A schematic diagram of the structure of a device for determining signal quality provided by an embodiment of the present disclosure.

[0132] like Figure 7 As shown, the signal quality determination device 700 includes: an acquisition module 710 , a sampling module 720 , a first determination module 730 , a second determination module 740 and a third determination module 750 .

[0133] Among them, the acquisition module 710 is used to encode the target signal to obtain the encoded data, and perform constellation mapping on the encoded data to obtain the constellation diagram of the target signal; the acquisition module 710 is also used to serially input the constellation diagram into the nodes at each level of the digital front-end link to obtain the first baseband signal output by the nodes at each level; the sampling module 720 is used to sample the first baseband signal output by at least one level of node in turn to obtain the first target sampling point in each first baseband signal; the first determination module 730 is used to determine the first error vector amplitude of each first baseband signal according to the first target sampling point in each first baseband signal; the second determination module 740 is used to perform phase rotation on each first baseband signal to obtain each second baseband signal, and determine the second error vector amplitude of each second baseband signal; the third determination module 750 is used to determine the quality of the target signal according to each first error vector amplitude and each second error vector amplitude.

[0134] As a possible implementation of the embodiment of the present disclosure, the sampling module 720 is used to determine, for any first baseband signal among the first baseband signals output by at least one level of the node, a sampling interval of any first baseband signal according to the symbol rate of each data symbol in any first baseband signal and the sampling rate of each data symbol; interpolate, scale and filter any first baseband signal in sequence according to the sampling interval of any first baseband signal to obtain a third baseband signal corresponding to any first baseband signal; determine the first sampling position of any first baseband signal according to the sampling interval of any first baseband signal; and perform equal-interval sampling on the third baseband signal corresponding to any first baseband signal according to the sampling interval and the first sampling position of any first baseband signal to obtain a first target sampling point in any first baseband signal.

[0135] As a possible implementation method of the embodiment of the present disclosure, the sampling module 720 is used to determine the interpolation interval of any first baseband signal according to the sampling interval of any first baseband signal; perform interpolation processing on any first baseband signal according to the interpolation interval of any first baseband signal to obtain any first baseband signal after interpolation processing; use the sampling interval of any first baseband signal to perform scaling processing on any first baseband signal after interpolation processing to obtain any first baseband signal after scaling processing; perform filtering processing on any first baseband signal after scaling processing to obtain a third baseband signal corresponding to any first baseband signal.

[0136] As a possible implementation manner of an embodiment of the present disclosure, the first determination module 730 is used to normalize the amplitude of the first target sampling point in each first baseband signal to obtain the normalized first target sampling point of each first baseband signal; for any first baseband signal, according to the modulation type of the digital front-end link where any first baseband signal is located, query the set constellation table to obtain multiple expected constellation points corresponding to any first baseband signal, wherein the set constellation table includes a mapping relationship between the modulation type and the expected constellation point; according to any of the normalized first target sampling points, determine the target expected constellation point from the multiple expected constellation points, wherein the distance between the target expected constellation point and any normalized first target sampling point is the smallest; and determine the first error vector amplitude of any first baseband signal according to the difference between each normalized first target sampling point in any first baseband signal and the corresponding target expected constellation point.

[0137] As a possible implementation method of the embodiment of the present disclosure, the third determination module 750 is used to determine a third error vector amplitude with a minimum value from each first error vector amplitude; determine a fourth error vector amplitude with a minimum value from each second error vector amplitude; and determine the quality of the target signal according to the minimum value of the third error vector amplitude and the fourth error vector amplitude.

[0138] As a possible implementation method of an embodiment of the present disclosure, the second determination module 740 is used to determine the rotation angle of any first baseband signal according to the angle formed by the line connecting any two expected constellation points in the set constellation table and the origin of the standard coordinate system; and to perform phase rotation on any first baseband signal using the set rotation direction and the rotation angle to obtain a second baseband signal corresponding to any first baseband signal.

[0139] As a possible implementation method of the embodiment of the present disclosure, the second determination module 740 is used to sample any second baseband signal to obtain a second target sampling point in any second baseband signal; and determine a second error vector amplitude of any second baseband signal according to the second target sampling point in any second baseband signal.

[0140] As a possible implementation manner of the embodiment of the present disclosure, each level of nodes includes: a shaping filter node and a sampling node, wherein the filtering parameters of the shaping filter node are determined according to the sampling rate of the sampling node.

[0141] The signal quality determination device of the embodiment of the present disclosure encodes the target signal to obtain the encoded data, performs constellation mapping on the encoded data to obtain the constellation diagram of the target signal; sequentially inputs the constellation diagram into the nodes of each level of the digital front-end link to obtain the first baseband signal output by the nodes of each level; sequentially samples the first baseband signal output by at least one level of node to obtain the first target sampling point in each first baseband signal; determines the first error vector amplitude of each first baseband signal according to the first target sampling point in each first baseband signal; performs phase rotation on each first baseband signal to obtain each second baseband signal, and determines the second error vector amplitude of each second baseband signal; determines the quality of the target signal according to each first error vector amplitude and each second error vector amplitude, thereby determining the quality of the target signal by integrating the first error vector amplitude of at least one first baseband signal output in the digital front-end link and the second error vector amplitude of at least one second baseband signal after the phase rotation of at least one first baseband signal, thereby improving the accuracy of the quality determination of the target signal.

[0142] It should be noted that the above explanation of the embodiment of the method for determining signal quality is also applicable to the device for determining signal quality of this embodiment, and will not be repeated here.

[0143] In order to implement the above embodiments, the present application also proposes an electronic device, such as Figure 8 As shown, Figure 8 It is a block diagram of an electronic device for determining signal quality according to an exemplary embodiment.

[0144] like Figure 8 As shown, the electronic device 800 includes:

[0145] The memory 810 and the processor 820, a bus 830 connecting different components (including the memory 810 and the processor 820), the memory 810 stores a computer program, and when the processor 820 executes the program, the method for determining the signal quality described in the embodiment of the present disclosure is implemented.

[0146] Bus 830 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. For example, these architectures include but are not limited to Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus and Peripheral Component Interconnect (PCI) bus.

[0147] The electronic device 800 typically includes a variety of electronic device readable media. These media can be any available media that can be accessed by the electronic device 800, including volatile and non-volatile media, removable and non-removable media.

[0148] The memory 810 may also include computer system readable media in the form of volatile memory, such as random access memory (RAM) 840 and / or cache memory 850. The electronic device 800 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 860 may be used to read and write non-removable, non-volatile magnetic media ( Figure 8 not shown, usually called a "hard drive"). Although Figure 8 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 830 via one or more data medium interfaces. The memory 810 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present disclosure.

[0149] A program / utility 880 having a set (at least one) of program modules 870 may be stored, for example, in the memory 810, such program modules 870 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 870 generally perform the functions and / or methods of the embodiments described in the present disclosure.

[0150] The electronic device 800 may also communicate with one or more external devices 890 (e.g., keyboards, pointing devices, displays, etc.), one or more devices that enable a user to interact with the electronic device 800, and / or any device that enables the electronic device 800 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed through an input / output (I / O) interface 892. Furthermore, the electronic device 800 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 893. Figure 8 As shown, the network adapter 893 communicates with other modules of the electronic device 800 via the bus 830. It should be understood that although Figure 8 Not shown, other hardware and / or software modules may be used in conjunction with electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0151] The processor 820 executes various functional applications and data processing by running the programs stored in the memory 810 .

[0152] It should be noted that the implementation process and technical principles of the electronic device of this embodiment refer to the aforementioned explanation of the method for determining the signal quality of the embodiment of the present disclosure, and will not be repeated here.

[0153] In order to implement the above embodiments, the present application further proposes a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method for determining the signal quality described in the above embodiments is implemented.

[0154] In order to implement the above embodiments, the present disclosure further provides a computer program product. When an instruction processor in the computer program product executes, the signal quality determination method described in the above embodiments is executed.

[0155] In the description of this specification, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0156] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0157] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for determining signal quality, characterized in that: include: Encoding the target signal to obtain encoded data, and performing constellation mapping on the encoded data to obtain a constellation diagram of the target signal; Inputting the constellation diagram serially into nodes at various levels of the digital front-end link to obtain first baseband signals output by nodes at various levels; Sequentially sampling the first baseband signals output by at least one level of the nodes to obtain first target sampling points in each of the first baseband signals; determining a first error vector magnitude of each of the first baseband signals according to a first target sampling point in each of the first baseband signals; performing phase rotation on each of the first baseband signals to obtain each of the second baseband signals, and determining a second error vector magnitude of each of the second baseband signals; The quality of the target signal is determined according to each of the first error vector magnitudes and each of the second error vector magnitudes.

2. The method according to claim 1, characterized in that The sequentially sampling the first baseband signals output by the at least one level of nodes to obtain the first target sampling points in each of the first baseband signals includes: For any first baseband signal among the first baseband signals output by at least one level of the nodes, determining a sampling interval of any first baseband signal according to a symbol rate of each data symbol in any first baseband signal and a sampling rate of each data symbol; According to a sampling interval of any of the first baseband signals, sequentially interpolate, scale and filter any of the first baseband signals to obtain a third baseband signal corresponding to any of the first baseband signals; Determining a first sampling position of any of the first baseband signals according to a sampling interval of any of the first baseband signals; According to the sampling interval and the first sampling position of any of the first baseband signals, the third baseband signal corresponding to any of the first baseband signals is sampled at equal intervals to obtain a first target sampling point in any of the first baseband signals.

3. The method according to claim 2, characterized in that The interpolating, scaling and filtering any of the first baseband signals in sequence according to the sampling interval of any of the first baseband signals to obtain a third baseband signal corresponding to any of the first baseband signals includes: Determining an interpolation interval of any of the first baseband signals according to a sampling interval of any of the first baseband signals; performing interpolation processing on any of the first baseband signals according to an interpolation interval of any of the first baseband signals to obtain any of the first baseband signals after interpolation processing; Using the sampling interval of any of the first baseband signals, scaling any of the first baseband signals after interpolation processing to obtain any of the scaled first baseband signals; A filtering process is performed on any of the first baseband signals after the scaling process to obtain a third baseband signal corresponding to any of the first baseband signals.

4. The method according to claim 1, characterized in that: The determining, according to the first target sampling point in each of the first baseband signals, a first error vector magnitude of each of the first baseband signals comprises: Normalizing the amplitude of the first target sampling point in each of the first baseband signals to obtain the normalized first target sampling point of each of the first baseband signals; For any of the first baseband signals, querying a set constellation table according to a modulation type of a digital front-end link where any of the first baseband signals is located, so as to obtain a plurality of expected constellation points corresponding to any of the first baseband signals, wherein the set constellation table includes a mapping relationship between the modulation type and the expected constellation points; Determining a target expected constellation point from the plurality of expected constellation points according to any of the normalized first target sampling points, wherein a distance between the target expected constellation point and any of the normalized first target sampling points is the smallest; A first error vector magnitude of any of the first baseband signals is determined according to a difference between each of the normalized first target sampling points and a corresponding target expected constellation point in any of the first baseband signals.

5. The method according to claim 1, characterized in that: The determining the quality of the target signal according to each of the first error vector magnitudes and each of the second error vector magnitudes includes: Determining a third error vector magnitude having a minimum value from among the first error vector magnitudes; Determining a fourth error vector magnitude with a minimum value from each of the second error vector magnitudes; The quality of the target signal is determined according to a minimum value between the third error vector magnitude and the fourth error vector magnitude.

6. The method according to claim 1, characterized in that The performing phase rotation on each of the first baseband signals to obtain each of the second baseband signals includes: For any of the first baseband signals, determining a rotation angle of any of the first baseband signals according to an angle formed by a line connecting any two expected constellation points in a set constellation table and an origin of a standard coordinate system; By setting the rotation direction and the rotation angle, phase rotation is performed on any of the first baseband signals to obtain a second baseband signal corresponding to any of the first baseband signals.

7. The method according to claim 1, characterized in that The determining a second error vector magnitude of each of the second baseband signals comprises: Sampling any of the second baseband signals to obtain a second target sampling point in any of the second baseband signals; A second error vector magnitude of any of the second baseband signals is determined according to a second target sampling point in any of the second baseband signals.

8. The method according to any one of claims 1 to 7, characterized in that The nodes at each level include: a shaping filter node and a sampling node, wherein the filtering parameters of the shaping filter node are determined according to the sampling rate of the sampling node.

9. A device for determining signal quality, characterized in that: include: An acquisition module is used to encode the target signal to obtain encoded data, and perform constellation mapping on the encoded data to obtain a constellation diagram of the target signal; The acquisition module is further used to serially input the constellation diagram into nodes at various levels of the digital front-end link to obtain first baseband signals output by nodes at various levels; A sampling module, used for sequentially sampling the first baseband signals output by at least one level of the nodes to obtain a first target sampling point in each of the first baseband signals; A first determination module, configured to determine a first error vector magnitude of each of the first baseband signals according to a first target sampling point in each of the first baseband signals; a second determination module, configured to perform phase rotation on each of the first baseband signals to obtain each of the second baseband signals, and determine a second error vector magnitude of each of the second baseband signals; The third determination module is used to determine the quality of the target signal according to each of the first error vector magnitudes and each of the second error vector magnitudes.

10. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for determining the signal quality according to any one of claims 1 to 8 is implemented.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for determining signal quality according to any one of claims 1 to 8 is implemented.

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