Signal identification method and system for mobile phone, storage medium and electronic device

Abstract

The application relates to the technical field of communication signal processing, and particularly discloses a signal identification method and system for a mobile phone, a storage medium and an electronic device. The signal identification method comprises the following steps: monitoring received data obtained when the mobile phone receives a signal in real time, wherein the received data comprises a signal strength deviation value and a signal time deviation value; calculating a signal identification deviation value; comparing the signal identification deviation value with a signal identification deviation threshold value; if the signal identification deviation value is greater than or equal to the signal identification deviation threshold value, a large-identification-deviation signal is generated, so as to indicate that the signal strength and signal time deviation are large when the mobile phone identifies the received signal, and the signal performance of the mobile phone is reflected from the data in two different dimensions of the signal strength and the signal receiving time.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of communication signal processing, in particular to a signal identification method and system for a mobile phone, a storage medium and an electronic device. BACKGROUND

[0002] Communication technology is the basis for mobile phone signal identification. A mobile phone connects with a base station through wireless communication technology to realize data transmission and reception. When the mobile phone processes the received wireless signal through the built-in signal processor, it can identify the current connected network type and adjust the communication parameters and strategies according to the network type to optimize the communication performance. However, the environment in which the mobile phone is located may interfere with the mobile phone's identification of the current connected network type, and thus needs to be addressed.

[0003] The actual waveform of the signal recognized by the mobile phone is obtained through an oscilloscope, and the actual signal waveform is compared and analyzed with the interference signal waveform to obtain a waveform similarity value. The waveform similarity value is compared with a waveform similarity threshold value. If the waveform similarity value is less than the waveform similarity threshold value, an interference identification second signal is generated, indicating that the actual signal waveform and the interference signal waveform have a small amplitude deviation and a small feature point deviation, meaning that the mobile phone is affected by interference. Based on the interference identification second signal, a network mode switching value is obtained to determine the network mode that the mobile phone needs to switch in different interference intensity environments. All network mode switching values are compared in size, and different mobile phone network modes are sequentially corresponded in order from small to large, thereby solving the problem of unstable signal recognition of the mobile phone in areas with poor signal or signal interference. SUMMARY

[0004] The present application aims to provide a signal identification method and system for a mobile phone, a storage medium and an electronic device to solve the technical problems in the background.

[0005] The object of the present application can be achieved by the following technical solutions:

[0006] In a first aspect, the present application provides a signal identification method for a mobile phone, comprising the following steps:

[0007] Step one: Real-time acquisition of the received data obtained by the mobile phone when receiving signals, wherein the received data includes signal strength error value and signal time deviation value. The signal strength error value and the signal time deviation value are added and calculated to obtain a signal identification deviation value.

[0008] Step two: Based on the signal identification deviation value, the signal identification deviation value is compared with the signal identification deviation threshold value to generate an identification deviation signal.

[0009] The identification deviation signal includes an identification deviation large signal and an identification deviation small signal.

[0010] If the signal recognition deviation value is greater than or equal to the signal recognition deviation threshold value, a large recognition deviation signal is generated;

[0011] If the signal recognition deviation value is less than the signal recognition deviation threshold value, a small recognition deviation signal is generated;

[0012] Step three: based on the large recognition deviation signal, the signal waveform is analyzed to obtain a waveform similarity value, to determine whether it is affected by interference, and a interference recognition signal is generated;

[0013] The interference recognition signal includes a first interference recognition signal and a second interference recognition signal.

[0014] Step four: based on the second interference recognition signal, a network mode switching value is obtained to determine the network mode that the mobile phone needs to switch in different interference intensity environments.

[0015] The specific process of network mode switching is as follows:

[0016] The network mode switching value is obtained in the following manner:

[0017] Based on the actual amplitude difference value FC m , the wave peak point position deviation value FP i and the wave trough point position deviation value GP u , the actual amplitude difference value FC m , the wave peak point position deviation value FP i and the wave trough point position deviation value GP u are added to obtain the network mode switching value.

[0018] Based on the network mode switching value, all network mode switching values are compared in size, and different mobile phone network modes are sequentially corresponded in order from small to large.

[0019] As a further scheme of the present application, the signal strength deviation value is obtained in the following manner:

[0020] In the monitoring period, the monitoring period is divided into a plurality of time nodes, the signal strength value corresponding to each time node is obtained, which is marked as the measured signal strength value, the measured signal strength value is subtracted from the standard signal strength value to obtain the signal strength difference value.

[0021] All signal strength difference values are added to obtain the average value, and the average value is compared with the standard signal strength value to obtain the signal strength deviation value.

[0022] The signal time deviation value is obtained in the following manner:

[0023] In the monitoring period, the actual signal time of the mobile phone is obtained, marked as an actual signal time value, the actual signal time value is subtracted from the standard signal time value, and a signal time difference value is obtained;

[0024] All signal time difference values are added to the standard signal time value, averaged, and calculated by ratio, and a signal time deviation value is obtained.

[0025] As a further scheme of the application: the waveform similarity value is obtained in the following manner:

[0026] The actual amplitude deviation value and the actual feature point deviation value are added and summed to obtain the waveform similarity value.

[0027] As a further scheme of the application: the actual amplitude deviation value is obtained in the following manner:

[0028] Based on the actual signal waveform, an X-Y axis coordinate system is established, the X axis represents time, and the Y axis represents the waveform amplitude, the actual signal waveform is substituted into the X-Y axis coordinate system, and an actual signal waveform change curve is obtained;

[0029] Based on the actual signal waveform change curve, the actual signal waveform change curve is divided into several actual waveform change sub-curves with equal length in time period, the wave peak point coordinates and the wave valley point coordinates in each actual waveform change sub-curve are obtained, and the adjacent wave peak point coordinates and wave valley point coordinates are substituted into the formula: The actual waveform change sub-curve amplitude value Fn is calculated, wherein (X f , Y f ) represents the actual wave peak point coordinates, (X g , Y g ) represents the actual wave valley point coordinates.

[0030] All actual waveform change sub-curve amplitude values are added and averaged to obtain an actual signal amplitude value;

[0031] The actual signal amplitude value is subtracted from all interference signal amplitude values in turn, the absolute value is taken, an actual amplitude difference value is obtained, and the actual amplitude difference value FC m is marked, wherein m represents different actual amplitude difference values.

[0032] All interference signal amplitude values are added and averaged to obtain an interference signal amplitude representation value;

[0033] The actual amplitude difference value is calculated by ratio with the interference signal amplitude representation value to obtain the actual amplitude deviation value.

[0034] As a further aspect of the present invention: the actual feature point deviation value is obtained as follows:

[0035] The actual feature point deviation value is obtained by adding the peak feature deviation value and the trough feature deviation value.

[0036] As a further aspect of the present invention: the method for obtaining the peak characteristic deviation value is as follows:

[0037] Based on the interference signal waveform, an XY-axis coordinate system is established, with the X-axis representing time and the Y-axis representing the amplitude of the interference waveform. Substituting the interference signal waveform into the XY-axis coordinate system, the variation curve of the interference signal waveform is obtained.

[0038] Obtain the coordinates of the peaks and troughs within the waveform change curve of the interference signal, and mark them as the coordinates of the interference peaks. Coordinates of the interference valley point

[0039] Substitute the coordinates of the peak points on the actual waveform change curve and the waveform change curves of multiple interference signals into the formula: The peak position deviation value FP was calculated. i , among which, (SX f SY f () represents the coordinates of the peak points within the actual signal waveform curve. The coordinates of the peak points within the waveform change curve of the interference signal are represented as follows: n represents the waveform change curve of different types of interference signals, and i represents the position deviation value of different peak points.

[0040] The peak position deviation values ​​are summed and averaged to obtain the peak characteristic deviation value.

[0041] As a further aspect of the present invention: the method for obtaining the trough characteristic deviation value

[0042] Substitute the coordinates of the trough points on the actual waveform change curve and the waveform change curves of multiple interference signals into the formula: The trough point position deviation value GP was calculated. u , among which, (SX g SY g () represents the coordinates of the trough points within the actual signal waveform curve. The coordinates of the trough points within the waveform change curve of the interference signal are represented as follows: n represents the waveform change curve of different types of interference signals, and u represents the position deviation value of different trough points.

[0043] The characteristic deviation value of the trough is obtained by summing all the deviation values ​​of the trough positions and taking the average value.

[0044] Secondly, the present invention provides a signal recognition system for mobile phones, the system comprising the following modules:

[0045] Identification and monitoring module: It acquires the received data obtained by the mobile phone when receiving signals in real time. The received data includes signal strength error value and signal time deviation value. The signal strength error value and signal time deviation value are added together to calculate the signal identification deviation value.

[0046] The identification and evaluation module compares the signal identification deviation value with the signal identification deviation threshold to generate an identification deviation signal.

[0047] The identification deviation signal includes a large identification deviation signal and a small identification deviation signal;

[0048] If the signal recognition deviation value is greater than or equal to the signal recognition deviation threshold, a large recognition deviation signal is generated.

[0049] If the signal recognition deviation value is less than the signal recognition deviation threshold, a small recognition deviation signal is generated;

[0050] Interference Analysis Module: Based on the identification of signals with large deviations, the module analyzes the signal waveform, obtains waveform similarity values, determines whether it is affected by interference, and generates an interference identification signal.

[0051] The interference identification signal includes a first interference identification signal and a second interference identification signal.

[0052] Optimization and adjustment module: Based on the interference identification second signal, the network mode switching value is obtained, and the network mode that the mobile phone needs to switch to under different interference intensity environments is determined;

[0053] The specific process of switching network modes is as follows:

[0054] The method for obtaining the network mode switching value is as follows:

[0055] Based on the actual amplitude difference FC m FP, the deviation value of the peak position i Deviation value GP of the trough point position u The actual amplitude difference FC m FP, the deviation value of the peak position i Deviation value GP of the trough point position u The network mode switching value is obtained by summing the results.

[0056] Based on the network mode switching value, all network mode switching values ​​are compared and then arranged in ascending order to correspond to different mobile network modes.

[0057] Thirdly, an electronic device includes a processor that reads and executes the mobile phone software identification program to implement the above-mentioned signal identification method for mobile phones.

[0058] Fourthly, the present invention provides a storage medium in which a mobile phone software identification program is stored, and when the mobile phone software identification program is executed by a processor, it implements the above-described signal identification method for a mobile phone.

[0059] The beneficial effects of this invention are:

[0060] (1) This invention monitors the received data obtained by the mobile phone when receiving signals in real time. The received data includes signal strength deviation value and signal time deviation value. The signal recognition deviation value is calculated and compared with the signal recognition deviation threshold. If the signal recognition deviation value is greater than or equal to the signal recognition deviation threshold, a large recognition deviation signal is generated, which indicates that the mobile phone has a large deviation in signal strength and signal time when recognizing the received signal. Thus, the mobile phone's signal recognition performance is reflected from the two different dimensions of signal strength and signal reception time.

[0061] (2) When generating the second interference identification signal, the present invention acquires the actual waveform of the mobile phone identification signal through an oscilloscope, marks it as the actual signal waveform, and compares and analyzes the actual signal waveform with the interference signal waveform to obtain a waveform similarity value. The waveform similarity value is compared with the waveform similarity threshold. If the waveform similarity value is less than the waveform similarity threshold, the second interference identification signal is generated, which indicates that the amplitude deviation between the actual signal waveform and the interference signal waveform is small and the feature point deviation is small, which means that it has been affected by interference. Based on the second interference identification signal, the network mode switching value is obtained, and the network mode that the mobile phone needs to switch to under different interference intensity environments is determined. By comparing the size of all the network mode switching values, and corresponding to different mobile phone network modes in order from small to large, the problem of unstable mobile phone identification signal in areas with poor signal or signal interference is solved. Attached Figure Description

[0062] The invention will now be further described with reference to the accompanying drawings.

[0063] Figure 1 This is a flowchart of an embodiment of the method of the present invention;

[0064] Figure 2 This is a flowchart of Embodiment 2 of the method of the present invention;

[0065] Figure 3 This is a schematic diagram of the system of the present invention. Detailed Implementation

[0066] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0067] Example 1:

[0068] Please see Figure 1 As shown in the embodiment of the present invention, the signal identification method for mobile phones specifically includes the following steps:

[0069] Step 1: Monitor the received data obtained by the mobile phone when receiving signals in real time. The received data includes signal strength deviation value and signal time deviation value, and calculate the signal recognition deviation value.

[0070] In some embodiments, the received data obtained by the mobile phone when receiving a signal is acquired in real time. The received data includes a signal strength error value and a signal time deviation value. The signal strength error value and the signal time deviation value are added together to obtain a signal identification deviation value.

[0071] The first specific method for obtaining the signal strength deviation value is as follows:

[0072] Within the monitoring period, the monitoring period is divided into several time nodes. The signal strength value corresponding to each time node is obtained and marked as the measured signal strength value. The difference between the measured signal strength value and the standard signal strength value is obtained.

[0073] The signal strength deviation is obtained by summing all the signal strength differences, taking the average value, and then comparing it with the standard signal strength value.

[0074] Secondly, the specific method for obtaining the signal time deviation value is as follows:

[0075] During the monitoring period, the actual signal reception time of the mobile phone is obtained and marked as the actual signal time value. The difference between the actual signal time value and the standard signal time value is obtained to obtain the signal time difference.

[0076] The signal time deviation is obtained by summing all the signal time differences with the standard signal time value, taking the average value, and then calculating the ratio of the average value to the standard signal time.

[0077] Step 2: Based on the signal recognition deviation value, compare the signal recognition deviation value with the signal recognition deviation threshold to generate a recognition deviation signal;

[0078] Among them, the identification deviation signal includes the identification deviation large signal and the identification deviation small signal;

[0079] In some embodiments, when a signal recognition deviation value is obtained, the signal recognition deviation value is compared with a signal recognition deviation threshold. The comparison process is as follows:

[0080] If the signal recognition deviation value is greater than or equal to the signal recognition deviation threshold, it means that the mobile phone has a large deviation in signal strength and signal time when recognizing the received signal, generating a signal with large recognition deviation.

[0081] If the signal recognition deviation value is less than the signal recognition deviation threshold, it means that when the mobile phone recognizes the received signal, the deviation in signal strength and signal reception time is small, and a small recognition deviation signal is generated.

[0082] The specific implementation scheme of this invention is as follows: Real-time monitoring of the received data obtained by the mobile phone when receiving signals, wherein the received data includes signal strength deviation value and signal time deviation value, and a signal recognition deviation value is calculated. The signal recognition deviation value is compared with a signal recognition deviation threshold. If the signal recognition deviation value is greater than or equal to the signal recognition deviation threshold, a large recognition deviation signal is generated, thereby indicating that the mobile phone has a large deviation in signal strength and signal time when recognizing the received signal. Thus, the mobile phone's signal recognition performance is reflected from two different dimensions of data: signal strength and signal reception time.

[0083] Example 2

[0084] Please see Figure 3 As shown in Embodiment 1, due to interference, the signal amplitude received by the mobile phone during signal recognition may deviate significantly, and the signal reception time may be delayed. This includes co-channel interference and adjacent-channel interference. The signal recognition method for mobile phones described in this embodiment of the invention includes the following steps:

[0085] Step 3: Based on the large identification deviation signal, analyze the signal waveform to obtain waveform similarity value, determine whether it is affected by interference, and generate interference identification signal;

[0086] The interference identification signal includes a first interference identification signal and a second interference identification signal.

[0087] Specifically, it needs further explanation: The meaning of the first interference identification signal is that the actual signal waveform deviates significantly from the interference signal waveform in amplitude and the characteristic points (peaks and troughs) deviate significantly, indicating that it is not affected by interference and is caused by other reasons; The meaning of the second interference identification signal is that the actual signal waveform deviates significantly from the interference signal waveform in amplitude and the characteristic points (peaks and troughs) deviate significantly, indicating that it is affected by interference.

[0088] In some embodiments, when a signal with large identification deviation is generated, the actual waveform of the mobile phone identification signal is obtained by using an oscilloscope, marked as the actual signal waveform, and the actual signal waveform is compared and analyzed with the interference signal waveform to obtain the waveform similarity value;

[0089] The waveform similarity value is compared with the waveform similarity threshold. The comparison process is as follows:

[0090] If the waveform similarity value is greater than or equal to the waveform similarity threshold, it indicates that the actual signal waveform and the interference signal waveform have a large amplitude deviation and a large feature point deviation, thus generating the first interference identification signal.

[0091] If the waveform similarity value is less than the waveform similarity threshold, it means that the amplitude deviation between the actual signal waveform and the interference signal waveform is small, and the feature point deviation is small, thus generating a second interference identification signal.

[0092] It should be explained that the waveform similarity value is a comprehensive measure that assesses the degree of similarity between the actual signal waveform and the interference signal waveform (or the standard signal waveform, depending on the purpose of the analysis). It combines information on the amplitude deviation of the signal waveform and the positional deviation of characteristic points (peaks and troughs) through a series of calculation steps to obtain a single value that reflects the similarity or difference between the waveforms.

[0093] Specifically, the smaller the waveform similarity value, the higher the similarity between the actual signal waveform and the interference signal waveform, meaning that the amplitude deviation and feature point position deviation are both small. This usually means that the signal may have been affected by interference. Conversely, the larger the waveform similarity value, the lower the similarity between the actual signal waveform and the interference signal waveform, meaning that the amplitude deviation and feature point position deviation are both large. This usually means that the signal may not have been affected by interference.

[0094] For example, the process of obtaining waveform similarity values ​​is as follows:

[0095] Based on the actual signal waveform, an XY-axis coordinate system is established, with the X-axis representing time and the Y-axis representing waveform amplitude. The actual signal waveform is then substituted into the XY-axis coordinate system to obtain the actual signal waveform change curve.

[0096] Based on the actual signal waveform change curve, the actual signal waveform change curve is divided into several equal-length sub-curves in a time interval manner. The coordinates of the peak points and trough points in each sub-curve are obtained, and the coordinates of adjacent peak points and trough points are substituted into the formula: The actual waveform change sub-curve amplitude value Fn is calculated, where (X f Y f (X) represents the actual peak coordinates.g Y g () represents the actual coordinates of the trough point;

[0097] The actual signal amplitude value is obtained by summing the amplitude values ​​of all the actual waveform change sub-curves and taking the average value.

[0098] The actual signal amplitude value is successively subtracted from the amplitude values ​​of all interfering signals, and the absolute value is taken to obtain the actual amplitude difference value, which is denoted as the actual amplitude difference value FC. m Where m represents the different actual amplitude differences, such as FC1, FC2, FC3, ..., FC m ;

[0099] The amplitude values ​​of all the interference signals are summed and averaged to obtain the amplitude characterization value of the interference signal.

[0100] The actual amplitude deviation value is obtained by calculating the ratio of the actual amplitude difference to the amplitude representation value of the interference signal.

[0101] Based on the interference signal waveform, an XY-axis coordinate system is established, with the X-axis representing time and the Y-axis representing the amplitude of the interference waveform. Substituting the interference signal waveform into the XY-axis coordinate system, the variation curve of the interference signal waveform is obtained.

[0102] Obtain the coordinates of the peaks and troughs within the waveform change curve of the interference signal, and mark them as the coordinates of the interference peaks. Coordinates of the interference valley point

[0103] Substitute the coordinates of the peak points on the actual waveform change curve and the waveform change curves of multiple interference signals into the formula: The peak position deviation value FP was calculated. i , among which, (SX f SY f () represents the coordinates of the peak points within the actual signal waveform curve. This represents the coordinates of the peak points within the waveform variation curve of the interference signal, where n represents the waveform variation curve of different types of interference signals, and i represents the different peak point position deviation values. For example, the peak point position deviation values ​​can be FP1, FP2, FP3...FP i ;

[0104] Substitute the coordinates of the trough points on the actual waveform change curve and the waveform change curves of multiple interference signals into the formula: The trough point position deviation value GP was calculated. u , among which, (SX g SY g() represents the coordinates of the trough points within the actual signal waveform curve. This represents the coordinates of the trough points within the waveform variation curve of the interference signal, where n represents the waveform variation curve of different types of interference signals, and u represents the different trough point position deviation values. For example, the trough point position deviation values ​​can be GP1, GP2, GP3, ..., GP... u ;

[0105] The peak position deviation values ​​are summed and averaged to obtain the peak characteristic deviation value.

[0106] The characteristic deviation value of the trough is obtained by summing all the deviation values ​​of the trough positions and taking the average value.

[0107] The peak feature deviation value is added to the trough feature deviation value to obtain the actual feature point deviation value;

[0108] Obtain the actual amplitude deviation value and the actual feature point deviation value, and sum the actual amplitude deviation value and the actual feature point deviation value to obtain the waveform similarity value;

[0109] It needs to be further explained that the interference signal waveform is generated in a laboratory or simulation environment by using mathematical models or simulation software based on known interference source characteristics and system parameters.

[0110] Step 4: Based on the interference identification second signal, obtain the network mode switching value and determine the network mode that the mobile phone needs to switch to under different interference intensity environments;

[0111] In some embodiments, when generating the interference identification second signal, a network switching value is obtained, and the network mode under different interference intensity environments is determined based on the network switching value.

[0112] For example, the network mode switching value is obtained as follows:

[0113] Based on the actual amplitude difference FC m FP, the deviation value of the peak position i Deviation value GP of the trough point position u The actual amplitude difference FC m FP, the deviation value of the peak position i Deviation value GP of the trough point position u The network mode switching value is obtained by summing the results.

[0114] Based on the network mode switching value, all network mode switching values ​​are compared and then arranged in ascending order to correspond to different mobile network modes.

[0115] The specific implementation scheme of this invention is as follows: When the second interference identification signal is generated, the actual waveform of the mobile phone identification signal is obtained through an oscilloscope and marked as the actual signal waveform. The actual signal waveform is compared and analyzed with the interference signal waveform to obtain a waveform similarity value. The waveform similarity value is compared with a waveform similarity threshold. If the waveform similarity value is less than the waveform similarity threshold, the second interference identification signal is generated, which indicates that the amplitude deviation and feature point deviation between the actual signal waveform and the interference signal waveform are small, meaning that it has been affected by interference. Based on the second interference identification signal, the network mode switching value is obtained to determine the network mode that the mobile phone needs to switch to under different interference intensity environments. By comparing the magnitudes of all network mode switching values, and in ascending order, they correspond to different mobile phone network modes, thereby solving the problem of unstable mobile phone identification signals in areas with poor signal or signal interference.

[0116] It should be noted that the standard values ​​or thresholds mentioned above are all derived by those skilled in the art through a large amount of experimental data, and are empirical values.

[0117] Example 3:

[0118] Based on Examples 1 and 2, please refer to Figure 3 As shown in the embodiment of the present invention, the mobile phone signal recognition system includes the following modules:

[0119] Identification and monitoring module: It acquires the received data obtained by the mobile phone when receiving signals in real time. The received data includes signal strength error value and signal time deviation value. The signal strength error value and signal time deviation value are added together to calculate the signal identification deviation value.

[0120] The identification and evaluation module compares the signal identification deviation value with the signal identification deviation threshold to generate an identification deviation signal.

[0121] The identification deviation signal includes a large identification deviation signal and a small identification deviation signal;

[0122] If the signal recognition deviation value is greater than or equal to the signal recognition deviation threshold, a large recognition deviation signal is generated.

[0123] If the signal recognition deviation value is less than the signal recognition deviation threshold, a small recognition deviation signal is generated;

[0124] Interference Analysis Module: Based on the identification of signals with large deviations, the module analyzes the signal waveform, obtains waveform similarity values, determines whether it is affected by interference, and generates an interference identification signal.

[0125] The interference identification signal includes a first interference identification signal and a second interference identification signal.

[0126] Optimization and adjustment module: Based on the interference identification second signal, the network mode switching value is obtained, and the network mode that the mobile phone needs to switch to under different interference intensity environments is determined.

[0127] Example 4:

[0128] Based on Embodiments 1, 2, and 3, the storage medium described in this embodiment of the invention includes a processor that reads and executes the mobile phone software identification program, thereby realizing any of the above-mentioned signal identification methods for mobile phones.

[0129] Example 5:

[0130] Based on Embodiments 1, 2, 3, and 4, the mobile phone signal recognition electronic device described in this embodiment of the invention includes a mobile phone software recognition program in the storage medium, which, when executed by a processor, implements the above-described signal recognition method for mobile phones.

[0131] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A signal identification method for mobile phones, characterized in that, Includes the following steps: Step 1: Acquire the received data obtained by the mobile phone when receiving signals in real time. The received data includes signal strength error value and signal time deviation value. Add the signal strength error value and signal time deviation value together to calculate the signal identification deviation value. Step 2: Based on the signal recognition deviation value, compare the signal recognition deviation value with the signal recognition deviation threshold to generate a recognition deviation signal; The identification deviation signal includes a large identification deviation signal and a small identification deviation signal; If the signal recognition deviation value is greater than or equal to the signal recognition deviation threshold, a large recognition deviation signal is generated. If the signal recognition deviation value is less than the signal recognition deviation threshold, a small recognition deviation signal is generated; Step 3: Based on the large identification deviation signal, analyze the signal waveform to obtain waveform similarity value, determine whether it is affected by interference, and generate interference identification signal; The interference identification signal includes a first interference identification signal and a second interference identification signal. The meaning of the first interference identification signal is: the actual signal waveform deviates significantly from the interference signal waveform in terms of amplitude, peak point or trough point, indicating that it is not affected by interference and is caused by other reasons; the meaning of the second interference identification signal is: the actual signal waveform deviates significantly from the interference signal waveform in terms of amplitude, peak point or trough point, indicating that it is affected by interference. Step 4: Based on the interference identification second signal, obtain the network mode switching value and determine the network mode that the mobile phone needs to switch to under different interference intensity environments; The specific process of switching network modes is as follows: The method for obtaining the network mode switching value is as follows: Based on the actual amplitude difference Peak position deviation value Deviation value of the trough point position The actual amplitude difference Peak position deviation value Deviation value of the trough point position The network mode switching value is obtained by summing the results. Based on the network mode switching value, all network mode switching values ​​are compared and then arranged in ascending order to correspond to different mobile network modes.

2. The signal identification method for mobile phones according to claim 1, characterized in that, The signal strength deviation value is obtained as follows: Within the monitoring period, the monitoring period is divided into several time nodes. The signal strength value corresponding to each time node is obtained and marked as the measured signal strength value. The difference between the measured signal strength value and the standard signal strength value is obtained. The signal strength deviation is obtained by summing all the signal strength differences, taking the average value, and then comparing it with the standard signal strength value. The method for obtaining the signal time deviation value is as follows: During the monitoring period, the actual signal reception time of the mobile phone is obtained and marked as the actual signal time value. The difference between the actual signal time value and the standard signal time value is obtained to obtain the signal time difference. The signal time deviation is obtained by summing all the signal time differences with the standard signal time value, taking the average value, and then calculating the ratio of the average value to the standard signal time.

3. The signal recognition method for mobile phones according to claim 1, characterized in that, The waveform similarity value is obtained as follows: Obtain the actual amplitude deviation value and the actual feature point deviation value, and sum the actual amplitude deviation value and the actual feature point deviation value to obtain the waveform similarity value.

4. The signal identification method for mobile phones according to claim 3, characterized in that, The actual amplitude deviation value is obtained as follows: Based on the actual signal waveform, an XY-axis coordinate system is established, with the X-axis representing time and the Y-axis representing waveform amplitude. The actual signal waveform is then substituted into the XY-axis coordinate system to obtain the actual signal waveform change curve. Based on the actual signal waveform change curve, the actual signal waveform change curve is divided into several equal-length actual waveform change sub-curves in the form of time intervals. The coordinates of the peak points and trough points in each actual waveform change sub-curve are obtained, and the coordinates of adjacent peak points and trough points are substituted into the formula: The amplitude value of the actual waveform change sub-curve is calculated. ,in,( , ) represents the actual peak coordinates, ( , () represents the actual coordinates of the trough point; The actual signal amplitude value is obtained by summing the amplitude values ​​of all the actual waveform change sub-curves and taking the average value. The actual signal amplitude value is obtained by successively subtracting the amplitude values ​​of all interfering signals, taking the absolute value, and marking it as the actual amplitude difference. , where m represents the difference in actual amplitude; The amplitude values ​​of all the interference signals are summed and averaged to obtain the amplitude characterization value of the interference signal. The actual amplitude deviation value is obtained by calculating the ratio of the actual amplitude difference to the amplitude representation value of the interference signal.

5. The signal identification method for mobile phones according to claim 3, characterized in that, The method for obtaining the actual feature point deviation value is as follows: The actual feature point deviation value is obtained by adding the peak feature deviation value and the trough feature deviation value.

6. The signal identification method for mobile phones according to claim 5, characterized in that, The method for obtaining the peak characteristic deviation value is as follows: Based on the interference signal waveform, an XY-axis coordinate system is established, with the X-axis representing time and the Y-axis representing the amplitude of the interference waveform. Substituting the interference signal waveform into the XY-axis coordinate system, the variation curve of the interference signal waveform is obtained. Obtain the coordinates of the peaks and troughs within the waveform change curve of the interference signal, and mark them as the coordinates of the interference peaks. , Coordinates of the interference trough point ( , ); Substitute the coordinates of the peak points on the actual waveform change curve and the waveform change curves of multiple interference signals into the formula: The deviation value of the wave crest position is calculated. ,in,( , ) represents the coordinates of the peak points within the actual signal waveform curve. , ) represents the coordinates of the peak points within the waveform change curve of the interference signal, where n represents the waveform change curve of different types of interference signals, and i represents the different peak point position deviation values; The peak position deviation values ​​are summed and averaged to obtain the peak characteristic deviation value.

7. The signal identification method for mobile phones according to claim 5, characterized in that, The method for obtaining the trough characteristic deviation value Substitute the coordinates of the trough points on the actual waveform change curve and the waveform change curves of multiple interference signals into the formula: The deviation value of the trough point position is calculated. ,in,( , ) represents the coordinates of the trough points within the actual signal waveform curve. ) represents the coordinates of the trough points within the waveform change curve of the interference signal, where n represents the waveform change curve of different types of interference signals, and u represents the position deviation value of different trough points; The characteristic deviation value of the trough is obtained by summing all the deviation values ​​of the trough positions and taking the average value.

8. A signal recognition system for mobile phones, characterized in that, The system performs the signal recognition method according to any one of claims 1-7, and the system includes the following modules: Identification and monitoring module: It acquires the received data obtained by the mobile phone when receiving signals in real time. The received data includes signal strength error value and signal time deviation value. The signal strength error value and signal time deviation value are added together to calculate the signal identification deviation value. The identification and evaluation module compares the signal identification deviation value with the signal identification deviation threshold to generate an identification deviation signal. The identification deviation signal includes a large identification deviation signal and a small identification deviation signal; If the signal recognition deviation value is greater than or equal to the signal recognition deviation threshold, a large recognition deviation signal is generated. If the signal recognition deviation value is less than the signal recognition deviation threshold, a small recognition deviation signal is generated; Interference Analysis Module: Based on the identification of signals with large deviations, the module analyzes the signal waveform, obtains waveform similarity values, determines whether it is affected by interference, and generates an interference identification signal. The interference identification signal includes a first interference identification signal and a second interference identification signal. The meaning of the first interference identification signal is: the actual signal waveform deviates significantly from the interference signal waveform in terms of amplitude, peak point or trough point, indicating that it is not affected by interference and is caused by other reasons; the meaning of the second interference identification signal is: the actual signal waveform deviates significantly from the interference signal waveform in terms of amplitude, peak point or trough point, indicating that it is affected by interference. Optimization and adjustment module: Based on the interference identification second signal, the network mode switching value is obtained, and the network mode that the mobile phone needs to switch to under different interference intensity environments is determined.

9. An electronic device, characterized in that, The device includes a processor that reads and executes a mobile phone software identification program to implement the signal identification method described in any one of claims 1-7.

10. A storage medium, characterized in that, The mobile phone software identification program in the storage medium implements the signal identification method according to any one of claims 1-7 when executed by the processor.

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