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

Abstract

The invention 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 electronic equipment, receiving data obtained when the mobile phone receives a signal is monitored in real time, and the receiving data comprises a signal strength deviation value and a signal time deviation value; a signal identification deviation value is obtained through calculation, the signal identification deviation value is compared with a signal identification deviation threshold value, and if the signal identification deviation value is larger than or equal to the signal identification deviation threshold value, a signal with large identification deviation is generated, so that when the mobile phone identifies the received signal, the identification signal strength and the signal time deviation are large. And the mobile phone identification signal performance is reflected from data of two different dimensions of signal intensity and signal receiving time.

Description

Technical Field

[0001] The present invention relates to the technical field of communication signal processing, and in particular to a signal recognition method, system, storage medium and electronic device for mobile phones. Background Art

[0002] Communication technology is the basis for mobile phone signal recognition. Mobile phones are connected to base stations through wireless communication technology to achieve data transmission and reception. When a mobile phone processes the received wireless signal through a built-in signal processor, it can identify the current connected network type and adjust communication parameters and strategies according to the network type to optimize communication performance. However, since the environment where the mobile phone is located will interfere with the recognition of the current connected network type by the mobile phone, it is necessary to solve this problem.

[0003] Obtain the actual waveform of the mobile phone recognition signal through an oscilloscope, compare and analyze the actual signal waveform with the interference signal waveform to obtain a waveform similarity value, compare the waveform similarity value with the waveform similarity threshold. If the waveform similarity value is less than the waveform similarity threshold, generate a second interference recognition signal, 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 is affected by interference. Based on the second interference recognition signal, obtain a network mode switching value, determine the network mode that the mobile phone needs to switch in different interference intensity environments, compare the sizes of all network mode switching values, and correspond to different mobile phone network modes in ascending order, thus solving the problem of unstable mobile phone recognition signals in areas with poor signals or signal interference. Summary of the Invention

[0004] The purpose of the present invention is to provide a signal recognition method, system, storage medium and electronic device for mobile phones to solve the technical problems in the above background.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] In a first aspect, the present invention provides a signal recognition method for mobile phones, including the following steps:

[0007] Step 1: Real-time obtain the received data obtained by the mobile phone when receiving a signal. Among them, the received data includes a signal strength error value and a signal time deviation value, add and sum the signal strength error value and the signal time deviation value to calculate a signal recognition deviation value;

[0008] Step 2: Based on the signal recognition deviation value, compare the signal recognition deviation value with a signal recognition deviation threshold to generate a recognition deviation signal;

[0009] The recognition deviation signal includes a large recognition deviation signal and a small recognition deviation signal;

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

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

[0012] Step 3: Based on the large signal with recognition deviation, analyze the signal waveform to obtain a waveform similarity value, determine whether it is affected by interference, and generate an interference recognition signal;

[0013] Among them, the interference recognition signal includes an interference recognition first signal and an interference recognition second signal;

[0014] Step 4: Based on the interference recognition second signal, obtain a network mode switching value, and determine the network mode that the mobile phone needs to switch to under different interference intensity environments;

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

[0016] The acquisition method of the network mode switching value is:

[0017] Based on the actual amplitude difference FC m 、the peak point position deviation value FP i and the trough point position deviation value GP u , add the actual amplitude difference FC m 、the peak point position deviation value FP i and the trough point position deviation value GP u to sum them up to obtain the network mode switching value;

[0018] Based on the network mode switching value, compare the sizes of all network mode switching values, and correspond to different mobile phone network modes in ascending order.

[0019] As a further solution of the present invention: The acquisition method of the signal strength deviation value is:

[0020] During the monitoring period, divide the monitoring period into several time nodes, obtain the signal strength value corresponding to each time node, mark it as the measured signal strength value, subtract the standard signal strength value from the measured signal strength value to obtain the signal strength difference;

[0021] Sum up all the signal strength differences and take the average value, and calculate the ratio with the standard signal strength value to obtain the signal strength deviation value;

[0022] The acquisition method of the signal time deviation value is:

[0023] During the monitoring period, obtain the actual signal reception time of the mobile phone, mark it as the actual signal time value, subtract the actual signal time value from the standard signal time value to obtain the signal time difference;

[0024] Add up all the signal time differences and the standard signal time value, take the average value, and calculate the ratio with the standard signal time to obtain the signal time deviation value.

[0025] As a further solution of the present invention: the method for obtaining the waveform similarity value is as follows:

[0026] Obtain the actual amplitude deviation value and the actual characteristic point deviation value, add up the actual amplitude deviation value and the actual characteristic point deviation value to obtain the waveform similarity value.

[0027] As a further solution of the present invention: the method for obtaining the actual amplitude deviation value is as follows:

[0028] Based on the actual signal waveform, establish an X-Y axis coordinate system, where the X axis represents time and the Y axis represents waveform amplitude. Substitute the actual signal waveform into the X-Y axis coordinate system to obtain the actual signal waveform change curve;

[0029] Based on the actual signal waveform change curve, divide the actual signal waveform change curve into several actual waveform change sub-curves of equal length in terms of time period, obtain the peak point coordinates and valley point coordinates within each actual waveform change sub-curve, and substitute the adjacent peak point coordinates and valley point coordinates into the formula: Calculate to obtain the actual waveform change sub-curve amplitude value Fn, where (X f , Y f ) represents the actual peak point coordinates, and (X g , Y g ) represents the actual valley point coordinates;

[0030] Add up all the actual waveform change sub-curve amplitude values and take the average value to obtain the actual signal amplitude value;

[0031] Subtract the actual signal amplitude value from all the interference signal amplitude values in turn, take the absolute value to obtain the actual amplitude difference, and mark it as the actual amplitude difference FC m , where m represents different actual amplitude differences;

[0032] Add up all the interference signal amplitude values and take the average value to obtain the interference signal amplitude characterization value;

[0033] Calculate the ratio of the actual amplitude difference to the interference signal amplitude characterization value to obtain the actual amplitude deviation value.

[0034] As a further solution of the present invention: the method for obtaining the actual feature point deviation value is as follows:

[0035] Add the peak feature deviation value and the trough feature deviation value to obtain the actual feature point deviation value.

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

[0037] Based on the interference signal waveform, establish an X-Y axis coordinate system, where the X axis represents time and the Y axis represents the interference waveform amplitude. Substitute the interference signal waveform into the X-Y axis coordinate system to obtain the interference signal waveform change curve;

[0038] Obtain the peak point coordinates and trough point coordinates in the interference signal waveform change curve, and mark them as the interference peak point coordinates interference trough point coordinates

[0039] Substitute the peak point coordinates on the actual waveform change curve and multiple interference signal waveform change curves into the formula: Calculate to obtain the peak point position deviation value FP i , where, (SX f , SY f ) represents the peak point coordinates in the actual signal waveform change curve, represents the peak point coordinates in the interference signal waveform change curve, where n represents different types of interference signal waveform change curves, and i represents different peak point position deviation values;

[0040] Add up all the peak point position deviation values, sum them up, and take the average to obtain the peak feature deviation value.

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

[0042] Substitute the trough point coordinates on the actual waveform change curve and multiple interference signal waveform change curves into the formula: Calculate to obtain the trough point position deviation value GP u , where, (SX g , SY g ) represents the trough point coordinates in the actual signal waveform change curve, represents the trough point coordinates in the interference signal waveform change curve, where n represents different types of interference signal waveform change curves, and u represents different trough point position deviation values;

[0043] Add up all the trough point position deviation values, sum them up, and take the average to obtain the trough feature deviation value,

[0044] Second aspect, the present invention provides a signal recognition system for a mobile phone, and the system includes the following modules:

[0045] Recognition and monitoring module: Obtain in real time the received data obtained by the mobile phone when receiving signals. Among them, the received data includes a signal strength error value and a signal time deviation value, add the signal strength error value and the signal time deviation value to calculate the sum, and obtain a signal recognition deviation value;

[0046] Recognition and evaluation module: Based on the signal recognition deviation value, compare the signal recognition deviation value with a signal recognition deviation threshold to generate a recognition deviation signal;

[0047] The recognition deviation signal includes a large recognition deviation signal and a small recognition 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 large recognition deviation signal, analyze the signal waveform to obtain a waveform similarity value, determine whether it is affected by interference, and generate an interference recognition signal;

[0051] Among them, the interference recognition signal includes a first interference recognition signal and a second interference recognition signal;

[0052] Optimization and adjustment module: Based on the second interference recognition signal, obtain a network mode switching value, and determine the network mode that the mobile phone needs to switch to in different interference intensity environments;

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

[0054] The obtaining method of the network mode switching value is:

[0055] Based on the actual amplitude difference FC m 、the peak point position deviation value FP i and the trough point position deviation value GP u , add the actual amplitude difference FC m 、the peak point position deviation value FP i and the trough point position deviation value GP u to calculate the sum to obtain the network mode switching value;

[0056] Based on the network mode switching value, compare the sizes of all the network mode switching values, and correspond to different mobile phone network modes in ascending order.

[0057] In a third aspect, an electronic device includes a processor that reads and executes the mobile phone software recognition program, thereby implementing the above-mentioned signal recognition method for mobile phones.

[0058] In a fourth aspect, the present invention provides a storage medium storing a mobile phone software recognition program, which, when executed by a processor, implements the above-mentioned signal recognition method for mobile phones.

[0059] Advantages of the present invention:

[0060] (1) By continuously monitoring the received data obtained when the mobile phone receives a signal, where the received data includes a signal strength deviation value and a signal time deviation value, and calculating a signal recognition deviation value, and comparing the signal recognition deviation value 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, indicating that when the mobile phone recognizes the received signal, the recognized signal strength and signal time deviation are relatively large. Thus, the signal recognition performance of the mobile phone is reflected from two different dimensions of signal strength and signal reception time.

[0061] (2) When the interference recognition second signal is generated, the actual waveform of the mobile phone recognition signal is obtained through an oscilloscope, marked as the actual signal waveform, 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. If the waveform similarity value is less than the waveform similarity threshold, an interference recognition second signal is generated, indicating that the amplitude deviation and feature point deviation between the actual signal waveform and the interference signal waveform are relatively small, meaning it is affected by interference. Based on the interference recognition second signal, a network mode switching value is obtained, and the network mode that the mobile phone needs to switch to in different interference intensity environments is determined. By comparing the sizes of all network mode switching values and corresponding them to different mobile phone network modes in ascending order, the problem of unstable signal recognition of the mobile phone in areas with poor signals or signal interference is solved. Description of the Drawings

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

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

[0064] Figure 2 is a flowchart of the second embodiment of the method of the present invention;

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

[0066] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts belong to the scope of protection of the present invention.

[0067] Embodiment 1:

[0068] Please refer to Figure 1 As shown in the figure, the signal recognition method for a mobile phone according to the embodiment of the present invention specifically includes the following steps:

[0069] Step 1: Real-time monitor the received data obtained when the mobile phone receives a signal. The received data includes a signal strength deviation value and a signal time deviation value, and calculate a signal recognition deviation value;

[0070] In some embodiments, the received data obtained when the mobile phone receives a signal is obtained 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 and summed to calculate a signal recognition deviation value;

[0071] Specifically, the acquisition method of the signal strength deviation value is as follows:

[0072] During the monitoring period, the monitoring period is divided into several time nodes, and the signal strength value corresponding to each time node is obtained and marked as the measured signal strength value. The measured signal strength value is subtracted from the standard signal strength value to obtain a signal strength difference value;

[0073] All the signal strength difference values are added and summed and averaged, and a ratio calculation is performed with the standard signal strength value to obtain a signal strength deviation value;

[0074] Specifically, the acquisition method of 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 actual signal time value is subtracted from the standard signal time value to obtain a signal time difference value;

[0076] All the signal time difference values are added and summed and averaged, and a ratio calculation is performed with the standard signal time to obtain a signal time deviation value;

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

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

[0079] In some embodiments, when the signal recognition deviation value is obtained, the signal recognition deviation value is compared with the signal recognition deviation threshold, and 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 indicates that when the mobile phone recognizes the received signal, the recognition signal strength and the signal time deviation are large, and a large recognition deviation signal is generated;

[0081] If the signal recognition deviation value is less than the signal recognition deviation threshold, it indicates that when the mobile phone recognizes the received signal, the recognition signal strength and the received signal time deviation are small, and a small recognition deviation signal is generated;

[0082] The specific implementation of the embodiment of the present invention is as follows: The received data obtained when the mobile phone receives the signal is monitored in real time. Among them, the received data includes the signal strength deviation value and the signal time deviation value, and 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, indicating that when the mobile phone recognizes the received signal, the recognition signal strength and the signal time deviation are large, and thus the signal recognition performance of the mobile phone is reflected from the data in two different dimensions of signal strength and signal reception time;

[0083] Embodiment 2

[0084] Please refer to Figure 3 As shown, on the basis of Embodiment 1, due to interference, there are situations where the amplitude deviation of the signal received by the mobile phone is large and the signal reception time of the mobile phone is delayed during the signal recognition process. Among them, it includes co-channel interference, adjacent-channel interference, etc. The signal recognition method for mobile phones described in the embodiment of the present invention includes the following steps:

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

[0086] Among them, the interference recognition signal includes an interference recognition first signal and an interference recognition second signal;

[0087] Specifically, it needs to be further explained that: The meaning represented by the interference recognition first signal is that the amplitude deviation between the actual signal waveform and the interference signal waveform is large, and the characteristic points (peak points, valley points) deviate greatly, indicating that it is not affected by interference and is caused by other reasons; The meaning represented by the interference recognition second signal is that the amplitude deviation between the actual signal waveform and the interference signal waveform is small, and the characteristic points (peak points, valley points) deviate slightly, indicating that it is affected by interference;

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

[0089] The waveform similarity value is compared with the waveform similarity threshold, and 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 amplitude deviation between the actual signal waveform and the interference signal waveform is large, and the feature point deviation is large, and a first interference recognition signal is generated;

[0091] If the waveform similarity value is less than the waveform similarity threshold, it indicates that the amplitude deviation between the actual signal waveform and the interference signal waveform is small, and the feature point deviation is small, and a second interference recognition signal is generated;

[0092] It should be explained that: the meaning represented by the waveform similarity value is: the waveform similarity value is a comprehensive measure that evaluates the similarity between the actual signal waveform and the interference signal waveform (or the standard signal waveform, depending on the analysis purpose). It combines the amplitude deviation of the signal waveform and the position deviation of the feature points (peak points, valley points), and obtains a single value through a series of calculation steps to reflect 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, that is, the amplitude deviation and the feature point position deviation are both small, which usually means that the signal may be affected by interference; on the contrary, the larger the waveform similarity value, the lower the similarity between the actual signal waveform and the interference signal waveform, that is, the amplitude deviation and the feature position deviation are both large, which usually means that the signal may not be affected by interference;

[0094] Exemplarily, the process of obtaining the waveform similarity value is as follows:

[0095] Based on the actual signal waveform, an X-Y axis coordinate system is established, the X axis represents time, and the Y axis represents waveform amplitude. The actual signal waveform is substituted into the X-Y 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 actual waveform change sub-curves in terms of time period, and the peak point coordinates and valley point coordinates within each actual waveform change sub-curve are obtained. The adjacent peak point coordinates and valley point coordinates are substituted into the formula: Calculate to obtain the actual waveform change sub-curve amplitude value Fn, where, (X f , Y f ) represents the actual peak point coordinates, (Xg , Y g ) is expressed as the actual wave trough point coordinates;

[0097] Sum up all the amplitude values of the actual waveform change sub-curves and take the average to obtain the actual signal amplitude value;

[0098] Subtract the actual signal amplitude value from all the interference signal amplitude values in sequence, take the absolute value to obtain the actual amplitude difference, and mark it as the actual amplitude difference FC m , where m represents different actual amplitude differences, for example: FC1, FC2, FC3,.......FC m ;

[0099] Sum up all the interference signal amplitude values and take the average to obtain the interference signal amplitude characterization value;

[0100] Calculate the ratio of the actual amplitude difference to the interference signal amplitude characterization value to obtain the actual amplitude deviation value;

[0101] Based on the interference signal waveform, establish an X-Y axis coordinate system, the X axis represents time, the Y axis represents the interference waveform amplitude, substitute the interference signal waveform into the X-Y axis coordinate system to obtain the interference signal waveform change curve;

[0102] Obtain the peak point coordinates and trough point coordinates in the interference signal waveform change curve, and mark them as the interference peak point coordinates interference trough point coordinates

[0103] Substitute the peak point coordinates on the actual waveform change curve and multiple interference signal waveform change curves into the formula: Calculate to obtain the peak point position deviation value FP i , where, (SX f , SY f ) is expressed as the peak point coordinates in the actual signal waveform change curve, is expressed as the peak point coordinates in the interference signal waveform change curve, where n represents different types of interference signal waveform change curves, i represents different peak point position deviation values, for example, the peak point position deviation values can be FP1, FP2, FP3.......FP i ;

[0104] Substitute the trough point coordinates on the actual waveform change curve and multiple interference signal waveform change curves into the formula: Calculate to obtain the trough point position deviation value GP u , where, (SX g , SY g) represented as the coordinates of the trough points within the actual signal waveform change curve, represented as the coordinates of the trough points within the interference signal waveform change curve, where n represents different types of interference signal waveform change curves, and u represents different trough point position deviation values. For example, the trough point position deviation values can be GP1, GP2, GP3.......GP u ;

[0105] Sum up all the peak point position deviation values and take the average to obtain the peak feature deviation value;

[0106] Sum up all the trough point position deviation values and take the average to obtain the trough feature deviation value;

[0107] Add the peak feature deviation value and 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, sum up the actual amplitude deviation value and the actual feature point deviation value to obtain the waveform similarity value;

[0109] It should be further explained that: the interference signal waveform is generated by using a mathematical model or simulation software to simulate the interference signal waveform in a laboratory or simulation environment based on the known characteristics of the interference source and system parameters;

[0110] Step Four: Based on the interference recognition 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 recognition second signal, obtain the network switching value, and based on the network switching value, determine the network mode under different interference intensity environments;

[0112] Exemplarily, the method for obtaining the network mode switching value is:

[0113] Based on the actual amplitude difference FC m , peak point position deviation value FP i and trough point position deviation value GP u , add up the actual amplitude difference FC m , peak point position deviation value FP i and trough point position deviation value GP u to sum up and obtain the network mode switching value;

[0114] Based on the network mode switching value, compare the sizes of all the network mode switching values and sequentially correspond to different mobile phone network modes in ascending order;

[0115] The specific implementation of the embodiment of the present invention is as follows: When generating the second interference recognition signal, the actual waveform of the mobile phone recognition signal is obtained through an oscilloscope, marked as the actual signal waveform, 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 the waveform similarity threshold. If the waveform similarity value is less than the waveform similarity threshold, the second interference recognition signal is generated, indicating that the amplitude deviation between the actual signal waveform and the interference signal waveform is small, and the feature point deviation is small, meaning that it is affected by interference. Based on the second interference recognition signal, a 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 sizes of all network mode switching values and corresponding to different mobile phone network modes in ascending order, the problem of unstable mobile phone recognition signals in areas with poor signals or signal interference is solved;

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

[0117] Embodiment Three:

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

[0119] Recognition monitoring module: Real-time obtain the received data obtained by the mobile phone when receiving signals. Among them, the received data includes a signal strength error value and a signal time deviation value, and the signal strength error value and the signal time deviation value are added and summed to obtain a signal recognition deviation value;

[0120] Recognition evaluation module: 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;

[0121] The recognition deviation signal includes a large recognition deviation signal and a small recognition 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 large recognition deviation signal, analyze the signal waveform to obtain a waveform similarity value, determine whether it is affected by interference, and generate an interference recognition signal;

[0125] Among them, the interference recognition signal includes a first interference recognition signal and a second interference recognition signal;

[0126] Optimization and adjustment module: Based on the interference recognition second signal, obtain the network mode switching value, and determine the network mode that the mobile phone needs to switch to in different interference intensity environments.

[0127] Embodiment 4:

[0128] Based on Embodiment 1, Embodiment 2, and Embodiment 3, a storage medium according to an embodiment of the present invention includes a processor that reads and executes the mobile phone software recognition program, thereby implementing any of the above signal recognition methods for mobile phones.

[0129] Embodiment 5:

[0130] Based on Embodiment 1, Embodiment 2, Embodiment 3, and Embodiment 4, a signal recognition electronic device for a mobile phone according to an embodiment of the present invention, the mobile phone software recognition program in the storage medium, and the mobile phone software recognition program implements the above signal recognition method for a mobile phone when executed by a processor.

[0131] The above has described in detail an embodiment of the present invention, but the content described is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. Any equivalent changes and improvements made within the scope of the application of the present invention should still fall within the scope covered by the patent of the present invention.

Claims

1. A signal recognition method for mobile phones, characterized in that, It includes the following steps: Step 1: Real-time obtain the received data obtained by the mobile phone when receiving signals. The received data includes a signal strength error value and a signal time deviation value. Add the signal strength error value and the signal time deviation value to calculate the sum, and obtain a signal recognition deviation value; Step 2: Based on the signal recognition deviation value, compare the signal recognition deviation value with a signal recognition deviation threshold to generate a recognition deviation signal; The recognition deviation signal includes a large recognition deviation signal and a small recognition deviation signal; If the signal recognition deviation value is greater than or equal to the signal recognition deviation threshold, generate a large recognition deviation signal; If the signal recognition deviation value is less than the signal recognition deviation threshold, generate a small recognition deviation signal; Step 3: Based on the large recognition deviation signal, analyze the signal waveform to obtain a waveform similarity value, determine whether it is affected by interference, and generate an interference recognition signal; Among them, the interference recognition signal includes a first interference recognition signal and a second interference recognition signal; Step 4: Based on the second interference recognition signal, obtain a network mode switching value, and determine the network mode that the mobile phone needs to switch to in different interference intensity environments; The specific process of network mode switching is as follows: The acquisition method of the network mode switching value is: Based on the actual amplitude difference FC m , the peak point position deviation value FP i and the trough point position deviation value GP u , add the actual amplitude difference FC m , the peak point position deviation value FP i and the trough point position deviation value GP u to sum them up to obtain the network mode switching value; Based on the network mode switching value, compare the sizes of all network mode switching values, and correspond to different mobile phone network modes in ascending order.

2. The signal recognition method for a mobile phone according to claim 1, wherein, The acquisition method of the signal strength deviation value is: During the monitoring period, divide the monitoring period into several time nodes, obtain the signal strength value corresponding to each time node, mark it as the measured signal strength value, subtract the measured signal strength value from the standard signal strength value to obtain a signal strength difference value; Add up all the signal strength difference values, take the average value, and perform a ratio calculation with the standard signal strength value to obtain a signal strength deviation value; The acquisition method of the signal time deviation value is: During the monitoring period, obtain the actual signal reception time of the mobile phone, mark it as the actual signal time value, subtract the actual signal time value from the standard signal time value to obtain a signal time difference value; Add up all the signal time difference values and the standard signal time value, take the average value, and perform a ratio calculation with the standard signal time to obtain a signal time deviation value.

3. The signal recognition method for a mobile phone according to claim 1, characterized in that, The acquisition method of the waveform similarity value is: Obtain the actual amplitude deviation value and the actual characteristic point deviation value, add the actual amplitude deviation value and the actual characteristic point deviation value to calculate the sum, and obtain a waveform similarity value.

4. The signal recognition method for a mobile phone according to claim 3, wherein The acquisition method of the actual amplitude deviation value is: Based on the actual signal waveform, establish an X-Y axis coordinate system, where the X axis represents time and the Y axis represents waveform amplitude. Substitute the actual signal waveform into the X-Y axis coordinate system to obtain an actual signal waveform change curve; Based on the actual signal waveform change curve, divide the actual signal waveform change curve into several actual waveform change sub-curves of equal length in terms of time periods, obtain the peak point coordinates and valley point coordinates within each actual waveform change sub-curve, and substitute the adjacent peak point coordinates and valley point coordinates into the formula: Calculate the amplitude value Fn of the actual waveform change sub-curve, where (X f , Y f ) represents the actual peak point coordinates, and (X g , Y g ) represents the actual valley point coordinates; Add up all the actual waveform change sub-curve amplitude values, take the average value, and obtain an actual signal amplitude value; The actual signal amplitude value is successively subtracted from all the interference signal amplitude values, and the absolute value is taken to obtain the actual amplitude difference, which is marked as the actual amplitude difference FC m , where m represents different actual amplitude differences; Add up all the interference signal amplitude values, take the average value, and obtain an interference signal amplitude characterization value; Perform a ratio calculation on the actual amplitude difference value and the interference signal amplitude characterization value to obtain an actual amplitude deviation value.

5. The signal recognition method for a mobile phone according to claim 3, characterized in that, The acquisition method of the actual characteristic point deviation value is: Add the peak feature deviation value and the trough feature deviation value to obtain the actual feature point deviation value.

6. The signal recognition method for a mobile phone according to claim 5, characterized in that, The method for obtaining the peak feature deviation value is as follows: Based on the interference signal waveform, establish an X-Y axis coordinate system, where the X axis represents time and the Y axis represents the interference waveform amplitude. Substitute the interference signal waveform into the X-Y axis coordinate system to obtain the interference signal waveform change curve; Obtain the peak point coordinates and valley point coordinates within the interference signal waveform change curve, and mark them as interference peak point coordinates respectively Interference valley point coordinates Substitute the peak point coordinates on the actual waveform change curve and multiple interference signal waveform change curves into the formula: Calculate the peak point position deviation value FP i , where, (SX f , SY f ) represents the peak point coordinates within the actual signal waveform change curve, represents the peak point coordinates within the interference signal waveform change curve, where n represents different types of interference signal waveform change curves, and i represents different peak point position deviation values; Add up all the peak point position deviation values, sum them up, and take the average to obtain the peak feature deviation value.

7. The signal recognition method for mobile phones according to claim 5, characterized in that The method for obtaining the trough feature 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: Calculate the trough point position deviation value GP u , where, (SX g , SY g ) represents the coordinates of the trough points within the actual signal waveform change curve, represents the coordinates of the trough points within the interference signal waveform change curve, where, n represents the waveform change curves of different types of interference signals, and u represents different trough point position deviation values; Add up all the trough point position deviation values, sum them up, and take the average to obtain the trough feature deviation value.

8. Signal recognition system for mobile phone, characterized in that, The system executes the signal recognition method described in any one of claims 1-7 above. The system includes the following modules: Recognition monitoring module: Real-time obtain the received data obtained by the mobile phone when receiving signals. Among them, the received data includes the signal strength error value and the signal time deviation value. Add up the signal strength error value and the signal time deviation value and calculate to obtain the signal recognition deviation value; Recognition evaluation module: 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 recognition deviation signal includes a large recognition deviation signal and a small recognition deviation signal; If the signal recognition deviation value is greater than or equal to the signal recognition deviation threshold, generate a large recognition deviation signal; If the signal recognition deviation value is less than the signal recognition deviation threshold, generate a small recognition deviation signal; Interference analysis module: Based on the large recognition deviation signal, analyze the signal waveform to obtain a waveform similarity value, determine whether it is affected by interference, and generate an interference recognition signal; Among them, the interference recognition signal includes a first interference recognition signal and a second interference recognition signal; Optimization and adjustment module: Based on the second interference recognition signal, obtain a network mode switching value, and determine the network mode that the mobile phone needs to switch to under different interference intensity environments.

9. An electronic device, characterized in that, It includes a processor that reads and executes the mobile phone software recognition program, thereby implementing the signal recognition method described in any one of claims 1-7 above.

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

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