CN115314134A

CN115314134A - Wi-Fi signal self-adaptive control method, system and mobile terminal

Info

Publication number: CN115314134A
Application number: CN202110498899.4A
Authority: CN
Inventors: 李�瑞
Original assignee: Oneplus Technology Shenzhen Co Ltd
Current assignee: Oneplus Technology Shenzhen Co Ltd
Priority date: 2021-05-08
Filing date: 2021-05-08
Publication date: 2022-11-08

Abstract

The embodiment of the application provides a Wi-Fi signal self-adaptive control method, a system and a mobile terminal, wherein the method comprises the following steps: preprocessing the signal quality data of the collected Wi-Fi signals, and extracting the characteristics of the preprocessed data to obtain a signal quality characteristic value; predicting the signal quality characteristic value at the next moment according to the obtained current signal quality characteristic value and the obtained historical signal quality characteristic value to obtain a signal quality expected value; and controlling the mobile terminal to transmit or receive the Wi-Fi signal at the next moment according to the signal quality expected value and the current signal quality characteristic value. The Wi-Fi signal connection of the mobile terminal is controlled through a feedback closed-loop control mode, and therefore the Wi-Fi service can be provided for users quickly and stably under different environments to the greatest extent.

Description

Wi-Fi signal self-adaptive control method, system and mobile terminal

Technical Field

The application relates to the technical field of terminal communication, in particular to a Wi-Fi signal self-adaptive control method, a system and a mobile terminal.

Background

When a conventional terminal device with a Wi-Fi (wireless fidelity) function is connected to an AP (Access Point), signal requirements are gradually increased, for example, it is required to still maintain high speed and stability of Wi-Fi signal transmission in a short distance with a strong signal, and still ensure practicality of Wi-Fi signals in a long distance with a weak signal. In order to solve the above-mentioned needs, in the existing solutions, firstly, physical avoidance is adopted, in order to avoid the situation that a terminal such as a mobile phone is too close to a Wi-Fi route and the like as much as possible, and the situation that the internet surfing speed of the terminal is slow or the terminal is disconnected is prevented; secondly, the signal strength of the connection between the terminal and the AP is in a relatively stable range through software control, namely, if the distance is too close, signal attenuation is carried out, and if the distance is too far, signal amplification is carried out.

However, the first solution does not solve the problem at all, and only provides a temporary solution to the customer; the second scheme cannot ensure the stability of the Wi-Fi connection device and the AP under different conditions due to the hardware difference and the software control limitation.

Disclosure of Invention

The embodiment of the application provides a Wi-Fi signal self-adaptive control method, a system and a mobile terminal, which can ensure that rapid and stable Wi-Fi service can be provided for users under different environments to the greatest extent.

The embodiment of the application provides a Wi-Fi signal self-adaptive control method, which comprises the following steps:

preprocessing the signal quality data of the collected Wi-Fi signals, and extracting the characteristics of the preprocessed data to obtain a signal quality characteristic value;

predicting the signal quality characteristic value at the next moment according to the obtained current signal quality characteristic value and the obtained historical signal quality characteristic value to obtain a signal quality expected value;

and controlling the mobile terminal to transmit or receive the Wi-Fi signal at the next moment according to the signal quality expected value and the current signal quality characteristic value.

In some embodiments of the present application, the Wi-Fi signal adaptive control method further comprises:

carrying out real-time anomaly detection on the Wi-Fi signals, and identifying signal anomaly types when detecting that the Wi-Fi signals are abnormal;

determining a signal adjustment scheme matching the signal anomaly type;

and regulating and controlling corresponding signal components of the mobile terminal according to the signal regulation scheme so that the mobile terminal recovers the transmission or the reception of the Wi-Fi signals.

In some embodiments of the present application, the preprocessing the signal quality data of the collected Wi-Fi signals, and performing feature extraction on the preprocessed data includes:

performing signal wavelet transformation on the acquired signal quality data, and performing influence factor classification on the signal quality on the data obtained after the wavelet transformation to obtain classification data of all factors;

and performing primary and secondary element analysis on each factor classification data to obtain primary element parameters related to the Wi-Fi signal quality, and taking the primary element parameters as the signal quality characteristic values.

In some embodiments of the present application, the predicting, according to the obtained current signal quality characteristic value and the historical signal quality characteristic value, a signal quality characteristic value at a next time includes:

correcting the current signal quality characteristic value by using a prediction model to output a signal quality characteristic value at the next moment; the prediction model is constructed based on historical signal quality characteristic values, and input variables of the prediction model comprise one or more combinations of signal strength, transmission rate, distance between the mobile terminal and the wireless access point equipment and electromagnetic environment quantization parameters of Wi-Fi signals.

In some embodiments of the present application, said identifying a signal abnormality type in the case of detecting a signal abnormality of the Wi-Fi signal includes:

under the condition that the Wi-Fi signal is detected to be abnormal, inquiring an abnormal diagnosis set through a signal quality control chart to match the signal quality characteristic value with the abnormal signal so as to identify and obtain a corresponding signal abnormal type;

the abnormal diagnosis set is obtained by learning the signal abnormal factors of the Wi-Fi signals based on a dictionary learning algorithm.

In some embodiments of the present application, the controlling the mobile terminal to output the Wi-Fi signal includes:

determining an amplification or attenuation scaling factor of the program-controlled amplifier according to a deviation between the signal quality expected value and the current signal quality characteristic value, and adjusting a driving input level of the Wi-Fi antenna according to the determined scaling factor so as to be used for transmitting or receiving Wi-Fi signals;

or determining a target antenna to be switched according to the deviation degree between the signal quality characteristic value and the current signal quality characteristic value, and switching to the target antenna to transmit or receive the Wi-Fi signal.

An embodiment of the present application further provides a Wi-Fi signal adaptive control system, including: the device comprises an acquisition processing module, a prediction module and a signal control module;

the acquisition processing module is used for preprocessing the signal quality data of the acquired Wi-Fi signals and extracting the characteristics of the preprocessed data to obtain a signal quality characteristic value;

the prediction module is used for predicting the signal quality characteristic value at the next moment according to the obtained current signal quality characteristic value and the historical signal quality characteristic value to obtain a signal quality expected value;

and the signal control module is used for controlling the mobile terminal to transmit or receive the Wi-Fi signal at the next moment according to the signal quality expected value and the current signal quality characteristic value.

In some embodiments of the present application, the Wi-Fi signal adaptive control system further comprises: a diagnostic module and an adjustment module;

the diagnosis module is used for carrying out real-time abnormity detection on the Wi-Fi signals and identifying the abnormal type of the signals under the condition that the Wi-Fi signals are detected to be abnormal;

the adjusting module is used for determining a signal adjusting scheme matched with the signal abnormity type;

the signal control module is further used for regulating and controlling corresponding signal components of the mobile terminal according to the signal regulation scheme so that the mobile terminal can recover the transmission or reception of the Wi-Fi signals.

Embodiments of the present application further provide a mobile terminal, which includes a Wi-Fi antenna, a processor, and a memory, where the Wi-Fi antenna is configured to transmit or receive a Wi-Fi signal, and the memory stores a computer program, and the processor is configured to execute the computer program to implement the above-mentioned Wi-Fi signal adaptive control method.

Embodiments of the present application also provide a readable storage medium storing a computer program that, when run on a processor, implements the Wi-Fi signal adaptive control method described above.

The embodiment of the application has the following beneficial effects:

according to the method, effective dimensionality reduction signal quality characteristic values are obtained by acquiring signal quality data of Wi-Fi signals in real time and performing principal component analysis and other processing on the acquired data; and constructing a prediction model by using the signal quality characteristic values for determining a signal quality expected value at the next moment; and finally, carrying out self-adaptive adjustment on Wi-Fi signal transmission or reception of the mobile terminal based on the deviation between the current value and the expected value, namely, through closed-loop control, the Wi-Fi service can be provided for users quickly and stably under different environments to the greatest extent.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments are briefly described below, it should be understood that the drawings shown below are only some embodiments of the present application, and therefore should not be considered as limiting the scope, and it is obvious for those skilled in the art that other related drawings can be obtained from the drawings without inventive effort.

Fig. 1 is a schematic view of an application scenario of a mobile terminal according to an embodiment of the present application;

FIG. 2 is a first flowchart of a Wi-Fi signal adaptive control method according to an embodiment of the present disclosure;

fig. 3 is a schematic flow chart illustrating signal quality characteristic value acquisition in a Wi-Fi signal adaptive control method according to an embodiment of the present disclosure;

FIG. 4 is a diagram illustrating a Wi-Fi signal adaptive control method according to an embodiment of the present application describing signal strength by a control diagram;

FIG. 5 is a second flowchart illustrating a Wi-Fi signal adaptive control method according to an embodiment of the present disclosure;

fig. 6 is a schematic structural diagram of a Wi-Fi signal adaptive control system according to an embodiment of the present application.

Description of the main element symbols:

100-a mobile terminal; 200-AP devices; a 101-Wi-Fi antenna; 102-a programmable amplifier;

a 200-Wi-Fi signal adaptive control system; 210-an acquisition processing module; 220-a prediction module; 230-a signal control module; 240-a diagnostic module; 250-adjusting module.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, as presented in the figures, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.

Example 1

Referring to fig. 1, the present embodiment provides a Wi-Fi signal adaptive control method, which can be applied to a mobile terminal 100 supporting Wi-Fi functions, such as a smart phone, a smart watch, a tablet computer, and a notebook computer. For example, as shown in fig. 1, the mobile terminal 100 performs Wi-Fi connection with the AP device 200 (such as a router, etc.), wherein a distance between the mobile terminal 100 and the AP device 200 may be changed at will, and in order to better ensure rapidity and stability of Wi-Fi connection, the present embodiment employs the following Wi-Fi signal adaptive control method, so as to obtain better Wi-Fi service experience.

As shown in fig. 2, the Wi-Fi signal adaptive control method includes:

and S10, preprocessing the signal quality data of the acquired Wi-Fi signals, and extracting the characteristics of the preprocessed data to obtain a signal quality characteristic value.

Exemplarily, the signal quality data related to the Wi-Fi signal is obtained by performing relevant signal acquisition on the Wi-Fi signal transmitted or received by the mobile terminal 100, for example, the signal quality data may include, but is not limited to, a combination of at least two of Wi-Fi signal strength, a distance between the mobile terminal 100 and the AP device 200, a Wi-Fi signal transmission rate, and electromagnetic wave radiation strength, inter-channel isolation, and other performance parameters related to an electromagnetic environment; the performance parameter related to the electromagnetic environment is mainly related to the electromagnetic environment factor, for example, the electromagnetic environment factor may be mutual interference between channels, other devices using the current channel around, and the like, such as other routers, induction cookers, spectrum analyzers, and the like.

The signal quality characteristic value refers to a main performance parameter for reflecting the Wi-Fi signal quality. Generally, there are many factors that can affect Wi-Fi signals, and in this embodiment, the main parameters that affect the quality of the current signal are obtained by performing corresponding preprocessing on the acquired data, such as short-time fourier transform, wavelet transform, and the like, and then performing processing on the preprocessed data, such as principal component analysis, cluster analysis, and the like, by extracting effective dimension reduction data from the preprocessed data.

In one embodiment, as shown in fig. 3, the step S10 may include:

and step S110, performing signal wavelet transformation on the acquired signal quality data.

Considering that Wi-Fi signals may sometimes fluctuate greatly due to external environmental factors, etc., a wavelet transform method may be used to process the collected Wi-Fi signals. The wavelet transformation not only can obtain each frequency component in the signal, but also can obtain the specific position of the corresponding frequency component on the time domain and the like by performing time-frequency analysis on the unsteady state signal. It will be appreciated that other analysis techniques, such as fourier transforms or short-time fourier transforms, may be used for other relatively stable signals acquired.

And step S120, carrying out influence factor classification of signal quality on the data obtained after the wavelet transformation to obtain various factor classification data.

Exemplarily, after wavelet transformation of the signals, relevant processing data, such as frequency spectrum, power or energy of Wi-Fi signals, strength change of the Wi-Fi signals at different moments and the like, can be obtained, and further, classification data of a plurality of factors can be obtained by analyzing signal quality influence factors of the data.

The reason is that there are many influencing factors of signal quality, and the influencing factors can be classified into different types in advance, such as signal strength type, distance type, environmental noise type, negotiation rate type, transmission rate type, and the like, wherein the negotiation rate type refers to the currently used network bandwidth, and the transmission rate type refers to the actual network transmission rate. The influence factors of the data obtained after wavelet transformation are classified according to different types, so that the primary and secondary element classification can be further performed on each factor classification data.

And S130, performing primary and secondary element analysis on each factor classification data to obtain primary element parameters related to Wi-Fi signal quality, and taking each primary element parameter as a signal quality characteristic value.

The primary and secondary element analysis, also called principal component analysis technology, mainly utilizes statistical principle to fuse a plurality of variables into one variable, so that the number of the variables is greatly reduced, namely, the dimension reduction of the variables is realized. For the above main element parameters, the main element parameters may be parameters that have the largest influence on the current Wi-Fi signal quality in classification data of one influence factor, or may be two or three parameters that have the highest influence on the current Wi-Fi signal quality, and the like, and may be specifically determined according to actual requirements.

For the step S130, exemplarily, after performing principal component analysis on the different factor classification data, corresponding principal component parameters can be obtained. Then, these main factor parameters are used as the signal quality characteristic values of the current Wi-Fi signal, which may include, but are not limited to, signal strength, transmission rate, etc., for example, so as to perform Wi-Fi signal control subsequently.

It can be understood that, because there are many collected performance parameters and many combinations of these performance parameters, in order to extract effective influencing factor data, the analyzing speed can be greatly increased by classifying the influencing factors and then analyzing the primary and secondary elements, and the control process of the signal quality is ensured to be accurate and reliable.

And step S20, predicting the signal quality characteristic value at the next moment according to the obtained current signal quality characteristic value and the historical signal quality characteristic value to obtain a signal quality expected value.

In order to maximize the real-time performance and accuracy of the control process, a prediction model can be constructed by predicting the trend of the received Wi-Fi signal quality, for example, according to the acquired historical signal quality characteristic value. Since the signal quality characteristic value at the next time is predicted, in the present embodiment, the input variable and the output variable of the prediction model are set to be the same.

In one embodiment, the input variables or output variables of the prediction model may include, but are not limited to, various combinations including signal strength, transmission rate, distance, and related parameters for quantifying electromagnetic environment, wherein the related quantified parameters for electromagnetic environment factors may be electromagnetic wave radiation intensity, channel isolation, crosstalk value, etc. The prediction model may be obtained by performing statistical analysis on a certain number of collected data samples. Furthermore, the prediction model has the autonomous learning capability, namely, the autonomous correction can be carried out according to the continuous increase of the data quantity, so that the prediction accuracy is ensured to the maximum extent.

In step S20, for example, the current signal quality characteristic value may be corrected and outputted by using the prediction model to predict the signal quality characteristic value at the next time, and the signal quality characteristic value at the next time of the predicted output may be used as an expected value for further adjustment in combination with the current actual value.

And step S30, controlling the mobile terminal 100 to transmit or receive the Wi-Fi signal at the next moment according to the signal quality expected value and the current signal quality characteristic value.

Exemplarily, after obtaining the expected value at the next time, the current actual value is adjusted according to the expected value, so as to achieve the purpose of adjusting the signal quality of the Wi-Fi signal in real time. Generally, as shown in fig. 1, a mobile terminal 100 includes at least one Wi-Fi antenna 101 and a programmable amplifier 102 (also called a programmable gain amplifier) connected to the Wi-Fi antenna 101, and considering that objects that can be adjusted on the side of the mobile terminal 100 mainly include a transmission rate and a signal strength of a signal, wherein the signal strength can be changed by adjusting a transmission power of a TX (transmission) antenna or a reception power of an RX (reception) antenna, or performing antenna switching.

In one embodiment, for step S30, the amplification or attenuation scaling factor of the programmable amplifier 102 may be adjusted, for example, according to the deviation between the signal quality expected value and the current signal quality characteristic value; furthermore, the driving input level of the Wi-Fi antenna 101 is adjusted according to the determined proportionality coefficient, so that the purpose of adjusting the transmitting power or the receiving power of the Wi-Fi antenna 101 is achieved, and finally the mobile terminal 100 can transmit a Wi-Fi signal meeting the requirement or can receive the Wi-Fi signal.

Alternatively, in another embodiment, if there are two or more antennas, exemplarily, an available antenna to be switched (referred to as a target antenna) may be determined according to a deviation degree between the expected signal quality value and the current signal quality characteristic value, and Wi-Fi signal communication is performed by switching to the target antenna, so as to ensure that the mobile terminal 100 can dynamically adjust transmission or reception of Wi-Fi signals.

It can be understood that, in the steps S10 to S30, the Wi-Fi signal connection of the mobile terminal 100 is adaptively controlled through a closed-loop system, so that the real-time performance and accuracy of the control system can be improved to the greatest extent, the speed and stability of the Wi-Fi connection are ensured, and the Wi-Fi use experience of the user is improved.

Considering that the Wi-Fi signal may suddenly become weak or even the wireless network may not be available when the mobile terminal 100 is connected to the Wi-Fi signal, the method of this embodiment further adds a function of diagnosing the signal abnormality and adjusting the signal in real time to further improve the anti-interference capability of the mobile terminal 100.

Further, as shown in fig. 4, the Wi-Fi signal adaptive control further includes:

and S40, carrying out real-time abnormity detection on the Wi-Fi signals, and identifying the abnormal type of the signals under the condition that the Wi-Fi signals are detected to be abnormal.

Exemplarily, when the abnormality detection is performed, whether Wi-Fi cutoff occurs or not, that is, whether an abnormal interruption phenomenon occurs during Wi-Fi communication is detected by monitoring whether the mobile terminal 100 performs Wi-Fi cutoff or not, and if the abnormal interruption phenomenon occurs, it is determined that the Wi-Fi connection at the time is abnormal.

The signal anomaly type may be obtained by classifying the data in which the signal anomaly occurs in advance, for example, the signal anomaly type may include, but is not limited to, one or more combinations of weak signal strength, unreachable wireless network, failed signal transmission (RX Fail) and failed signal reception (TX Fail). It will be appreciated that the primary cause of an anomaly is also determined by the type of anomaly to which it belongs.

In one embodiment, for example, the anomaly diagnostic set may be queried by a signal quality control map to match signal quality characteristic values for the presence of a signal anomaly to identify a corresponding signal anomaly type. The Control Chart (Control Chart) is also called as a management Chart, and can Control the quality fluctuation of a signal Control process by distinguishing the fluctuation of a signal caused by an abnormal reason or the normal fluctuation caused by the inherent reason of the signal communication process, and can enable the process to be in a controlled state by timely adjusting and eliminating the abnormal fluctuation.

The above-mentioned anomaly diagnosis set refers to a set in which data is anomalous, and can be obtained by learning signal anomaly factors of Wi-Fi signals. It is understood that the term "abnormal" mainly refers to a discrepancy or an exceeding of an allowable fluctuation range from an expected data size. For example, in an embodiment, the above-mentioned abnormality diagnosis set may be learned based on a dictionary learning algorithm, but of course, other algorithms may be used to construct the abnormality diagnosis set, and the invention is not limited thereto. The dictionary learning algorithm is mainly used for sparsely representing data by constructing a dictionary, and the dictionary learning algorithm is used for classifying historical data with signal abnormality to obtain a corresponding abnormality diagnosis set, so that the subsequent abnormal type can be quickly matched by searching the abnormality diagnosis set when the signal abnormality occurs.

And S50, determining a signal adjusting scheme matched with the signal abnormity type.

Wherein, an appropriate control scheme is selected for each anomaly type to adjust. Exemplarily, when the signal abnormality type of the current Wi-Fi signal is determined, the corresponding adjustment scheme may be further determined. For example, when the detected abnormal type is that the signal strength is too weak, a scheme for adjusting the antenna transmission power can be selected. Or, when the abnormal type is detected to be that the transmission rate is too low, a scheme for adjusting the transmission rate and the like can be selected.

And step S60, regulating and controlling corresponding signal components of the mobile terminal 100 according to the signal regulation scheme so that the mobile terminal 100 resumes transmitting or receiving Wi-Fi signals.

Exemplarily, the relevant signal components are subjected to adjustment control according to the determined adjustment scheme, such as adjustment of relevant parameters of the components, switching of the signal components, and the like, so that the mobile terminal 100 resumes normal transmission or reception of Wi-Fi signals, thereby satisfying user requirements. The above-mentioned corresponding signal components mainly depend on the software and hardware configuration of the mobile terminal 100, and for example, may be input parameter adjustment of the above-mentioned program-controlled amplifier for driving the Wi-Fi antenna 101 to transmit or receive signals, or antenna switching by an antenna switch, and the like.

Taking a Wi-Fi signal strength closed-loop control system as an example, as shown in fig. 5, the main controller receives signal quality related data fed back by the antenna side, and performs corresponding processing on the signal quality related data to obtain a required current signal characteristic value, and then predicts a characteristic value at the next moment according to the current characteristic value and historical data, and then controls related signal components such as a program control amplifier, a Wi-Fi antenna and the like according to the predicted value to realize transmission or reception of a Wi-Fi signal at the next moment. In addition, the main controller also carries out abnormity diagnosis according to the current signal characteristic value and regulates and controls the signal assembly after abnormity occurs so as to further ensure that the transmitted or received Wi-Fi signal meets the requirement.

The Wi-Fi signal self-adaptive control method of the embodiment obtains an effective signal quality characteristic value by classifying and reducing the dimension of signal quality data of Wi-Fi signals acquired in real time; using the signal quality characteristic values to construct a prediction model, and the prediction model is used for determining a signal quality expected value at the next moment; and finally, dynamically controlling the mobile terminal to transmit or receive Wi-Fi signals by combining the current value and the expected value, realizing self-adaptive control by closed-loop control, and ensuring the rapidness and stability of Wi-Fi connection to the maximum extent. In addition, by carrying out abnormity diagnosis on the signals and adopting a corresponding adjustment scheme for adjustment when the signals are abnormal, the stability of Wi-Fi connection can be further ensured, and the user experience is improved.

Example 2

Referring to fig. 6, based on the method of embodiment 1, this embodiment provides a Wi-Fi signal adaptive control system 200, where exemplarily, the Wi-Fi signal adaptive control system 200 includes: an acquisition processing module 210, a prediction module 220, and a signal control module 230.

The acquisition processing module 210 is configured to pre-process the signal quality data of the acquired Wi-Fi signal, and perform feature extraction on the pre-processed data to obtain a signal quality feature value;

the prediction module 220 is configured to predict a signal quality characteristic value at a next time according to the obtained current signal quality characteristic value and the obtained historical signal quality characteristic value, so as to obtain a signal quality expected value;

the signal control module 230 is configured to control the mobile terminal to transmit or receive the Wi-Fi signal at the next time in real time according to the expected signal quality value and the current signal quality characteristic value.

Further, as shown in fig. 6, the system further includes: a diagnostic module 240 and an adjustment module 250.

The diagnosis module 240 is configured to perform real-time anomaly detection on the Wi-Fi signal, and identify a signal anomaly type when the Wi-Fi signal is detected to be anomalous.

The adjustment module 250 is used to determine a signal adjustment scheme matching the signal anomaly type.

The signal control module 230 is further configured to regulate corresponding signal components of the mobile terminal according to the signal adjustment scheme, so that the mobile terminal resumes transmitting or receiving Wi-Fi signals.

It is to be understood that the apparatus of the present embodiment corresponds to the method of embodiment 1 described above, and the alternatives of embodiment 1 described above are equally applicable to the present embodiment, and therefore, the description thereof will not be repeated.

The application further provides a mobile terminal, exemplarily comprising a Wi-Fi antenna, a processor and a memory, wherein the Wi-Fi antenna is used for transmitting or receiving Wi-Fi signals, the memory stores a computer program, and the processor enables the mobile terminal to execute the functions of the above-mentioned Wi-Fi signal adaptive control method or the above-mentioned modules in the Wi-Fi signal adaptive control system by operating the computer program.

The application also provides a readable storage medium for storing the computer program used in the mobile terminal.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative and, for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In addition, each functional module or unit in each embodiment of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a smart phone, a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application.

Claims

1. A Wi-Fi signal adaptive control method, comprising:

preprocessing the signal quality data of the acquired Wi-Fi signals, and extracting the characteristics of the preprocessed data to obtain a signal quality characteristic value;

2. The method of claim 1, further comprising:

carrying out real-time anomaly detection on the Wi-Fi signals, and identifying the signal anomaly type under the condition that the Wi-Fi signal anomaly is detected;

determining a signal adjustment scheme matching the signal anomaly type;

and regulating and controlling corresponding signal components of the mobile terminal according to the signal regulation scheme so that the mobile terminal recovers the transmission or reception of the Wi-Fi signal.

3. The method according to claim 1 or 2, wherein the pre-processing the signal quality data of the collected Wi-Fi signals and performing feature extraction on the pre-processed data comprises:

performing signal wavelet transformation on the acquired signal quality data, and classifying the influencing factors of the signal quality on the data obtained after the wavelet transformation to obtain classified data of all the factors;

and performing primary and secondary element analysis on each factor classification data to obtain a primary element parameter related to Wi-Fi signal quality, and taking the primary element parameter as the signal quality characteristic value.

4. The method of claim 3, wherein predicting the signal quality characteristic value at the next time according to the obtained current signal quality characteristic value and the historical signal quality characteristic value comprises:

correcting the current signal quality characteristic value by using a prediction model to output a signal quality characteristic value at the next moment; wherein the prediction model is constructed based on the characteristic values according to the historical signal quality; the input variables of the prediction model comprise one or more of the combination of signal strength of Wi-Fi signals, transmission rate, distance between the mobile terminal and the wireless access point device and electromagnetic environment quantification parameters.

5. The method of claim 2, wherein the identifying a type of signal abnormality in the case of detecting a signal abnormality in the Wi-Fi signal comprises:

6. The method according to claim 1 or 2, wherein the mobile terminal comprises at least one Wi-Fi antenna and a program-controlled amplifier connected to the Wi-Fi antenna, and the controlling of Wi-Fi signal transmission or reception of the mobile terminal comprises:

7. A Wi-Fi signal adaptive control system, comprising: the device comprises an acquisition processing module, a prediction module and a signal control module;

8. The system of claim 7, further comprising: a diagnostic module and an adjustment module;

the diagnosis module is used for carrying out real-time abnormity detection on the Wi-Fi signals and identifying the signal abnormity type under the condition that the Wi-Fi signals are detected to be abnormal;

9. A mobile terminal, characterized in that the mobile terminal comprises a Wi-Fi antenna for transmitting or receiving Wi-Fi signals, a processor and a memory, the memory storing a computer program, the processor being configured to execute the computer program to implement the Wi-Fi signal adaptive control method of any of claims 1 to 6.

10. A readable storage medium, characterized in that it stores a computer program which, when run on a processor, implements the Wi-Fi signal adaptive control method according to any one of claims 1 to 6.