Method, device, electronic device and storage medium for waking up wireless device

Abstract

The present application discloses a method, apparatus, electronic device, and storage medium for waking up a wireless device, belonging to the field of communication technology. The method for waking up a wireless device is used for a wireless device connected to a router. The method for waking up a wireless device includes: obtaining time information of a beacon frame sent by the router, where the time information is associated with the time when the beacon frame is sent; determining a target prediction model based on the time information, where the target prediction model is a first prediction model with the lowest power consumption determined from multiple first prediction models based on the time information, where the first power consumption includes: a second power consumption corresponding to the wireless device running the first prediction model, and a third power consumption corresponding to the wireless device performing a wake-up operation according to a first wake-up strategy, where the first wake-up strategy is a strategy corresponding to the first prediction model; and performing a wake-up operation according to the first wake-up strategy corresponding to the target model.

Description

Technical Field

[0001] The present application belongs to the field of communication technology, and specifically relates to a method, apparatus, electronic device, and storage medium for waking up a wireless device. Background Art

[0002] The portability of smart devices means they cannot be equipped with large-capacity power supply equipment. As the wireless module is one of the main sources of power consumption, the sleep power saving strategy of the wireless module plays an important role in the battery life of smart devices. The wireless module in sleep state will listen to the router's beacon frame through periodic short wake-up.

[0003] In the related art, when a wireless module monitors beacon frames sent by a router, in order to meet the low power consumption requirements of the device, there is usually a problem of loss of the monitored beacon frames. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a method, apparatus, electronic device and storage medium for waking up a wireless device, which achieves low power consumption while reducing the delay problem caused by the loss of beacon frame monitoring of the wireless device.

[0005] In a first aspect, an embodiment of the present application provides a method for waking up a wireless device, which is used for a wireless device, and the wireless device is connected to a router. The method for waking up the wireless device includes: obtaining time information of a beacon frame sent by the router, and the time information is associated with the sending time of the beacon frame; determining a target prediction model based on the time information, and the target prediction model is a prediction model with the lowest first power consumption determined from multiple first prediction models based on the time information, and the first power consumption includes: the second power consumption corresponding to the wireless device running the first prediction model, and the third power consumption corresponding to the wireless device performing the wake-up operation according to the first wake-up strategy, wherein the first wake-up strategy is a strategy corresponding to the first prediction model; performing the wake-up operation according to the first wake-up strategy corresponding to the target model.

[0006] In a second aspect, an embodiment of the present application provides a wake-up device for a wireless device, which is used for the wireless device, and the wireless device is connected to a router. The wake-up device for the wireless device includes: an acquisition module, which is used to obtain time information of the router sending a beacon frame, and the time information is associated with the sending time of the beacon frame; a determination module, which is used to determine a target prediction model based on the time information, and the target prediction model is a first prediction model with the lowest power consumption determined from multiple first prediction models based on the time information. The first power consumption includes: the second power consumption corresponding to the wireless device running the first prediction model, and the third power consumption corresponding to the wireless device performing the wake-up operation according to the first wake-up strategy, wherein the first wake-up strategy is a strategy corresponding to the first prediction model; an execution module, which is used to perform the wake-up operation according to the first wake-up strategy corresponding to the target model.

[0007] In a third aspect, an embodiment of the present application provides an electronic device comprising a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the programs or instructions are executed by the processor, the steps of the method of the first aspect are implemented.

[0008] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method of the first aspect are implemented.

[0009] In a fifth aspect, an embodiment of the present application provides a chip, which includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the steps of the method of the first aspect.

[0010] In a sixth aspect, an embodiment of the present application provides a computer program product, which is stored in a storage medium and is executed by at least one processor to implement the method of the first aspect.

[0011] In an embodiment of the present application, based on the time information of the router sending the beacon frame obtained by the wireless device, multiple first prediction models that can accurately predict the time point when the router sends the beacon frame are established, and the model with the lowest first power consumption is selected as the target prediction model. The target prediction model is deployed to the wireless device, so that the wireless device can perform a wake-up operation according to the first wake-up strategy corresponding to the target prediction model, thereby achieving low power consumption while reducing the delay problem caused by the loss of beacon frame monitoring of the wireless device. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A schematic diagram showing a process of waking up a wireless device according to an embodiment of the present application is shown;

[0013] Figure 2 A waveform diagram of the wake-up and sleep-down of a wireless device provided by an embodiment of the present application is shown;

[0014] Figure 3 A schematic diagram showing the structure of a wake-up device for a wireless device provided in an embodiment of the present application is shown;

[0015] Figure 4 shows a structural block diagram of an electronic device according to an embodiment of the present application;

[0016] Figure 5 A schematic diagram of the hardware structure of an electronic device implementing an embodiment of the present application. DETAILED DESCRIPTION

[0017] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0018] The terms "first," "second," and the like in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. In addition, the term "and / or" in the specification and claims refers to at least one of the connected objects, and the character " / " generally indicates that the objects connected are in an "or" relationship.

[0019] The following is combined with Figures 1 to 5 , through specific embodiments and their application scenarios, the wake-up method of the wireless device, the wake-up device of the wireless device, the electronic device and the storage medium provided in the embodiments of the present application are described in detail.

[0020] In some embodiments of the present application, a method for waking up a wireless device is provided, which is applied to the wireless device. The wireless device is connected to a router, and the wireless device is communicated with the router through a wireless module. Figure 1 FIG. 1 shows a flow chart of a method for waking up a wireless device according to an embodiment of the present application. Figure 1 As shown, the wake-up method of the wireless device includes:

[0021] Step 102: Obtain time information of the beacon frame sent by the router, where the time information is associated with the time when the beacon frame is sent;

[0022] In the embodiment of the present application, the router continuously sends beacon frames, and the wireless device can obtain the time information when the router sends the beacon frames.

[0023] After receiving the beacon frame, the wireless device can obtain the sending time of the beacon frame through the beacon frame and record time information related to the sending time.

[0024] Among them, the time information includes the time interval between each beacon frame sent by the router, the time when the router sends the beacon frame, etc.

[0025] Step 104: determining a target prediction model based on the time information, where the target prediction model is a prediction model with the minimum first power consumption determined from a plurality of first prediction models based on the time information;

[0026] The first power consumption includes the second power consumption corresponding to the wireless device running the first prediction model and the third power consumption corresponding to the wireless device performing the wake-up operation according to the first wake-up strategy, wherein the first wake-up strategy is a strategy corresponding to the first prediction model.

[0027] In the embodiment of the present application, based on the acquired time information of the router sending the beacon frame, multiple first prediction models for predicting the router sending the beacon frame can be established, and the first prediction model with the lowest first power consumption among the multiple first prediction models is selected as the target prediction model.

[0028] The first power consumption of the first prediction model includes two power consumptions: the second power consumption and the third power consumption.

[0029] The second power consumption is the power consumption corresponding to when the wireless device runs the first prediction model. The wireless device can obtain the first wake-up strategy corresponding to the router by running the first prediction model.

[0030] It should be noted that the second power consumption is associated with the computational complexity of the first prediction model. The higher the computational complexity of the first prediction model, the higher the power consumption of the wireless device when predicting beacon frames using the first prediction model. The second power consumption is associated with the number of calculations performed during each run of the first prediction model. The higher the number of calculations performed during each prediction of the first prediction model, the higher the power consumption of the wireless device when predicting beacon frames using the first prediction model.

[0031] The third power consumption is the power consumption required by the wireless device to perform the wake-up operation according to the first wake-up strategy.

[0032] It should be noted that the third power consumption is associated with the wake-up duration corresponding to the first wake-up strategy and the hardware parameters of the wireless device. When the hardware parameters of the wireless devices are the same, the longer the wake-up duration, the higher the corresponding third power consumption.

[0033] Specifically, the wireless device establishes multiple first prediction models based on time information. The wireless device determines multiple first wake-up strategies corresponding to the multiple first prediction models. The wireless device obtains a second power consumption required for the wireless device to run each first prediction model, and a third power consumption required for the wireless device to perform a wake-up operation according to each first wake-up strategy. The model with the lowest first power consumption among the multiple first prediction models is determined as a target prediction model, where the first power consumption is the sum of the second power consumption and the third power consumption.

[0034] It should be noted that the wireless device uses different time series prediction algorithms to establish multiple first prediction models based on time information, such as a periodic factor algorithm, a linear regression algorithm, and an autoregressive integrated moving average model (ARIMA). The corresponding first wake-up strategy is then calculated based on the preset error range of the different first prediction models, and the first wake-up strategy includes the wake-up duration. The second power consumption required for the wireless device to run each first prediction model and the third power consumption of the wireless device performing the wake-up operation according to the corresponding first wake-up strategy are determined. The sum of the corresponding second power consumption and the third power consumption is determined as the first power consumption corresponding to the first prediction model, thereby determining the first power consumption corresponding to each first prediction model. The first prediction model with the lowest first power consumption is selected from the multiple first prediction models as the target prediction model for the wireless device.

[0035] It should be noted that the process of establishing multiple first prediction models based on time information and selecting a target prediction model from the multiple first prediction models can be performed by the wireless device or by the cloud server. When the cloud server performs the above process, the wireless device needs to upload the time information to the cloud server after obtaining the time information. After the cloud server determines the target prediction model, it sends the target prediction model and its corresponding first wake-up strategy to the wireless device.

[0036] Step 106: Perform a wake-up operation according to the first wake-up strategy corresponding to the target model.

[0037] In an embodiment of the present application, after determining the target prediction model, the wireless device performs a wake-up operation through a first wake-up strategy corresponding to the target prediction model to achieve accurate monitoring of the beacon frame.

[0038] Specifically, when a wireless device is connected to a router, the wireless device can receive beacon frames sent by the router and obtain the time information of the current router sending the beacon frame from the beacon frame. Based on the time information, multiple first prediction models are established. Each of the multiple first prediction models can accurately predict the time point when the router sends the beacon frame, so each first prediction model corresponds to a first wake-up strategy. After obtaining the multiple first prediction models, the first power consumption of the first prediction model is determined based on each first prediction model and its corresponding first wake-up strategy. The model with the lowest power consumption among the multiple first prediction models is selected as the target prediction model. The target prediction model is then deployed in the wireless device, enabling the wireless device to predict the time when the router sends the beacon frame and perform a wake-up operation according to the first wake-up strategy corresponding to the target prediction model to monitor the beacon frames sent by the router.

[0039] Figure 2 The waveform diagram of the wake-up and sleep of the wireless device provided by the embodiment of the present application is shown. As Figure 2 shown, the time point when the beacon frame sent by the router reaches the wireless device is y, the central moment when the wireless device wakes up and then goes to sleep is x, and the time length for the wireless device to listen for the beacon frame sent by the router is dx. It can be seen that as long as |x - y| < dx / 2 is satisfied, it can be ensured that the wireless device can receive the beacon frame sent by the router.

[0040] In the embodiment of the present application, according to the time information of the beacon frame sent by the router obtained by the wireless device, multiple first prediction models that can accurately predict the time point when the router sends the beacon frame are established, and the model with the smallest first power consumption among them is selected as the target prediction model. The target prediction model is deployed in the wireless device, so that the wireless device can perform the wake-up operation according to the first wake-up strategy corresponding to the target prediction model, achieving the reduction of the delay problem caused by the loss of beacon frame listening while taking into account low power consumption.

[0041] In some embodiments of the present application, before performing the wake-up operation according to the first wake-up strategy corresponding to the target prediction model, it includes: determining the first moment when the router sends the beacon frame through the target prediction model; obtaining the wake-up duration of the first wake-up strategy corresponding to the target prediction model; and determining the second moment corresponding to the first wake-up strategy according to the first moment and the wake-up duration.

[0042] Performing the wake-up operation according to the first wake-up strategy corresponding to the target prediction model includes:

[0043] When the wireless device runs to the second moment, the wireless device switches from the sleep state to the wake-up state;

[0044] When the wireless device is in the wake-up state and reaches the wake-up duration, control the wireless device to switch from the wake-up state to the sleep state.

[0045] In the embodiment of the present application, after the target prediction model is deployed in the wireless device, the wireless device runs the target prediction model, and can predict the moment when the router sends the beacon frame, obtaining the first moment, that is, the first moment is the time point predicted by the wireless device through the target prediction model.

[0046] The first wake-up strategy of the target prediction model corresponds to a wake-up duration, and this wake-up duration is the minimum duration that can meet the prediction accuracy. According to the first moment and the wake-up duration, the second moment corresponding to the first wake-up strategy of the target prediction model can be determined.

[0047] Specifically, in the case where the first moment when the router sends a beacon frame is predicted by the target prediction model, to ensure that the wireless device can receive the beacon frame sent by the router while being in the wake-up state, the wireless device needs to be in the wake-up state at the first moment. The wireless device determines the second moment based on the first moment and the wake-up duration corresponding to the first wake-up policy, and makes the wireless device start to perform the wake-up operation at the second moment and wake up for the wake-up duration, so as to ensure that the wireless device is in the wake-up state at the first moment.

[0048] During the process of the wireless device performing the wake-up operation, the wireless device wakes up at the second moment and switches to the sleep state after reaching the wake-up duration, ensuring that the wireless device can be in the wake-up state at the first moment.

[0049] Exemplarily, in the case where the first moment is determined to be t1 and the wake-up duration is △t, then the second moment t2 = t1 - △t / 2, making the wireless device wake up at the t2 moment. When the wake-up duration reaches △t / 2, the router sends a beacon frame at the first moment. After the wake-up duration reaches △t, the wireless device is controlled to switch to the sleep state.

[0050] In the embodiments of the present application, the wireless device can determine the second moment when the wireless device switches from the sleep state to the wake-up state according to the first moment predicted by the target prediction model and the wake-up duration corresponding to the first wake-up policy. The wireless device switches to the wake-up state at the second moment and switches to the sleep state after the wake-up state lasts for the wake-up duration, which can ensure that the wireless device accurately receives the beacon frame sent by the router at the first moment and avoids the problem of beacon frame loss.

[0051] In some embodiments of the present application, obtaining the wake-up duration of the first wake-up policy corresponding to the target preset model includes: obtaining the preset error range corresponding to the target prediction model; according to the preset error range, determining the wake-up duration of the first wake-up policy corresponding to the target prediction model, where the wake-up duration is greater than the reception duration of receiving the beacon frame from the router and greater than or equal to the first duration, and the first duration is associated with the preset error range.

[0052] It should be noted that as Figure 2 shown, since ensuring |x - y| < dx / 2 can guarantee that the wireless device can receive the beacon frame, there can be a certain error in the established multiple first prediction models, and this error is related to the wake-up duration, where y is the time point when the beacon frame arrives at the wireless device, x is the central moment from when the wireless device wakes up to when it sleeps, and dx is the wake-up duration.

[0053] The preset error range is the allowable error range for the multiple first prediction models. The accuracy index of the multiple first prediction models can be determined according to the preset error range.

[0054] In some possible implementations, the accuracy index of the first prediction model may be selected to be 95%, that is, the allowable error range is 1% to 5%.

[0055] Since the error of the target prediction model is related to the wake-up duration, the minimum wake-up duration (first duration) corresponding to the target prediction model can be determined according to the preset error range of the target prediction model and the model parameters of the target prediction model, that is, the wake-up duration corresponding to the first wake-up strategy needs to be greater than or equal to the first duration. In the process of determining the wake-up duration, it should be noted that the higher the model accuracy of the target prediction model and the higher the computational complexity of the target prediction model, the shorter the wake-up duration of the first wake-up strategy corresponding to the target prediction model. The lower the model accuracy of the target prediction model and the lower the computational complexity of the target prediction model, the longer the wake-up duration of the first wake-up strategy corresponding to the target prediction model.

[0056] Specifically, different first prediction models correspond to different preset error ranges. After obtaining the prediction error range of the target prediction model, the first duration corresponding to the target prediction model can be determined based on the prediction error range. The first duration is the minimum wake-up duration within the preset error range. The duration of the router sending the beacon frame, i.e., the duration of the wireless device receiving the beacon frame, is also obtained. The wake-up duration corresponding to the first wake-up strategy is set to be greater than or equal to the first duration and greater than the duration of receiving the beacon frame, further improving the accuracy of executing the wake-up operation based on the second time and the wake-up duration.

[0057] In the embodiment of the present application, the minimum wake-up duration (first duration) within the preset error range of the target prediction model is determined based on the preset error range, and the wake-up duration is set to be greater than or equal to the first duration. Since the wake-up duration is associated with the wake-up error, the error of the first wake-up strategy corresponding to the target prediction model can be flexibly adjusted by setting the wake-up duration.

[0058] It should be noted that, when a smaller error is required, the wake-up time is increased, and when power consumption needs to be reduced as much as possible, the wake-up time is decreased.

[0059] In some embodiments of the present application, the wake-up duration is greater than the second duration, and the second duration is a predicted duration for the wireless device to predict the sending time of the beacon frame sent by the router through a target prediction model.

[0060] In an embodiment of the present application, the wake-up duration is greater than the time required for the target prediction model to predict the next beacon frame, ensuring that during the stage of the wireless module wake-up operation, the target prediction model has predicted the time point when the router sends the next beacon frame, thereby enabling the wireless device to continuously predict the router's sending of beacon frames based on the target prediction model, and perform the wake-up operation based on the prediction result and the corresponding first wake-up strategy, further improving the accuracy of the wireless device in performing the wake-up operation.

[0061] In some embodiments of the present application, according to the first wake-up strategy corresponding to the target prediction model, before executing the wake-up operation, it also includes: obtaining first identification information corresponding to the router; when the first identification information matches the preset identification information, obtaining the second prediction model corresponding to the first identification information; and determining that the target prediction model is the second prediction model.

[0062] In this embodiment of the present application, before executing a wake-up operation according to a first wake-up strategy corresponding to a target prediction model, the wireless device determines whether the router is a commonly used router based on first identification information in a beacon frame sent by the router. If the router is a commonly used router, the wireless device determines the target prediction model to be a second prediction model, where the second prediction model is a prediction model determined by the wireless device based on historically received time information.

[0063] For example, the second prediction model is stored in the wireless device, and the corresponding second prediction model can be found based on the first identification information. Alternatively, the second prediction model is stored in a cloud server, and the wireless device uploads the first identification information to the cloud server, which can then transmit the corresponding second prediction model back to the wireless device based on the first identification information.

[0064] Specifically, the preset identification information is identification information of a frequently used router. The wireless device determines whether the router is a frequently used router based on the first identification information in the beacon frame sent by the router. If the identification information matches the preset identification information, i.e., the first identification information is identification information of a frequently used router, the wireless device determines that the router is a frequently used router. If the identification information does not match the preset identification information, i.e., the first identification information is not identification information of a frequently used router, the wireless device determines that the router is an uncommon router.

[0065] If the judgment result is a commonly used router, the second prediction model corresponding to the commonly used router is obtained, and the target prediction model is determined to be the second prediction model.

[0066] It should be noted that the step of determining that the target prediction model is the second prediction model can be performed before obtaining the time information of the beacon frame sent by the router. Specifically, before obtaining the time information, the first identification information of the beacon frame is obtained. When the first identification information matches the preset identification information, the router is determined to be a commonly used router, the second prediction model corresponding to the first identification information is used as the target prediction model, and the wake-up operation is performed according to the first wake-up strategy corresponding to the target prediction model. When the first identification information does not match the preset identification information, the router is determined to be an uncommon router, and the time information of the beacon frame sent by the router is continued to be obtained, and multiple first prediction models are established based on the time information, and the target prediction model with the lowest first power consumption among the multiple first prediction models is screened.

[0067] After obtaining the corresponding target prediction model and the first wake-up strategy for the uncommon router, the uncommon router is set as a common router and added to the common list stored locally on the wireless device. If the number of common routers in the common list exceeds the set upper limit, the common router that has not been used for the longest time is deleted from the common list.

[0068] In an embodiment of the present application, the wireless device can determine whether the router is a commonly used router based on the first identification information. If the router is a commonly used router, the target prediction model is determined to be a second prediction model corresponding to the commonly used router, which was obtained historically. Because the second prediction model is the target prediction model determined by the wireless device based on historically obtained time information, by reusing the historically determined second prediction model, the wireless device does not need to re-establish the first prediction model based on the time information, nor does it need to filter the first prediction model with the lowest power consumption among the first prediction models. This reduces the computational complexity of the wireless device's process of determining the target prediction model, reduces the power consumption required by the wireless device during the process, and improves the efficiency of the process of determining the target prediction model.

[0069] The embodiment of the present application provides a method for waking up a wireless device, which can be executed by a wake-up device of the wireless device. In the embodiment of the present application, the wake-up device of the wireless device is used as an example to illustrate the wake-up method of the wireless device.

[0070] In some embodiments of the present application, a wireless device wake-up device 300 is provided, which is applied to the wireless device. The wireless device is connected to a router. Figure 3 FIG. 3 shows a schematic diagram of a structure of a wake-up device 300 for a wireless device according to an embodiment of the present application. Figure 3 As shown, the wake-up device 300 of the wireless device includes:

[0071] An acquisition module 302 is configured to acquire time information sent by the router, where the time information is associated with the sending time of the beacon frame;

[0072] a determination module 304 configured to determine a target prediction model based on the time information, where the target prediction model is a prediction model with the smallest first power consumption determined from a plurality of first prediction models based on the time information, where the first power consumption includes: a second power consumption corresponding to the wireless device running the first prediction model, and a third power consumption corresponding to the wireless device performing a wake-up operation according to a first wake-up strategy, where the first wake-up strategy is a strategy corresponding to the first prediction model;

[0073] The execution module 306 is configured to execute a wake-up operation according to the first wake-up strategy.

[0074] In an embodiment of the present application, based on the time information of the router sending the beacon frame obtained by the wireless device, multiple first prediction models that can accurately predict the time point when the router sends the beacon frame are established, and the model with the lowest first power consumption is selected as the target prediction model. The target prediction model is deployed to the wireless device, so that the wireless device can perform a wake-up operation according to the first wake-up strategy corresponding to the target prediction model, thereby achieving low power consumption while reducing the delay problem caused by the loss of beacon frame monitoring of the wireless device.

[0075] In some embodiments of the present application, the determination module 304 is configured to determine, by using a target prediction model, a first time at which the router sends a beacon frame;

[0076] An acquisition module 302 is configured to acquire a wake-up duration of a first wake-up strategy corresponding to a target prediction model;

[0077] A determination module 304 is configured to determine a second time corresponding to the first wake-up strategy based on the first time and the wake-up duration;

[0078] An execution module 306 is configured to switch the wireless device from a dormant state to an awake state when the wireless device operates to a second moment;

[0079] The execution module 306 is configured to control the wireless device to switch from the awake state to the sleep state when the wireless device is in the awake state for a period of time.

[0080] In the embodiment of the present application, the wireless device can determine the second time at which the wireless device switches from the sleep state to the awake state based on the first time predicted by the target prediction model and the wake-up duration corresponding to the first wake-up policy. The wireless device switches to the awake state at the second time, and then switches back to the sleep state after the awake state lasts for the wake-up duration. This ensures that the wireless device accurately receives the beacon frame sent by the router at the first time, thus avoiding the problem of beacon frame loss.

[0081] In some embodiments of the present application, the acquisition module 302 is used to obtain a preset error range corresponding to the target prediction model;

[0082] The determination module 304 is used to determine the wake-up duration of the first wake-up strategy corresponding to the target prediction model according to the preset error range. The wake-up duration is greater than the reception duration of the beacon frame received from the router and is greater than or equal to the first duration. The first duration is associated with the preset error range.

[0083] In the embodiment of the present application, the minimum wake-up duration (first duration) within the preset error range of the target prediction model is determined based on the preset error range, and the wake-up duration is set to be greater than or equal to the first duration. Since the wake-up duration is associated with the wake-up error, the error of the first wake-up strategy corresponding to the target prediction model can be flexibly adjusted by setting the wake-up duration.

[0084] It should be noted that, when a smaller error is required, the wake-up time is increased, and when power consumption needs to be reduced as much as possible, the wake-up time is decreased.

[0085] In some embodiments of the present application, the wake-up duration is greater than the second duration, and the second duration is a predicted duration for the wireless device to predict the sending time of the beacon frame sent by the router through a target prediction model.

[0086] In an embodiment of the present application, the wake-up duration is greater than the time required for the target prediction model to predict the next beacon frame, ensuring that during the stage of the wireless module wake-up operation, the target prediction model has predicted the time point when the router sends the next beacon frame, thereby enabling the wireless device to continuously predict the router's sending of beacon frames based on the target prediction model, and perform the wake-up operation based on the prediction result and the corresponding first wake-up strategy, further improving the accuracy of the wireless device in performing the wake-up operation.

[0087] In some embodiments of the present application, the acquisition module 302 is configured to acquire first identification information corresponding to the router;

[0088] The acquisition module is further configured to acquire a second prediction model corresponding to the first identification information when the first identification information matches the preset identification information;

[0089] The determination module is further used to determine that the target prediction model is the second prediction model.

[0090] In an embodiment of the present application, the wireless device can determine whether the router is a commonly used router based on the first identification information. If the router is a commonly used router, the target prediction model is determined to be a second prediction model corresponding to the commonly used router, which was obtained historically. Because the second prediction model is the target prediction model determined by the wireless device based on historically obtained time information, by reusing the historically determined second prediction model, the wireless device does not need to re-establish the first prediction model based on the time information, nor does it need to filter the first prediction model with the lowest power consumption among the first prediction models. This reduces the computational complexity of the wireless device's process of determining the target prediction model, reduces the power consumption required by the wireless device during the process, and improves the efficiency of the process of determining the target prediction model.

[0091] The wake-up device of the wireless device in the embodiment of the present application can be an electronic device or a component in the electronic device, such as an integrated circuit or chip. The electronic device can be a terminal or other device other than a terminal. For example, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a mobile internet device (MID), an augmented reality (AR) / virtual reality (VR) device, a robot, a wearable device, an ultra-mobile personal computer (UMPC), a netbook or a personal digital assistant (PDA), etc. It can also be a server, a network attached storage (NAS), a personal computer (PC), a television (TV), a teller machine or a self-service machine, etc., and the embodiment of the present application does not specifically limit it.

[0092] The wake-up device of the wireless device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0093] The wake-up device for a wireless device provided in the embodiment of the present application can implement each process implemented in the above method embodiment, and will not be described again here to avoid repetition.

[0094] Optionally, an embodiment of the present application further provides an electronic device, which includes a wake-up device for a wireless device as in any of the above embodiments, and thus has all the beneficial effects of the wake-up device for a wireless device in any of the embodiments, which will not be elaborated upon here.

[0095] Optionally, an embodiment of the present application further provides an electronic device, Figure 4 FIG. 1 shows a structural block diagram of an electronic device according to an embodiment of the present application. Figure 4 As shown, the electronic device 400 includes a processor 402, a memory 404, and a program or instruction stored in the memory 404 and executable on the processor 402. When the program or instruction is executed by the processor 402, each process of the above-mentioned embodiment of the method for waking up a wireless device is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0096] It should be noted that the electronic devices in the embodiments of the present application include the above-mentioned mobile electronic devices and non-mobile electronic devices.

[0097] Figure 5 A schematic diagram of the hardware structure of an electronic device implementing an embodiment of the present application.

[0098] The electronic device 500 includes but is not limited to components such as a radio frequency unit 501 , a network module 502 , an audio output unit 503 , an input unit 504 , a sensor 505 , a display unit 506 , a user input unit 507 , an interface unit 508 , a memory 509 , and a processor 510 .

[0099] Those skilled in the art will understand that the electronic device 500 may also include a power source (such as a battery) to power each component, and the power source may be logically connected to the processor 510 through a power management system, thereby implementing functions such as charging, discharging, and power consumption management through the power management system. Figure 5 The electronic device structure shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be repeated here.

[0100] The processor 510 is configured to obtain time information sent by the router, where the time information is associated with the sending time of the beacon frame;

[0101] Processor 510 is configured to determine a target prediction model based on the time information, where the target prediction model is a prediction model with the smallest first power consumption determined from a plurality of first prediction models based on the time information, where the first power consumption includes: a second power consumption corresponding to the wireless device running the first prediction model, and a third power consumption corresponding to the wireless device performing a wake-up operation according to a first wake-up strategy, where the first wake-up strategy is a strategy corresponding to the first prediction model;

[0102] The processor 510 is configured to perform a wake-up operation according to a first wake-up strategy.

[0103] In an embodiment of the present application, based on the time information of the router sending the beacon frame obtained by the wireless device, multiple first prediction models that can accurately predict the time point when the router sends the beacon frame are established, and the model with the lowest first power consumption is selected as the target prediction model. The target prediction model is deployed to the wireless device, so that the wireless device can perform a wake-up operation according to the first wake-up strategy corresponding to the target prediction model, thereby achieving low power consumption while reducing the delay problem caused by the loss of beacon frame monitoring of the wireless device.

[0104] Further, the processor 510 is configured to determine, by using a target prediction model, a first moment at which the router sends a beacon frame;

[0105] Processor 510 is configured to obtain a wake-up duration of a first wake-up strategy corresponding to a target prediction model;

[0106] Processor 510, configured to determine a second time corresponding to the first wake-up strategy according to the first time and the wake-up duration;

[0107] The processor 510 is configured to switch the wireless device from a dormant state to an awake state when the wireless device operates at a second moment;

[0108] The processor 510 is configured to control the wireless device to switch from the awake state to the sleep state when the wireless device is in the awake state for a period of time.

[0109] In the embodiment of the present application, the wireless device can determine the second time at which the wireless device switches from the sleep state to the awake state based on the first time predicted by the target prediction model and the wake-up duration corresponding to the first wake-up policy. The wireless device switches to the awake state at the second time, and then switches back to the sleep state after the awake state lasts for the wake-up duration. This ensures that the wireless device accurately receives the beacon frame sent by the router at the first time, thus avoiding the problem of beacon frame loss.

[0110] Furthermore, the processor 510 is configured to obtain a preset error range corresponding to the target prediction model;

[0111] Processor 510 is used to determine the wake-up duration of the first wake-up strategy corresponding to the target prediction model based on a preset error range, where the wake-up duration is greater than the reception duration of the beacon frame received from the router and is greater than or equal to the first duration, and the first duration is associated with the preset error range.

[0112] In the embodiment of the present application, the minimum wake-up duration (first duration) within the preset error range of the target prediction model is determined based on the preset error range, and the wake-up duration is set to be greater than or equal to the first duration. Since the wake-up duration is associated with the wake-up error, the error of the first wake-up strategy corresponding to the target prediction model can be flexibly adjusted by setting the wake-up duration.

[0113] It should be noted that, when a smaller error is required, the wake-up time is increased, and when power consumption needs to be reduced as much as possible, the wake-up time is decreased.

[0114] Furthermore, the wake-up duration is greater than the second duration, and the second duration is a predicted duration for the wireless device to predict the sending time of the beacon frame sent by the router through the target prediction model.

[0115] In an embodiment of the present application, the wake-up duration is greater than the time required for the target prediction model to predict the next beacon frame, ensuring that during the stage of the wireless module wake-up operation, the target prediction model has predicted the time point when the router sends the next beacon frame, thereby enabling the wireless device to continuously predict the router's sending of beacon frames based on the target prediction model, and perform the wake-up operation based on the prediction result and the corresponding first wake-up strategy, further improving the accuracy of the wireless device in performing the wake-up operation.

[0116] In some embodiments of the present application, the processor 510 is configured to obtain first identification information corresponding to the router;

[0117] Processor 510, configured to obtain a second prediction model corresponding to the first identification information when the first identification information matches the preset identification information;

[0118] The processor 510 is configured to determine that the target prediction model is the second prediction model.

[0119] In an embodiment of the present application, the wireless device can determine whether the router is a commonly used router based on the first identification information. If the router is a commonly used router, the target prediction model is determined to be a second prediction model corresponding to the commonly used router, which was obtained historically. Because the second prediction model is the target prediction model determined by the wireless device based on historically obtained time information, by reusing the historically determined second prediction model, the wireless device does not need to re-establish the first prediction model based on the time information, nor does it need to filter the first prediction model with the lowest power consumption among the first prediction models. This reduces the computational complexity of the wireless device's process of determining the target prediction model, reduces the power consumption required by the wireless device during the process, and improves the efficiency of the process of determining the target prediction model.

[0120] It should be understood that in an embodiment of the present application, the input unit 504 may include a graphics processing unit (GPU) 5041 and a microphone 5042, and the graphics processor 5041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 506 may include a display panel 5061, and the display panel 5061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 507 includes a touch panel 5071 and at least one of other input devices 5072. The touch panel 5071 is also called a touch screen. The touch panel 5071 may include two parts: a touch detection device and a touch controller. Other input devices 5072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and an operating stick, which will not be repeated here.

[0121] The memory 509 can be used to store software programs and various data. The memory 509 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, applications or instructions required for at least one function (such as a sound playback function, an image playback function, etc.). In addition, the memory 509 may include a volatile memory or a non-volatile memory, or the memory 509 may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM), and a direct memory bus random access memory (DRRAM). The memory 509 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0122] Processor 510 may include one or more processing units. Optionally, processor 510 integrates an application processor and a modem processor. The application processor primarily handles operations related to the operating system, user interface, and application programs, while the modem processor primarily processes wireless communication signals, such as a baseband processor. It is understood that the modem processor may not be integrated into processor 510.

[0123] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above-mentioned method embodiment are implemented and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0124] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0125] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned wireless device wake-up method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0126] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0127] An embodiment of the present application provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the above-mentioned embodiment of the wake-up method for a wireless device, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0128] It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, it should be noted that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0129] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of each embodiment of the present application.

[0130] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

Claims

1. A method for waking up a wireless device, used for a wireless device, characterized in that: The wireless device is connected to a router, and the waking-up method of the wireless device includes: Obtaining first identification information corresponding to the router; When the first identification information matches the preset identification information, obtaining a second prediction model corresponding to the first identification information, the preset identification information corresponds to a common router, and the common router corresponds to the second prediction model; Determining the target prediction model to be the second prediction model; When the first identification information does not match the preset identification information, acquiring time information of the beacon frame sent by the router, where the time information is associated with the sending time of the beacon frame; Determining a target prediction model based on the time information, the target prediction model being a prediction model with a first minimum power consumption determined from a plurality of first prediction models based on the time information, the first power consumption comprising: a second power consumption corresponding to the wireless device running the first prediction model, and a third power consumption corresponding to the wireless device performing a wake-up operation according to a first wake-up strategy, wherein the first prediction model is used to predict the router sending the beacon frame, and the first wake-up strategy is a strategy corresponding to the first prediction model; Perform a wake-up operation according to the first wake-up strategy corresponding to the target prediction model.

2. The method for waking up a wireless device according to claim 1, wherein: Before executing the wake-up operation according to the first wake-up strategy corresponding to the target prediction model, the method includes: Determining, by means of the target prediction model, a first time at which the router sends the beacon frame; Obtaining the wake-up duration of the first wake-up strategy corresponding to the target prediction model; Determining a second time corresponding to the first wake-up strategy according to the first time and the wake-up duration; The performing a wake-up operation according to the first wake-up strategy corresponding to the target prediction model includes: When the wireless device runs to the second moment, the wireless device switches from a dormant state to an awake state; When the wireless device is in the awake state for the awake time period, the wireless device is controlled to switch from the awake state to the sleep state.

3. The method for waking up a wireless device according to claim 2, wherein: The acquiring the wake-up duration of the first wake-up strategy corresponding to the target preset model includes: Obtaining a preset error range corresponding to the target prediction model; According to the preset error range, the wake-up duration of the first wake-up strategy corresponding to the target prediction model is determined, the wake-up duration is greater than the reception duration of the beacon frame from the router, and is greater than or equal to the first duration, and the first duration is associated with the preset error range.

4. A wireless device wake-up device, used for a wireless device, characterized in that: The wireless device is connected to a router, and the device's wake-up device includes: An acquisition module, configured to acquire first identification information corresponding to the router; The acquisition module is further configured to acquire a second prediction model corresponding to the first identification information when the first identification information matches preset identification information, the preset identification information corresponds to a common router, and the common router corresponds to the second prediction model; A determination module, configured to determine that the target prediction model is the second prediction model; The acquisition module is further configured to, when the first identification information does not match the preset identification information, acquire time information of when the router sends the beacon frame, where the time information is associated with the sending moment of the beacon frame; The determination module is further configured to determine a target prediction model based on the time information, the target prediction model being a prediction model with a first minimum power consumption determined from a plurality of first prediction models based on the time information, the first power consumption comprising: a second power consumption corresponding to the wireless device running the first prediction model, and a third power consumption corresponding to the wireless device performing a wake-up operation according to a first wake-up strategy, wherein the first prediction model is used to predict the router sending the beacon frame, and the first wake-up strategy is a strategy corresponding to the first prediction model; An execution module is configured to execute a wake-up operation according to the first wake-up strategy.

5. The wireless device wake-up device according to claim 4, characterized in that The determining module is configured to determine, by using the target prediction model, the first moment at which the router sends the beacon frame; The acquisition module is used to obtain the wake-up duration of the first wake-up strategy corresponding to the target prediction model; The determining module is configured to determine a second time corresponding to the first wake-up strategy according to the first time and the wake-up duration; The execution module is configured to switch the wireless device from a dormant state to an awake state when the wireless device runs to the second moment; The execution module is configured to control the wireless device to switch from the awake state to the sleep state when the wireless device is in the awake state for the awake time duration.

6. The wireless device wake-up device according to claim 5, characterized in that The acquisition module is used to obtain a preset error range corresponding to the target prediction model; The determination module is used to determine the wake-up duration of the first wake-up strategy corresponding to the target prediction model based on the preset error range, the wake-up duration is greater than the reception duration of the beacon frame from the router, and is greater than or equal to the first duration, and the first duration is associated with the preset error range.

7. An electronic device, characterized in that: include: A processor and a memory, wherein the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, the steps of the wake-up method of the wireless device according to any one of claims 1 to 3 are implemented.

8. A readable storage medium having a program or instruction stored thereon, characterized in that: When the program or instruction is executed by a processor, the steps of the method for waking up a wireless device according to any one of claims 1 to 3 are implemented.

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