Dynamic Adjustment Method for the Number of Receiving Antennas of a Terminal Device and a Communication Terminal Device

Abstract

The present invention discloses a method for dynamically adjusting the number of receiving antennas of a terminal device and a communication terminal device. The method includes: the terminal device obtains current status data, where the status data includes the application scenario of the application programs currently running in the foreground of the terminal device, the interaction frequency with the user in this application scenario, and the current communication signal status; processes the status data through a prediction model to obtain a prediction result, where the prediction result includes the number of antennas adapted to the current state of the terminal device; and adjusts the number of receiving antennas of the terminal device currently in the working state according to the prediction result. The above dynamic adjustment method of the present invention, on the premise of ensuring communication quality, intelligently optimizes the antenna configuration according to the actual application scenario and interaction frequency of the user, thereby significantly reducing the power consumption of the terminal device, improving the energy use efficiency, effectively improving the stability and response speed of communication at the same time, and optimizing the user experience in high-demand application scenarios.

Description

Technical Field

[0001] The present invention relates to the technical field of terminal device communication, and particularly to a method for dynamically adjusting the number of receiving antennas of a terminal device and a communication terminal device. Background Art

[0002] In the current mobile communication field, the number of receiving antennas directly affects the communication efficiency and energy consumption of terminal devices. In existing technologies, multi-antenna receiving systems can improve signal reception performance, enhance signal stability, and expand the coverage area. However, the main disadvantage of such systems is relatively high power consumption, which is particularly critical in mobile devices because their energy supply is usually limited.

[0003] In current solutions, mobile phone chip platforms adjust the number of antennas according to signal quality (such as RSRP and SNR) to make a trade-off between power consumption and performance. These optimizations are mainly carried out at the modem level, such as switching between 2Rx (two receiving antennas) and 4Rx (four receiving antennas). However, this method only considers the channel characteristics at the physical level and does not involve the actual usage behavior of users in different application scenarios, resulting in inflexible and inaccurate adjustment responses. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for dynamically adjusting the number of receiving antennas of a terminal device and a communication terminal device that adaptively adjusts the number of antennas according to the application scenario of the application program of the terminal device and the degree of interaction with the user.

[0005] To achieve the above purpose, the present invention provides a method for dynamically adjusting the number of receiving antennas of a terminal device, which includes:

[0006] The terminal device obtains current status data, where the status data includes the application scenario of the application program currently running in the foreground of the terminal device, the interaction frequency with the user in this application scenario, and the current communication signal status;

[0007] Process the status data through a prediction model with a neural network architecture constructed according to sample data to obtain a prediction result, where the prediction result includes the number of antennas adapted to the current state of the terminal device;

[0008] Adjust the number of receiving antennas of the terminal device currently in the working state according to the prediction result

[0009] Preferably, after adjusting the number of receiving antennas of the terminal device currently in the working state, start a first timer, and stop adjusting the data of the receiving antennas of the terminal device before the first timer overflows.

[0010] Preferably, the communication signal state includes the signal strength and signal-to-noise ratio of the communication signal.

[0011] Preferably, a first threshold corresponding to the signal strength is set in the prediction model. When the current signal strength of the terminal device is less than the first threshold, the number of antennas in the prediction result is the maximum value.

[0012] Preferably, a second threshold corresponding to the signal-to-noise ratio is set in the prediction model. When the current signal-to-noise ratio of the terminal device is less than the second threshold, the number of antennas in the prediction result is the maximum value.

[0013] Preferably, the communication signal state further includes the packet loss rate and / or delay information of the communication signal.

[0014] Preferably, when the application scenario is video, the communication signal state includes the signal strength, the signal-to-noise ratio, and the packet loss rate.

[0015] When the application scenario is live broadcast, the communication signal state includes the signal strength, the signal-to-noise ratio, and the network downlink transmission rate.

[0016] When the application scenario is a game, the communication signal state includes the signal strength, the signal-to-noise ratio, and the delay information.

[0017] The present invention also discloses a communication terminal device, which includes a processor and a plurality of receiving antennas. The processor adjusts the working states of the plurality of receiving antennas based on the dynamic adjustment method described above.

[0018] The present invention also discloses a communication terminal device, which includes:

[0019] One or more processors;

[0020] A memory;

[0021] And one or more programs, where one or more programs are stored in the memory and are configured to be executed by the one or more processors. The programs include instructions for executing the dynamic adjustment method described above.

[0022] The present invention also discloses a computer-readable storage medium, which includes a computer program that can be executed by a processor to complete the dynamic adjustment method described above.

[0023] Compared with the prior art, the dynamic adjustment method provided by the above technical solution of the present invention intelligently optimizes the antenna configuration according to the actual application scenario and interaction frequency of the user on the premise of ensuring communication quality, thereby significantly reducing the power consumption of the terminal device and improving the energy use efficiency. At the same time, through refined scenario recognition and antenna adjustment strategies, the stability and response speed of communication are effectively improved, the user experience in high-demand application scenarios is optimized, the intelligent balance between performance and power consumption is achieved, and the overall performance and user satisfaction of the communication terminal device are enhanced. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flowchart of the execution of the dynamic adjustment method in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0025] To describe in detail the technical content, structural features, achieved objectives and effects of the present invention, the following is described in detail in conjunction with the embodiments and with reference to the drawings.

[0026] This embodiment discloses a method for dynamically adjusting the number of receiving antennas of a terminal device, which is used to adjust the number of receiving antennas of the terminal device in the startup state. It can be seen that the terminal device in this embodiment is at least configured with two receiving antennas, and the terminal device in this embodiment and the following embodiments are described by taking four as an example.

[0027] Such as Figure 1 , the dynamic adjustment method in this embodiment includes the following steps:

[0028] S1: The terminal device obtains the current status data, and the status data includes the application scenario of the application program currently running in the foreground of the terminal device, the interaction frequency with the user in this application scenario, and the current communication signal status. It should be noted that the interaction frequency includes the frequency of sliding the screen during the user operation.

[0029] S2: Process the status data through a prediction model with a neural network architecture constructed according to the sample data to obtain a prediction result, and the prediction result includes the number of antennas adapted to the current status of the terminal device.

[0030] S3: Adjust the number of receiving antennas of the terminal device currently in the working state according to the prediction result. For example, if the currently activated receiving antennas of the terminal device are four, and the number of antennas given by the prediction model is two, then two terminal antennas are turned off. Another example is that if the currently activated receiving antennas of the terminal device are two, and the number of antennas given by the prediction model is four, then two terminal antennas are added.

[0031] The dynamic adjustment method provided in this embodiment dynamically adjusts the number of receiving antennas by comprehensively considering the user's interaction frequency and the application scenario requirements. This method not only takes into account the physical signal state but also takes into account the user's behavior patterns, such as the screen sliding frequency, etc., so as to more accurately match the power consumption and performance requirements of the terminal.

[0032] In addition, scene recognition technology is introduced, and by classifying the requirements of different applications, the antenna adjustment strategy is further refined. This scene recognition ability makes the antenna adjustment more accurate and faster in response, thus optimizing the user experience and device performance.

[0033] On the other hand, after adjusting the number of receiving antennas of the terminal device currently in the working state, start the first timer, and before the first timer overflows, stop adjusting the data of the receiving antennas of the terminal device.

[0034] In this embodiment, through the setting of the first timer, it is possible to effectively avoid the system instability and additional power consumption of the terminal device caused by frequent adjustment of the number of receiving antennas. Specifically, after starting the first timer, stop adjusting the data of the receiving antennas before the timer overflows, which helps to stabilize the receiving state of the terminal device, maintain the consistency of the antenna configuration within a certain period of time, thereby reducing the power consumption fluctuation and potential communication interruption caused by excessive adjustment, and enhancing the reliability of the system and the coherence of the user experience in the terminal device.

[0035] On the other hand, the communication signal state includes the signal strength and signal-to-noise ratio of the communication signal. That is to say, the prediction model also gives the optimized number of receiving antennas with reference to the current signal strength and signal-to-noise ratio of the terminal device, so as to effectively ensure the communication quality of the terminal device.

[0036] In this regard, a first threshold corresponding to the signal strength and a second threshold corresponding to the signal-to-noise ratio are set in the prediction model.

[0037] When the current signal strength of the terminal device is less than the first threshold, the number of antennas in the prediction result is the maximum value.

[0038] When the current signal-to-noise ratio of the terminal device is less than the second threshold, the number of antennas in the prediction result is the maximum value.

[0039] In this embodiment, by setting a threshold value related to the communication signal status in the prediction model, the number of receiving antennas can be automatically increased when the signal conditions are poor to ensure the communication quality. Specifically, by setting the thresholds for signal strength and signal-to-noise ratio, when the actual signal strength or signal-to-noise ratio is lower than the set threshold, the prediction result will recommend the use of the maximum number of receiving antennas. This adjustment can provide stronger reception capabilities when the signal environment is not ideal, thereby reducing the risk of data loss and communication interruption, and significantly improving the performance and reliability of terminal equipment in areas with weak signals, especially suitable for mobile communication needs in complex environments or marginal coverage areas.

[0040] Furthermore, the communication signal status also includes the packet loss rate and / or delay information of the communication signal, so as to provide better prediction results for application scenarios with high requirements on the packet loss rate and delay information.

[0041] Specifically, when the application scenario is video, the communication signal status includes signal strength, signal-to-noise ratio, and packet loss rate;

[0042] When the application scenario is live broadcast, the communication signal status includes signal strength, signal-to-noise ratio, and network downlink transmission rate;

[0043] When the application scenario is gaming, the communication signal status includes signal strength, signal-to-noise ratio, and delay information.

[0044] In addition, for the prediction model, the training process is as follows:

[0045] 1. Data Collection

[0046] 1.1 First, collect data covering a variety of application scenarios, such as screen sliding frequency, signal strength (RSRP), signal-to-noise ratio (SNR), etc. In addition, for specific application scenarios (such as video, live broadcast, games, etc.), collect specific parameters such as packet loss rate, downlink transmission rate, round-trip time (RTT), etc.

[0047] 1.2 The collected data must be tested and verified on the existing network and experimental network to ensure the accuracy and reliability of the data, that is, to ensure that the terminal device does not lag under these standard data used for training.

[0048] 2. Data Preprocessing

[0049] 2.1 Clean the data and remove the records with incomplete parameters to obtain standard data.

[0050] 2.2 Format the data to fit the training model, which usually includes regularization and possible feature engineering to improve the model's training results and predictive ability.

[0051] 3. Model construction and training

[0052] 3.1 Use deep learning frameworks (such as TensorFlow or Keras) to build a Recurrent Neural Network (RNN) model. RNN is a model suitable for processing time series data and can effectively process and predict user behaviors and signal states that change over time.

[0053] 3.2 Divide the dataset, generally using 70% as the training set and 30% as the test set.

[0054] 3.3 Set specific thresholds in the model, such as thresholds for signal strength and signal-to-noise ratio. When the signal strength or signal-to-noise ratio is below these thresholds, the model will recommend using the maximum number of receiving antennas to ensure communication quality.

[0055] 4. Evaluation and Optimization:

[0056] 4.1 Evaluate the model on a test machine, setting the target prediction accuracy (e.g., >85%) as the criterion for the effectiveness of the model.

[0057] 4.2 Adjust the model parameters according to the test results and optimize the model to improve the prediction accuracy and response speed.

[0058] 5. Deployment and Application:

[0059] 5.1 Deploy the trained model on the terminal device so that it can dynamically adjust the number of receiving antennas according to real-time data.

[0060] 5.2 Configure a timer to prevent frequent adjustment of the number of receiving antennas in a short period of time, thus maintaining the stability of the system and reducing power consumption.

[0061] 5.1 This prediction model based on deep learning can accurately adjust the number of receiving antennas according to the actual behaviors of users and the network environment, thereby optimizing the device performance and user experience.

[0062] In summary, the present invention discloses a method for dynamically adjusting the number of receiving antennas of a terminal device, which dynamically adjusts the number of receiving antennas by comprehensively considering the interaction frequency of users and the requirements of application scenarios. This method not only takes into account the physical signal state but also takes into account the user's behavior patterns, such as the screen sliding frequency, etc., so as to more accurately match the power consumption and performance requirements of the terminal.

[0063] For example, according to the screen sliding frequency of the user in different applications and the communication signal states in various scenarios, use an AI prediction model to predict the number of antennas most suitable for the current state. Such intelligent adjustment can significantly reduce power consumption without sacrificing connection quality, especially in low-frequency interaction scenarios where high-performance communication is not required.

[0064] In addition, this solution also introduces scene recognition technology. By classifying the requirements of different applications, such as the high requirement for packet loss rate in WeChat video applications or the sensitivity to latency in game applications, the antenna adjustment strategy is further refined. This scene recognition ability makes the antenna adjustment more accurate and responsive, thus optimizing the user experience and device performance.

[0065] Generally speaking, by introducing the AI multi-scene prediction model to dynamically adjust the number of receiving antennas, the present invention not only solves the problem of insufficient perception of user behavior in traditional methods, but also can intelligently balance power consumption and performance according to the different requirements of specific application scenarios, significantly improving the overall efficiency and user satisfaction of mobile communication devices.

[0066] In another preferred embodiment of the present invention, a communication terminal device is also disclosed, which includes a processor and a plurality of receiving antennas, and the processor adjusts the working states of the plurality of receiving antennas based on the above dynamic adjustment method.

[0067] The present invention also discloses another communication terminal device, which includes one or more processors, a memory, and one or more programs, wherein one or more programs are stored in the memory and are configured to be executed by the one or more processors. The programs include instructions for executing the dynamic adjustment method as described above. The processor can be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, for executing relevant programs to implement the functions required by the functional modules in the communication terminal device of the embodiments of the present application, or to execute the dynamic adjustment method of the method embodiments of the present application.

[0068] The present invention also discloses a computer-readable storage medium, which includes a computer program that can be executed by a processor to complete the dynamic adjustment method as described above. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more integrated available media. The available medium can be a read-only memory (ROM), a random access memory (RAM), a magnetic medium, such as a floppy disk, a hard disk, a magnetic tape, a magnetic disk, or an optical medium, such as a digital versatile disc (DVD), or a semiconductor medium, such as a solid state disk (SSD), etc.

[0069] The embodiments of the present application also disclose a computer program product or a computer program. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device executes the above dynamic adjustment method.

[0070] The above-disclosed are only the preferred embodiments of the present invention. Of course, the scope of rights of the present invention cannot be limited thereby. Therefore, equivalent changes made according to the scope of the patent application of the present invention still fall within the scope covered by the present invention.

Claims

1. A method for dynamically adjusting the number of receiving antennas of a terminal device, characterized in that: include: The terminal device acquires current status data, wherein the status data includes an application scenario of an application currently running in the foreground of the terminal device, a frequency of interaction with a user in the application scenario, and a current communication signal status; Processing the state data by a prediction model having a neural network architecture constructed according to the sample data to obtain a prediction result, wherein the prediction result includes the number of antennas adapted to the current state of the terminal device; Adjusting the number of receiving antennas currently in operation of the terminal device according to the prediction result; The communication signal status includes the signal strength and signal-to-noise ratio of the communication signal; A first threshold corresponding to the signal strength is set in the prediction model, and when the current signal strength of the terminal device is less than the first threshold, the number of antennas in the prediction result is a maximum value; A second threshold corresponding to the signal-to-noise ratio is set in the prediction model. When the current signal-to-noise ratio of the terminal device is less than the second threshold, the number of antennas in the prediction result is a maximum value.

2. The method for dynamically adjusting the number of receiving antennas of a terminal device according to claim 1, characterized in that: After adjusting the number of receiving antennas of the terminal device that are currently in working state, start the first timer, and stop adjusting the data of the receiving antennas of the terminal device before the first timer overflows.

3. The method for dynamically adjusting the number of receiving antennas of a terminal device according to claim 1, characterized in that: The communication signal status also includes the packet loss rate and / or delay information of the communication signal.

4. The method for dynamically adjusting the number of receiving antennas of a terminal device according to claim 3, characterized in that: When the application scenario is video, the communication signal status includes the signal strength, the signal-to-noise ratio, and the packet loss rate; When the application scenario is live broadcast, the communication signal status includes the signal strength, the signal-to-noise ratio, and the network downlink transmission rate; When the application scenario is a game, the communication signal status includes the signal strength, the signal-to-noise ratio and delay information.

5. A communication terminal device, characterized in that: The invention comprises a processor and a plurality of receiving antennas, wherein the processor adjusts the working states of the plurality of receiving antennas based on the dynamic adjustment method according to any one of claims 1 to 4.

6. A communication terminal device, characterized in that: include: one or more processors; Memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs comprising instructions for executing the dynamic adjustment method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: The invention comprises a computer program, wherein the computer program can be executed by a processor to implement the dynamic adjustment method according to any one of claims 1 to 4.

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