Antenna mode selection method and apparatus, electronic device, and storage medium

Abstract

The application relates to the technical field of communication, in particular to an antenna mode selection method and device, electronic equipment and storage medium, comprising the following steps: updating a current channel probability model of a client based on current parameters of a channel environment of the client; combining configuration parameters of a target wireless device and the updated current channel probability model, estimating the throughput of at least one antenna mode of the target wireless device, and selecting an antenna mode with the maximum throughput as a target antenna mode of the client. Thus, by pre-modeling the channel environment and obtaining the target antenna mode with the maximum throughput corresponding to the current parameters of the channel environment as the target antenna mode of the client, the problems that, in the related art, the optimal antenna mode is obtained by using a fixed rate file and a timing or conditional detection method, the optimization time is long, the adjustment cannot be made in time according to the channel environment or the client, and multiple threshold conditions need to be set are solved, and the communication performance is effectively improved.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to an antenna mode selection method, apparatus, electronic device and storage medium. Background Technology

[0002] In wireless communication, when the channel environment changes, the client's location changes, or the polarization mode of the communication antenna is adjusted, timely switching to the appropriate antenna mode can greatly improve the overall communication performance.

[0003] In related technologies, when selecting an antenna mode, the rate range is usually fixed first, and then each antenna mode is traversed to obtain quality metrics such as throughput or Received Signal Strength Indicator (RSSI) for each antenna mode. Then, the current PER (Packet Error Rate) and EVM (Error Vector Magnitude) are judged by thresholds to determine whether to readjust the rate and traverse until the convergence condition is met, and the antenna mode with the best performance is selected. At the same time, timed detection or threshold condition detection is set.

[0004] However, the antenna mode selection of related technologies has the following problems: (1) During the traversal of a fixed rate range, there may be multiple directions with similar packet error rates or signal strength indicators, which cannot be well distinguished; (2) When the environment or the client changes between two detection intervals, the timing detection or threshold condition detection cannot be detected in time and the antenna can not be adjusted; (3) Multiple threshold conditions need to be set, and the wireless environment is complex and changeable, making it difficult to find a unified and effective threshold, which needs to be solved urgently. Summary of the Invention

[0005] This application provides an antenna mode selection method, apparatus, electronic device, and storage medium, which solves the problems in related technologies that use fixed rate ranges and timed or conditional detection methods to obtain the optimal antenna mode, resulting in long optimization time, inability to make timely adjustments according to changes in the channel environment or client, and the need to set multiple threshold conditions, thus effectively improving communication performance.

[0006] The first aspect of this application provides an antenna mode selection method, comprising the following steps: obtaining current parameters of the channel environment of a client; updating the current channel probability model of the client based on the current parameters of the channel environment; combining the configuration parameters of the target wireless device and the updated current channel probability model to estimate the throughput of at least one antenna mode of the target wireless device, and selecting the antenna mode with the highest throughput as the target antenna mode of the client.

[0007] Optionally, before updating the current channel probability model of the client based on the current parameters of the channel environment, the method further includes: obtaining the initial channel environment parameters of the client; obtaining an initial channel model based on the initial channel environment parameters; and updating the initial channel model based on a plurality of preset posterior probability values ​​to obtain the current channel probability model.

[0008] Optionally, obtaining the initial channel model based on the initial channel environment parameters includes: determining the received signal strength range and initial step size of the client based on the initial channel environment parameters, and obtaining an initial received signal strength quantization result based on the received signal strength range and the initial step size; determining the transmission rate of the client based on the initial channel environment parameters, and mapping the transmission rate according to a preset modulation and coding scheme table to obtain an initial transmission rate quantization result; and combining the initial received signal strength quantization result and the initial transmission rate quantization result to obtain the initial channel model.

[0009] Optionally, after selecting the antenna mode with the highest throughput as the target antenna mode for the client, the method further includes: normalizing the preset multiple posterior probability values ​​based on a preset normalization strategy; and updating the initial channel model according to the normalized preset multiple posterior probability values ​​to obtain a new current channel probability model.

[0010] Optionally, the step of combining the configuration parameters of the target wireless device and the updated current channel probability model to estimate the throughput of at least one antenna mode of the target wireless device includes: obtaining the current received signal strength quantization result and the current transmission rate quantization result based on the configuration parameters of the target wireless device and the updated current channel probability model; and estimating the throughput of at least one antenna mode of the target wireless device based on the received signal strength quantization result and the current transmission rate quantization result according to a preset conditional probability formula.

[0011] Optionally, the configuration parameters of the target wireless device include the antenna modes and / or rate settings supported by the target wireless device.

[0012] A second aspect of this application provides an antenna mode selection device, comprising: an acquisition module for acquiring current parameters of a client's channel environment; an update module for updating the client's current channel probability model based on the current parameters of the channel environment; and a selection module for combining configuration parameters of a target wireless device and the updated current channel probability model to estimate the throughput of at least one antenna mode of the target wireless device, and selecting the antenna mode with the highest throughput as the target antenna mode for the client.

[0013] Optionally, before updating the current channel probability model of the client based on the current parameters of the channel environment, the updating module is further configured to: obtain the initial channel environment parameters of the client; obtain an initial channel model based on the initial channel environment parameters; and update the initial channel model based on a plurality of preset posterior probability values ​​to obtain the current channel probability model.

[0014] Optionally, the update module is further configured to: determine the received signal strength range and initial step size of the client based on the initial channel environment parameters, and obtain an initial received signal strength quantization result based on the received signal strength range and the initial step size; determine the transmission rate of the client based on the initial channel environment parameters, and map the transmission rate according to a preset modulation and coding scheme table to obtain an initial transmission rate quantization result; and combine the initial received signal strength quantization result and the initial transmission rate quantization result to obtain the initial channel model.

[0015] Optionally, after selecting the antenna mode with the highest throughput as the target antenna mode for the client, the selection module is further configured to: normalize the preset multiple posterior probability values ​​according to a preset normalization strategy; update the initial channel model according to the preset multiple posterior probability values ​​after normalization to obtain a new current channel probability model.

[0016] Optionally, the selection module is further configured to: obtain the current received signal strength quantization result and the current transmission rate quantization result based on the configuration parameters of the target wireless device and the updated current channel probability model; and estimate the throughput of at least one antenna mode of the target wireless device based on the received signal strength quantization result and the current transmission rate quantization result according to a preset conditional probability formula.

[0017] Optionally, the configuration parameters of the target wireless device include the antenna modes and / or rate settings supported by the target wireless device.

[0018] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the antenna mode selection method as described in the above embodiments.

[0019] A fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the antenna mode selection method as described in the above embodiments.

[0020] This application updates the client's current channel probability model based on the current parameters of the channel environment. Combining the target wireless device's configuration parameters with the updated current channel probability model, it estimates the throughput of at least one antenna mode of the target wireless device and selects the antenna mode with the highest throughput as the client's target antenna mode. Therefore, by pre-modeling the channel environment and obtaining the corresponding antenna mode with the highest throughput as the client's target antenna mode based on the current parameters of the channel environment, this solves the problems of related technologies that rely on fixed rate ranges and timed or conditional detection methods to obtain the optimal antenna mode, resulting in long optimization times, inability to make timely adjustments based on changes in the channel environment or the client, and the need to set multiple threshold conditions. This effectively improves communication performance.

[0021] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0022] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0023] Figure 1 This is a flowchart of an antenna mode selection method provided according to an embodiment of this application;

[0024] Figure 2 This is a flowchart of an antenna mode selection method according to an embodiment of this application;

[0025] Figure 3 This is an example diagram of an antenna mode selection device according to an embodiment of this application;

[0026] Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0027] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0028] The antenna mode selection method, apparatus, electronic device, and storage medium of this application are described below with reference to the accompanying drawings. Addressing the issues raised in the background section regarding the related technologies that rely on fixed rate ranges and timed or conditional detection methods to obtain the optimal antenna mode, resulting in long optimization times, inability to adjust in a timely manner according to changes in the channel environment or client, and the need to set multiple threshold conditions, this application provides an antenna mode selection method. In this method, the current channel probability model of the client is updated based on the current parameters of the channel environment. Combining the configuration parameters of the target wireless device with the updated current channel probability model, the throughput of at least one antenna mode of the target wireless device is estimated, and the antenna mode with the highest throughput is selected as the target antenna mode for the client. Therefore, by pre-modeling the channel environment and obtaining the corresponding antenna mode with the highest throughput as the target antenna mode for the client based on the current parameters of the channel environment, the problems of long optimization times, inability to adjust in a timely manner according to changes in the channel environment or client, and the need to set multiple threshold conditions in the related technologies based on fixed rate ranges and timed or conditional detection methods are solved, effectively improving communication performance.

[0029] Specifically, Figure 1 This is a flowchart illustrating an antenna mode selection method provided in an embodiment of this application.

[0030] like Figure 1 As shown, the antenna mode selection method includes the following steps:

[0031] In step S101, the current parameters of the client's channel environment are obtained.

[0032] The current parameters of the channel environment include the client-supported rate, Received Signal Strength Index (RSSI), and Packet Error Rate (PER).

[0033] It should be understood that there are many methods to obtain the current parameters of the client's channel environment.

[0034] As one possible implementation, embodiments of this application may employ a deterministic parameter estimation algorithm to obtain the current parameters of the client's channel environment.

[0035] As another possible implementation, embodiments of this application may employ a parameter subspace estimation algorithm to obtain the current parameters of the client's channel environment.

[0036] It should be noted that the above-described methods for obtaining the current parameters of the client's channel environment through parameter estimation algorithms and parameter subspace estimation algorithms are merely illustrative and are not intended to limit the present invention. Those skilled in the art can select different channel parameter acquisition algorithms to obtain the current parameters of the client's channel environment according to actual conditions. To avoid redundancy, detailed descriptions are not provided here.

[0037] In step S102, the client's current channel probability model is updated based on the current parameters of the channel environment.

[0038] To facilitate understanding of this application by those skilled in the art, the current method of generating the channel probability model will be described in detail first.

[0039] Preferably, in some embodiments, before updating the client's current channel probability model based on the current parameters of the channel environment, the method further includes: obtaining the client's initial channel environment parameters; obtaining an initial channel model based on the initial channel environment parameters; and updating the initial channel model based on a plurality of preset posterior probability values ​​to obtain the current channel probability model.

[0040] The initial channel environment parameters are the client's initial parameters, such as the initial supported rate (limiting the transmission rate), initial RSSI, and initial PER. The initial channel model can be obtained based on the initial channel environment parameters in the following way:

[0041] As one possible implementation, in some embodiments, obtaining the initial channel model based on initial channel environment parameters includes: determining the received signal strength range and initial step size of the received signal based on the initial channel environment parameters, and obtaining the initial received signal strength quantization result based on the received signal strength range and initial step size; determining the transmission rate of the client based on the initial channel environment parameters, and mapping the transmission rate according to a preset modulation and coding scheme table to obtain the initial transmission rate quantization result; and combining the initial received signal strength quantization result and the initial transmission rate quantization result to obtain the initial channel model.

[0042] The received signal strength range can be a range preset by the user, a range obtained through a limited number of experiments, or a range obtained through a limited number of computer simulations. The initial step size of the received signal can be a step size preset by the user, a step size obtained through a limited number of experiments, or a step size obtained through a limited number of computer simulations. In other words, both the received signal strength range and the initial step size of the received signal can be customized by those skilled in the art according to the actual situation.

[0043] It should be understood that when obtaining the initial channel model, the embodiments of this application can mainly map RSSI and txRate (TRANSFER RATE). For example, the default initial RSSI range of the client is [-82, -20], and the initial step size is set to 3dBm. Thus, the quantization strategy in related technologies can be used to obtain the initial received signal strength quantization result based on the initial RSSI range of [-82, -20] and the initial step size of 3dBm. Furthermore, the client's transmission rate is mapped according to a preset modulation and coding scheme (MCS) table. For example, if the client's parameters are (11n, 20M, 2NSS) and the MCS range is [0, 15], the initial transmission rate quantization result can be obtained.

[0044] Therefore, the initial channel model can be obtained by combining the initial received signal strength quantization result and the initial transmission rate quantization result, wherein the initial channel model is as shown in equation (1):

[0045] C k =γ k +η k (1)

[0046] Among them, C k For channel environment k, γ k η represents the initial received signal strength quantization result for channel k. k The initial transmission rate quantization result for channel k.

[0047] For example, assuming the initial received signal strength quantization result of channel k is [-82, -20] and the initial transmission rate quantization result of channel k is [0, 15], then C k The value of is [-82, -5].

[0048] It should be noted that C k The value of can be changed through other operations. For example, the range [-82, -5] can be changed to [0, 77] by adding 82 to all values. No transformation restrictions are imposed here. Alternatively, only the initial received signal strength quantization result or the initial transmission rate quantization result can be used as the description of the channel model. Preferably, considering that performance is related to both the current client's received signal strength and transmission rate, a combination of the two is adopted.

[0049] Furthermore, after obtaining the initial channel model, in order to obtain the current channel probability model, this embodiment of the application can use multiple preset posterior probability values ​​to update the initial channel model, wherein the current channel probability model can be as shown in equations (2) and (3):

[0050]

[0051]

[0052] in, This is the success probability value updated for the i-th sampling point of channel k. P represents the success probability before the update. k (s|a i C k,i (i) represents the i-th sampling point on channel k, with antenna mode a. i The conditional probability value at time s, where s = 1 indicates successful transmission, otherwise it indicates transmission failure, r i Let be the transmission rate at the i-th sampling point.

[0053] Therefore, after obtaining the current parameters of the channel environment based on step S101, the current channel probability model of the client is updated based on the current parameters of the channel environment, thereby ensuring that the corresponding channel probability model is updated in a timely manner for each transmission, and thus accurately predicting the performance of each antenna mode.

[0054] In step S103, the throughput of at least one antenna mode of the target wireless device is estimated by combining the configuration parameters of the target wireless device and the updated current channel probability model, and the antenna mode with the highest throughput is selected as the target antenna mode of the client.

[0055] In some embodiments, the configuration parameters of the target wireless device include the antenna modes and / or rate settings supported by the target wireless device.

[0056] Optionally, in some embodiments, the throughput of at least one antenna mode of the target wireless device is estimated by combining the configuration parameters of the target wireless device and the updated current channel probability model, including: obtaining the current received signal strength quantization result and the current transmission rate quantization result according to the configuration parameters of the target wireless device and the updated current channel probability model; and estimating the throughput of at least one antenna mode of the target wireless device based on the received signal strength quantization result and the current transmission rate quantization result according to a preset conditional probability formula.

[0057] It should be understood that, according to the antenna mode and rate range supported by the target wireless device, and the updated current channel probability model, the current received signal strength quantization result is obtained from the receiver's ACK (Acknowledge character) or BLOCKACK frame, and the current transmission rate quantization result is obtained from the transmitter's rate, thereby obtaining the current C. k,i And calculate the throughput of at least one antenna mode of the target wireless device using a preset conditional probability formula:

[0058] T j =P(1|a j C k，i )r j (4)

[0059] Wherein, P(1|a j C k,i ) is C k,i Let i be the i-th sampling point on channel k, and let a be the antenna mode. j The conditional probability value for successful transmission.

[0060] Finally, in this embodiment, the antenna mode with the highest throughput is selected as the target antenna mode for the client.

[0061] Furthermore, to further understand the antenna mode selection method of this application, examples are provided below.

[0062] For example, when the client sends the current parameters of the channel environment for the first time, the target wireless device supports the antenna mode A1, and the client receives the signal strength R1. The result of this transmission is updated to the probability value corresponding to (A1, R1), and the channel probability model is updated according to the updated probability value.

[0063] When the client sends the current parameters of the channel environment for the second time, the antenna mode supported by the target wireless device and the signal strength received by the client remain unchanged, just like the first time. The result of this transmission is updated to the probability value corresponding to (A1, R1), and the channel probability model is updated according to the updated probability value.

[0064] When the client sends the current parameters of the channel environment for the third time, the antenna mode supported by the target wireless device changes to A2, and the received signal strength of the client changes to R2. The transmission result is updated to the probability value corresponding to (A2, R2), and the channel probability model is updated according to the updated probability value.

[0065] Even if the current parameters of the client's channel environment or the antenna mode supported by the target wireless device do not change during this transmission, the corresponding channel probability model is updated in a timely manner with each transmission result.

[0066] Therefore, when the channel environment changes, by updating the channel probability model with each transmission result in a timely manner, there is no need to set parameters such as detection interval or fixed rate threshold. The antenna mode can be automatically reselected according to the prediction of the channel probability model, which improves the sensitivity of the antenna selection algorithm to environmental changes and the accuracy of selection, thereby avoiding the lag of statistical probability.

[0067] Furthermore, in some embodiments, after selecting the antenna mode with the highest throughput as the target antenna mode for the client, the method further includes: normalizing multiple preset posterior probability values ​​based on a preset normalization strategy; updating the initial channel model according to the multiple preset posterior probability values ​​after normalization to obtain a new current channel probability model.

[0068] One feasible preset normalization strategy is a linear normalization strategy, which normalizes the sampled preset multiple posterior probability values ​​so that the preset multiple posterior probability values ​​are restricted to the range of (0, 1) by weights after normalization, so as to avoid the probability values ​​being too low or too high after a period of time. The initial channel model is updated according to the normalized preset multiple posterior probability values ​​to obtain a new current channel probability model.

[0069] Another feasible pre-defined normalization strategy is a normalization algorithm strategy, which normalizes multiple pre-defined posterior probability values ​​sampled, so that the pre-defined multiple posterior probability values ​​are restricted to the range of (0, 1) after normalization by weighting, so as to avoid the probability values ​​being too low or too high after a period of time, and the initial channel model is updated according to the pre-defined multiple posterior probability values ​​after normalization to obtain a new current channel probability model.

[0070] It should be noted that the preset normalization strategy can be a linear normalization strategy, a normalization algorithm strategy, etc., and no specific restrictions are made here. Those skilled in the art can use different normalization strategies to normalize the multiple preset posterior probability values ​​and then limit them to the range of (0, 1) through weights.

[0071] To enable those skilled in the art to further understand the antenna mode selection method of the embodiments of this application, a detailed description is provided below with reference to specific embodiments.

[0072] like Figure 2 As shown, Figure 2 This is a flowchart of an antenna mode selection method according to a specific embodiment of this application. The antenna mode selection method includes the following steps:

[0073] In step 201, the configuration parameters of the target wireless device are obtained, wherein the configuration parameters include the antenna modes and / or rate settings supported by the target wireless device.

[0074] In step 202, the channel environment parameters of the client are obtained, including parameters such as the rate supported by the client, the received signal strength, and the packet error rate, as the initial state.

[0075] In step 203, quantization and mapping rules are determined based on relevant parameters to obtain the initial channel model.

[0076] In step 204, the channel probability model is updated using multiple preset posterior probability values.

[0077] In step 205, the throughput is estimated based on the updated channel probability model, and the antenna mode with the highest throughput is selected.

[0078] In step 206, multiple preset posterior probability values ​​are renormalized periodically.

[0079] According to the antenna mode selection method proposed in this application, the current channel probability model of the client is updated based on the current parameters of the channel environment. Combining the configuration parameters of the target wireless device and the updated current channel probability model, the throughput of at least one antenna mode of the target wireless device is estimated, and the antenna mode with the highest throughput is selected as the target antenna mode of the client. Therefore, by pre-modeling the channel environment and obtaining the corresponding antenna mode with the highest throughput as the target antenna mode of the client based on the current parameters of the channel environment, this solves the problems in related technologies that rely on fixed rate ranges and timed or conditional detection methods to obtain the optimal antenna mode, resulting in long optimization times, inability to make timely adjustments based on changes in the channel environment or the client, and the need to set multiple threshold conditions. This effectively improves communication performance.

[0080] Next, the antenna mode selection device proposed according to the embodiments of this application is described with reference to the accompanying drawings.

[0081] Figure 3 This is a block diagram of an antenna mode selection device according to an embodiment of this application.

[0082] like Figure 3 As shown, the antenna mode selection device 10 includes: an acquisition module 100, an update module 200, and a selection module 300.

[0083] The acquisition module 100 is used to acquire the current parameters of the channel environment of the client; the update module 200 is used to update the current channel probability model of the client based on the current parameters of the channel environment; and the selection module 300 is used to combine the configuration parameters of the target wireless device and the updated current channel probability model to estimate the throughput of at least one antenna mode of the target wireless device, and select the antenna mode with the highest throughput as the target antenna mode of the client.

[0084] Optionally, in some embodiments, before updating the client's current channel probability model based on the current parameters of the channel environment, the update module 200 is further configured to: obtain the client's initial channel environment parameters; obtain an initial channel model based on the initial channel environment parameters; and update the initial channel model based on a plurality of preset posterior probability values ​​to obtain the current channel probability model.

[0085] Optionally, in some embodiments, the update module 200 is further configured to: determine the received signal strength range and the initial step size of the received signal based on the initial channel environment parameters, and obtain the initial received signal strength quantization result according to the received signal strength range and the initial step size of the received signal; determine the transmission rate of the client based on the initial channel environment parameters, and map the transmission rate according to a preset modulation and coding scheme table to obtain the initial transmission rate quantization result; and obtain the initial channel model by combining the initial received signal strength quantization result and the initial transmission rate quantization result.

[0086] Optionally, in some embodiments, after selecting the antenna mode with the highest throughput as the target antenna mode for the client, the selection module 300 is further configured to: normalize multiple preset posterior probability values ​​based on a preset normalization strategy; update the initial channel model according to the multiple preset posterior probability values ​​after normalization to obtain a new current channel probability model.

[0087] Optionally, in some embodiments, the selection module 300 is further configured to: obtain the current received signal strength quantization result and the current transmission rate quantization result based on the configuration parameters of the target wireless device and the updated current channel probability model; and estimate the throughput of at least one antenna mode of the target wireless device based on the received signal strength quantization result and the current transmission rate quantization result according to a preset conditional probability formula.

[0088] Optionally, in some embodiments, the configuration parameters of the target wireless device include the antenna modes and / or rate settings supported by the target wireless device.

[0089] It should be noted that the foregoing explanation of the antenna mode selection method embodiment also applies to the antenna mode selection device of this embodiment, and will not be repeated here.

[0090] The antenna mode selection device proposed in this application updates the client's current channel probability model based on the current parameters of the channel environment. Combining the configuration parameters of the target wireless device with the updated current channel probability model, it estimates the throughput of at least one antenna mode of the target wireless device and selects the antenna mode with the highest throughput as the client's target antenna mode. Therefore, by pre-modeling the channel environment and obtaining the corresponding antenna mode with the highest throughput as the client's target antenna mode based on the current parameters of the channel environment, it solves the problems in related technologies that rely on fixed rate ranges and timed or conditional detection methods to obtain the optimal antenna mode, resulting in long optimization times, inability to adjust in a timely manner according to changes in the channel environment or the client, and the need to set multiple threshold conditions. This effectively improves communication performance.

[0091] Figure 4A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include:

[0092] The memory 401, the processor 402, and the computer program stored on the memory 401 and capable of running on the processor 402.

[0093] When the processor 402 executes the program, it implements the antenna mode selection method provided in the above embodiments.

[0094] Furthermore, electronic devices also include:

[0095] Communication interface 403 is used for communication between memory 401 and processor 402.

[0096] The memory 401 is used to store computer programs that can run on the processor 402.

[0097] The memory 401 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0098] If the memory 401, processor 402, and communication interface 403 are implemented independently, then the communication interface 403, memory 401, and processor 402 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be divided into address buses, data buses, control buses, etc. For ease of representation, Figure 4 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0099] Optionally, in a specific implementation, if the memory 401, processor 402, and communication interface 403 are integrated on a single chip, then the memory 401, processor 402, and communication interface 403 can communicate with each other through an internal interface.

[0100] Processor 402 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0101] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the antenna mode selection method described above.

[0102] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0103] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0104] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0105] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0106] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0107] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it includes one or a combination of the steps of the method embodiments.

[0108] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0109] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. An antenna mode selection method, characterized in that, Includes the following steps: Get the current parameters of the client's channel environment; The client's current channel probability model is updated based on the current parameters of the channel environment; as well as Based on the configuration parameters of the target wireless device and the updated current channel probability model, the throughput of at least one antenna mode of the target wireless device is estimated, and the antenna mode with the highest throughput is selected as the target antenna mode for the client. The current channel probability model is as follows: ； ； in, For channel The The success probability value of updating each sampling point The success probability before the update. For channel The first Each sampling point and antenna mode is The conditional probability value at that time. A value of 1 indicates successful transmission; otherwise, it indicates transmission failure. For the first The transmission rate at each sampling point The throughput of the at least one antenna mode is: ； in, For channel The first One sampling point, Antenna mode, For channel The first Each sampling point and antenna mode is The conditional probability value for successful transmission.

2. The method according to claim 1, characterized in that, Before updating the client's current channel probability model based on the current parameters of the channel environment, the method further includes: Obtain the initial channel environment parameters of the client; An initial channel model is obtained based on the initial channel environment parameters, and the initial channel model is updated based on multiple preset posterior probability values ​​to obtain the current channel probability model.

3. The method according to claim 2, characterized in that, The step of obtaining the initial channel model based on the initial channel environment parameters includes: Based on the initial channel environment parameters, the received signal strength range and initial step size of the received signal are determined, and the initial received signal strength quantization result is obtained according to the received signal strength range and the initial step size of the received signal. Based on the initial channel environment parameters, the transmission rate of the client is determined, and the transmission rate is mapped according to a preset modulation and coding scheme table to obtain the initial transmission rate quantization result. The initial channel model is obtained by combining the initial received signal strength quantization result and the initial transmission rate quantization result.

4. The method according to claim 2, characterized in that, After selecting the antenna mode with the highest throughput as the target antenna mode for the client, the following steps are also included: Based on a preset normalization strategy, the preset multiple posterior probability values ​​are normalized respectively. The initial channel model is updated based on the preset multiple posterior probability values ​​after normalization to obtain a new current channel probability model.

5. The method according to claim 1, characterized in that, The step of estimating the throughput of at least one antenna mode of the target wireless device by combining the configuration parameters of the target wireless device and the updated current channel probability model includes: Based on the configuration parameters of the target wireless device and the updated current channel probability model, the current received signal strength quantization result and the current transmission rate quantization result are obtained; Based on a preset conditional probability formula, the throughput of at least one antenna mode of the target wireless device is estimated according to the received signal strength quantization result and the current transmission rate quantization result.

6. The method according to any one of claims 1-5, characterized in that, The configuration parameters of the target wireless device include the antenna modes and / or rate settings supported by the target wireless device.

7. An antenna mode selection device, characterized in that, include: The acquisition module is used to obtain the current parameters of the client's channel environment; The update module is used to update the current channel probability model of the client based on the current parameters of the channel environment. as well as The selection module is used to combine the configuration parameters of the target wireless device and the updated current channel probability model to estimate the throughput of at least one antenna mode of the target wireless device, and select the antenna mode with the highest throughput as the target antenna mode for the client. The current channel probability model is as follows: ； ； in, For channel The The success probability value of updating each sampling point The success probability before the update. For channel The first Each sampling point and antenna mode is The conditional probability value at that time. A value of 1 indicates successful transmission; otherwise, it indicates transmission failure. For the first The transmission rate at each sampling point The throughput of the at least one antenna mode is: ； in, For channel The first One sampling point, Antenna mode, For channel The first Each sampling point and antenna mode is The conditional probability value for successful transmission.

8. The apparatus according to claim 7, characterized in that, Before updating the client's current channel probability model based on the current parameters of the channel environment, the update module is further configured to: Obtain the initial channel environment parameters of the client; An initial channel model is obtained based on the initial channel environment parameters, and the initial channel model is updated based on multiple preset posterior probability values ​​to obtain the current channel probability model.

9. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the antenna mode selection method as described in any one of claims 1-6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the antenna mode selection method as described in any one of claims 1-6.

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