A method and apparatus for determining a link rate

Abstract

The application provides a link rate determination method and device, and relates to the technical field of wireless communication. The method comprises the following steps: obtaining probability distribution information of a transmission success probability corresponding to each transmission rate, wherein the probability distribution information is determined according to historical transmission result information corresponding to the transmission rate, and the historical transmission result information comprises a transmission success number and a transmission failure number; obtaining the transmission success probability corresponding to each transmission rate according to the probability distribution information; and selecting an optimal transmission rate corresponding to a preset moment according to the transmission success probability. According to the embodiment of the application, the optimal transmission rate can be quickly and accurately selected by selecting the optimal transmission rate through the probability distribution, and the robustness is higher.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to a method and apparatus for determining link rate. Background Technology

[0002] Optimal link transmission rate selection is one of the hot topics in the field of next-generation mobile communications. However, due to the high-speed movement of users and the difficulty in obtaining accurate and complete channel state information, it is challenging to accurately and quickly determine the optimal link transmission rate. Summary of the Invention

[0003] The purpose of this invention is to provide a method and apparatus for determining link rate, so as to solve the problem of how to accurately and quickly determine the optimal link transmission rate.

[0004] To achieve the above objectives, embodiments of the present invention provide a method for determining link rate, the method comprising:

[0005] Obtain the probability distribution information of the transmission success probability corresponding to each transmission rate. The probability distribution information is determined based on the historical transmission result information corresponding to the corresponding transmission rate. The historical transmission result information includes the number of successful transmissions and the number of failed transmissions.

[0006] Based on the probability distribution information, obtain the transmission success probability corresponding to each transmission rate;

[0007] Based on the transmission success probability, the optimal transmission rate corresponding to the preset time is selected.

[0008] Optionally, the method in this embodiment of the invention further includes:

[0009] Based on the number of times each transmission rate is selected as the optimal transmission rate, determine whether to update the probability distribution information;

[0010] If it is determined that the probability distribution information should be updated, then the optimal transmission rate corresponding to the next preset time is selected based on the transmission success probability determined based on the updated probability distribution information.

[0011] If it is determined that the probability distribution information should not be updated, then the optimal transmission rate corresponding to the next preset time is selected based on the transmission success probability determined based on the probability distribution information.

[0012] Optionally, determining whether to update the probability distribution information based on the number of times each transmission rate is selected as the optimal transmission rate includes:

[0013] If the number of times at least one transmission rate is selected as the optimal transmission rate is greater than the target number corresponding to the transmission rate, the probability distribution information is determined to be updated.

[0014] Optionally, the target number satisfies the following formula:

[0015] Target number of times = 2^(l) i );

[0016] Among them, l i This represents the target value corresponding to the i-th transmission rate at the preset time, where i is the index value of the transmission rate, and i≥1.

[0017] Optionally, after determining to update the probability distribution information, the method further includes:

[0018] The l i Updated to l i +1.

[0019] Optionally, selecting the optimal transmission rate corresponding to a preset time based on the transmission success probability includes:

[0020] Obtain the product of each transmission rate and the corresponding probability of successful transmission;

[0021] The transmission rate corresponding to the largest product is selected as the optimal transmission rate for the preset time.

[0022] Optionally, after determining to update the probability distribution information, the method further includes:

[0023] Obtain transmission result information of transmission at the optimal transmission rate within the target time period before the probability distribution information is updated;

[0024] Based on the transmission result information, update the historical transmission result information corresponding to the optimal transmission rate;

[0025] The probability distribution information is updated based on the updated historical transmission results.

[0026] This invention also provides a link rate determination apparatus, comprising:

[0027] The first determining module is used to obtain the probability distribution information of the transmission success probability corresponding to each transmission rate. The probability distribution information is determined based on the historical transmission result information corresponding to the corresponding transmission rate. The historical transmission result information includes the number of successful transmissions and the number of failed transmissions.

[0028] The second determining module is used to obtain the transmission success probability corresponding to each transmission rate based on the probability distribution information.

[0029] The first selection module is used to select the optimal transmission rate corresponding to a preset time based on the transmission success probability.

[0030] Optionally, the apparatus of this embodiment further includes:

[0031] The third determining module is used to determine whether to update the probability distribution information based on the number of times each transmission rate is selected as the optimal transmission rate;

[0032] The second selection module is used to select the optimal transmission rate corresponding to the next preset time based on the transmission success probability determined based on the updated probability distribution information if it is determined to update the probability distribution information.

[0033] The third selection module is used to select the optimal transmission rate corresponding to the next preset time based on the transmission success probability determined by the probability distribution information if it is determined not to update the probability distribution information.

[0034] Optionally, the third determining module is used to determine to update the probability distribution information when the number of times at least one transmission rate is selected as the optimal transmission rate is greater than the target number corresponding to the transmission rate.

[0035] This invention also provides a link rate determination apparatus, comprising: a transceiver and a processor.

[0036] The processor is used to obtain the probability distribution information of the transmission success probability corresponding to each transmission rate. The probability distribution information is determined based on the historical transmission result information corresponding to the corresponding transmission rate. The historical transmission result information includes the number of successful transmissions and the number of failed transmissions.

[0037] Based on the probability distribution information, obtain the transmission success probability corresponding to each transmission rate;

[0038] Based on the transmission success probability, the optimal transmission rate corresponding to the preset time is selected.

[0039] This invention also provides a link rate determination apparatus, comprising: a transceiver, a processor, a memory, and a program or instructions stored in the memory and executable on the processor; when the processor executes the program or instructions, it implements the steps in the link rate determination method described above.

[0040] This invention also provides a readable storage medium storing a program or instructions that, when executed by a processor, implement the steps in the method for determining the link rate as described above.

[0041] The beneficial effects of the above-described technical solution of the present invention are as follows:

[0042] In this embodiment of the invention, the probability distribution information of the transmission success probability corresponding to each transmission rate is obtained. Based on the probability distribution of the transmission success probability, the transmission success probability corresponding to each transmission rate is determined. Based on the transmission success probability, the optimal transmission rate is selected. That is, in this embodiment of the invention, the transmission success probability is treated as a random variable and assigned a probability distribution. At the corresponding time, the transmission success probability is obtained based on the probability distribution, and the optimal transmission rate is selected in this way. This method is different from the scheme of uniformly selecting the transmission rate in the existing scheme. Selecting the optimal transmission rate through the probability distribution can quickly and accurately select the optimal transmission rate, and it is more robust. Attached Figure Description

[0043] Figure 1 This is a flowchart illustrating the method for determining the link rate according to an embodiment of the present invention.

[0044] Figure 2 This is a schematic diagram of the probability density function of the beta distribution in an embodiment of the present invention;

[0045] Figure 3 This is a schematic diagram of the simulation verification results of an embodiment of the present invention;

[0046] Figure 4 This is a schematic diagram of the link rate determination device according to an embodiment of the present invention;

[0047] Figure 5 This is one of the structural block diagrams of a link rate determination device according to an embodiment of the present invention;

[0048] Figure 6 This is a second structural block diagram of the link rate determination device according to an embodiment of the present invention. Detailed Implementation

[0049] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0050] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of the invention. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification do not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments.

[0051] In various embodiments of the present invention, it should be understood that the sequence number of each process described below does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0052] In addition, the terms "system" and "network" are often used interchangeably in this article.

[0053] In the embodiments provided in this application, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean determining B solely based on A; B can also be determined based on A and / or other information.

[0054] like Figure 1 As shown, this embodiment of the invention provides a method for determining link rate, the method comprising:

[0055] Step 101: Obtain the probability distribution information of the transmission success probability corresponding to each transmission rate. The probability distribution information is determined based on the historical transmission result information corresponding to the corresponding transmission rate. The historical transmission result information includes the number of successful transmissions and the number of failed transmissions.

[0056] In this embodiment of the invention, assuming the total system operation time is T, the data transmission time is discretized into T time points (i.e., T preset time points), and t is used to represent the time index value, i.e., t = 1, 2, ..., T. Throughout the system, the transmitter can select N different transmission rates, denoted as r1, ..., r... N Each transmission rate r i All will be in θ i The probability of successful transmission is that the data is successfully received by the receiver. Due to the random uncertainty of the channel, this probability of successful transmission cannot be predicted in advance. Therefore, the transmitter needs to design the current link rate selection strategy based on historical transmission results to optimize the average throughput of the entire system. This adaptive link transmission rate selection design method is based on the batch processing Thompson sampling method, abbreviated as MBTS algorithm.

[0057] Assume the transmission rate (optimal transmission rate) selected at time t is denoted as r. i (t)(or it can also be written as r) i ), transmission rate r i The corresponding number of successful transmissions is S i (or described as S) i(t) ), transmission rate r i The corresponding number of successful transmissions is F. i (or described as F) i(t) In the embodiments of the present invention, (S) can be used. i ,F i The tuple represents the historical transmission result information collected by the system.

[0058] The probability distribution information for the transmission success probability corresponding to each of the above transmission rates is random distribution information, which can be a beta distribution, Gaussian distribution, etc. In this embodiment of the invention, the beta distribution is used as an example. Assume that the two parameters α and β (taking positive integer values) in the beta distribution are used to represent the number of successful transmissions and the number of failed transmissions, respectively. Let Beta(α,β) represent the beta distribution. Under parameters α and β, its probability density function f(x; α,β) is:

[0059] This formula is an existing formula and will not be explained in detail here. Where x represents the probability of successful transmission, α represents the number of successful transmissions, and β represents the number of failed transmissions. In this embodiment, the specific value of α can be α0. i +1 or S i +1, the specific value of β can be β i +1 or F i +1.

[0060] Figure 2 The text provides some examples of the probability density function of the beta distribution. The larger the parameter of the beta distribution, the closer the probability density function is to an impulse function. When the probability of successful transmission θ is... i When considered as a random variable, if its prior distribution is uniform, the collected historical data on whether the transmission was successful (S) i ,F i The posterior probability distribution of this random variable still follows a beta distribution, and the parameter changes to Beta(α). i +1, β i +1), that is

[0061] Step 102: Based on the probability distribution information, obtain the transmission success probability corresponding to each transmission rate.

[0062] Optionally, the probability distribution information corresponding to each transmission rate is sampled to obtain the transmission success probability corresponding to each transmission rate. Here, the above transmission success probability is randomly generated after sampling the probability distribution information corresponding to each transmission rate.

[0063] In this step, the probability of successful transmission can be sampled based on the aforementioned posterior distribution.

[0064] Step 103: Select the optimal transmission rate corresponding to the preset time based on the transmission success probability.

[0065] The optimal transmission rate is the transmission rate used for data transmission at a preset time. The preset time can be the current time or the time after the current time. For example, at time t0, the optimal transmission rate corresponding to time t1 among the T preset times can be selected. Time t0 can be before time t1 or the same as time t1.

[0066] Optionally, the optimal transmission rate corresponding to different preset times can be determined according to different probability distribution information.

[0067] Optionally, selecting the optimal transmission rate corresponding to a preset time based on the transmission success probability includes:

[0068] Obtain the product of each transmission rate and the corresponding probability of successful transmission;

[0069] The transmission rate corresponding to the largest product is selected as the optimal transmission rate for the preset time.

[0070] For example, after sampling the transmission success probability from the above beta distribution, select a value such that r i θ i (t)(the θ) i (t) can also be described as θ i Transmit at the maximum transmission rate. Figure 2 As can be seen from this, historical data (S) decreases over time. i ,F i The probability density function of the beta distribution will gradually increase, therefore, the probability density function of the beta distribution will gradually converge to a value at the true value θ. i The impulse function at point θ indicates the probability of successful transmission. i The estimates will gradually become more accurate.

[0071] Here, when channel state statistics are unavailable, historical ACK / NACK signals are collected to determine the number of successful and failed transmissions, thereby estimating the channel's transmission success probability.

[0072] In this embodiment of the invention, the probability distribution information of the transmission success probability corresponding to each transmission rate is obtained. Based on the probability distribution of the transmission success probability, the transmission success probability corresponding to each transmission rate is determined. Based on the transmission success probability, the optimal transmission rate is selected. That is, in this embodiment of the invention, the transmission success probability is treated as a random variable and assigned a probability distribution. At the corresponding time, the transmission success probability is obtained based on the probability distribution, and the optimal transmission rate is selected in this way. This method is different from the scheme of uniformly selecting the transmission rate in the existing scheme. Selecting the optimal transmission rate through the probability distribution can quickly and accurately select the optimal transmission rate, and it is more robust.

[0073] Optionally, the method in this application embodiment further includes:

[0074] Based on the number of times each transmission rate is selected as the optimal transmission rate, determine whether to update the probability distribution information;

[0075] If it is determined that the probability distribution information should be updated, then the optimal transmission rate corresponding to the next preset time is selected based on the transmission success probability determined based on the updated probability distribution information.

[0076] If it is determined that the probability distribution information should not be updated, then the optimal transmission rate corresponding to the next preset time is selected based on the transmission success probability determined based on the probability distribution information.

[0077] Specifically, the number of times each transmission rate is selected as the optimal transmission rate refers to the number of times each transmission rate is selected as the optimal transmission rate before the next preset time.

[0078] For example, select the optimal transmission rate corresponding to 10 preset times. Assume that the first probability distribution information is used at the first preset time and the second preset time, and the first probability distribution information is updated to the second probability distribution information at the second preset time. Then, select the optimal transmission rate corresponding to at least one subsequent preset time according to the second probability distribution information.

[0079] Optionally, determining whether to update the probability distribution information based on the number of times each transmission rate is selected as the optimal transmission rate includes:

[0080] If the number of times at least one transmission rate is selected as the optimal transmission rate is greater than the target number corresponding to the transmission rate, the probability distribution information is determined to be updated.

[0081] Optionally, after determining to update the probability distribution information, the method further includes:

[0082] Obtain transmission result information of transmission at the optimal transmission rate within the target time period before the probability distribution information is updated;

[0083] Based on the transmission result information, update the historical transmission result information corresponding to the optimal transmission rate;

[0084] The probability distribution information is updated based on the updated historical transmission results.

[0085] In this embodiment of the invention, at time t, only the selected transmission rate r i (t) corresponds to the historical data (S) i(t) ,F i(t) Only if the transmission is successful will S be updated: i(t) Add 1; otherwise, F i(t)Add 1. One specific algorithm implementation method is to use a Boolean variable x. i(t) Let (t) record whether the transmission was successful at the selected transmission rate index value i(t) at the current time t, where 1 indicates success and 0 indicates failure. Then, at time t, only the selected transmission rate r i(t) History of successes and failures (S) i(t) ,F i(t) This will be updated:

[0086] (S i(t) ,F i(t) )=(S i(t) +x i(t) (t),F i(t) +1-x i(t) (t)).

[0087] Optionally, the target number satisfies the following formula:

[0088] Target number of times = 2^(l) i );

[0089] Among them, l i This represents the target value corresponding to the i-th transmission rate at the preset time, where i is the index value of the transmission rate, and i≥1. "^" represents the exponentiation operator.

[0090] Optionally, after determining to update the probability distribution information, the method further includes:

[0091] The l i Updated to l i +1.

[0092] In this embodiment of the invention, n is recorded. i The speed r before time t (such as a preset time) i The number of times it is selected as the optimal transmission rate (which can also be described as n) i(t) ), l i (can also be described as l) i(t) The value of ) is a natural number starting from zero. After each transmission moment, for each transmission rate r i The following inequalities are used for judgment:

[0093] n i <2^(l) i );

[0094] For N transmission rates, if all the above inequalities are satisfied, then no strategy adjustment is performed at the current time (i.e., the probability distribution information is not updated), and the process returns to step 102 to continue sampling the probability distribution information to obtain the transmission success probability. Based on this transmission success probability, the optimal transmission rate is selected. Otherwise, a strategy update is required (i.e., updating the above probability distribution information). Specifically, the strategy adjustment involves updating the historical transmission result information corresponding to the optimal transmission rate based on the transmission result information of transmissions performed at the optimal transmission rate within the target time period. This means updating the parameter (α). i ,β i ),Right now Based on the updated historical transmission results, the probability distribution information of the transmission success probability corresponding to each transmission rate is re-determined.

[0095] In this embodiment of the invention, the above-mentioned inequality is determined at each of the above-mentioned discrete time points, and at the current time, only the selected transmission rate is selected a number of times, n. i(t) It will change, therefore, it can only be n. i(t) <2^(l) i(t) The condition is not met; therefore, after updating the strategy, only l needs to be updated. i(t) =l i(t) +1, so that from the next moment on, the inequality n i(t) <2^(l i(t) It can also be satisfied. For example, if r1 is selected as the optimal transmission rate at the current time, then only l is updated. 1(t) =l 1(t) +1, while other transmission rates correspond to l i(t) Leave it unchanged. Finally, return to step 101.

[0096] In addition, in this embodiment of the invention, during initialization, n i =l i =0, S i =Fi=α i =β i =0.

[0097] In this embodiment of the invention, by making decisions on the update strategy, the number and complexity of strategy adjustments and update deployments are greatly reduced. Furthermore, we have theoretically proven that this scheme, compared to the traditional Thompson sampling algorithm, does not change the theoretical lower bound of throughput performance while reducing the number of strategy updates. Simultaneously, due to the decision threshold 2^(l) iThe rate of change is exponentially increasing. Therefore, in the initial stage of transmission, due to the limited historical data available to the system, the estimation error is relatively large, resulting in a shorter update interval. As the amount of historical data increases and the estimation error decreases, the update interval also increases, achieving adaptive policy update timing. Compared to periodic updates or other schemes, this scheme can find the optimal transmission rate faster with fewer policy updates.

[0098] according to Figure 3 The simulation results shown demonstrate that this algorithm (MBTS) and the improved CBTS algorithm based on it outperform other UCB-SC and GBTS algorithms. Figure 3 The simulation parameters were set to 8 communication rates [6,9,12,18,24,36,48,54] (Mbit / s), and the actual transmission success probability was [0.95,0.9,0.8,0.65,0.45,0.25,0.15,0.1].

[0099] In this embodiment of the invention, two time dimensions are introduced to distinguish between the sampling granularity of the random variable for the transmission success probability (i.e., the W time points mentioned above) and the granularity of the random distribution update frequency used in the strategy (i.e., the frequency granularity corresponding to the update time of the probability distribution information). By increasing the granularity of the strategy update frequency, the number of strategy updates and adjustments can be greatly reduced without compromising the theoretical lower bound of the algorithm's throughput performance. Furthermore, in this embodiment of the invention, by adaptively selecting the strategy update time, the strategy update interval grows approximately exponentially, thus resolving the performance loss caused by inaccurate estimation in the early stages.

[0100] The method of this invention, through online learning, finds the optimal transmission rate in a short time to maximize the average throughput of the system. Compared with existing technologies, this solution integrates the data transmission and channel probing states, improving the time utilization of transmitted data. Furthermore, based on the mature recommendation algorithm Thompson's algorithm, it introduces a batch learning approach, proposing a batch Thompson sampling algorithm. The transmitter only needs to update and redeploy the strategy at certain times, demonstrating that throughput performance can achieve the same convergence order.

[0101] like Figure 4 As shown, this embodiment of the invention also provides a link rate determination device 400, comprising:

[0102] The first determining module 401 is used to obtain the probability distribution information of the transmission success probability corresponding to each transmission rate. The probability distribution information is determined based on the historical transmission result information corresponding to the corresponding transmission rate. The historical transmission result information includes the number of successful transmissions and the number of failed transmissions.

[0103] The second determining module 402 is used to obtain the transmission success probability corresponding to each transmission rate based on the probability distribution information.

[0104] The first selection module 403 is used to select the optimal transmission rate corresponding to a preset time based on the transmission success probability.

[0105] The apparatus of this embodiment further includes:

[0106] The third determining module is used to determine whether to update the probability distribution information based on the number of times each transmission rate is selected as the optimal transmission rate;

[0107] The second selection module is used to select the optimal transmission rate corresponding to the next preset time based on the transmission success probability determined based on the updated probability distribution information if it is determined to update the probability distribution information.

[0108] The third selection module is used to select the optimal transmission rate corresponding to the next preset time based on the transmission success probability determined by the probability distribution information if it is determined not to update the probability distribution information.

[0109] In the apparatus of this embodiment, the third determining module is used to determine and update the probability distribution information when the number of times at least one transmission rate is selected as the optimal transmission rate is greater than the target number corresponding to the transmission rate.

[0110] In the apparatus of this embodiment, the target number satisfies the following formula:

[0111] Target number of times = 2^(l) i );

[0112] Among them, l i This represents the target value corresponding to the i-th transmission rate at the preset time, where i is the index value of the transmission rate, and i≥1.

[0113] The apparatus of this embodiment further includes:

[0114] The first update module is used to update the probability distribution information after the third determining module determines that the probability distribution information needs to be updated. i Updated to l i +1.

[0115] The apparatus of this embodiment of the invention, wherein the first selection module includes:

[0116] The first acquisition submodule is used to obtain the product of each transmission rate and the corresponding transmission success probability;

[0117] The third selection submodule is used to select the transmission rate corresponding to the largest product as the optimal transmission rate corresponding to the preset time.

[0118] The apparatus of this embodiment further includes:

[0119] The first acquisition module is used to acquire transmission result information of transmission at the optimal transmission rate within the target time period before the probability distribution information is updated, after the first determining submodule determines to update the probability distribution information.

[0120] The second update module is used to update the historical transmission result information corresponding to the optimal transmission rate according to the transmission result information.

[0121] The third update module is used to update the probability distribution information based on the updated historical transmission result information.

[0122] The link rate determination device of this invention can implement all the implementation methods in the above-described link rate determination method embodiments and achieve the same technical effect, which will not be elaborated here.

[0123] like Figure 5 As shown, this embodiment of the invention also provides a link rate determination device 500, including: a transceiver 520 and a processor 510;

[0124] The processor 510 is configured to: acquire probability distribution information of the transmission success probability corresponding to each transmission rate, wherein the probability distribution information is determined based on the historical transmission result information corresponding to the corresponding transmission rate, and the historical transmission result information includes the number of successful transmissions and the number of failed transmissions; acquire the transmission success probability corresponding to each transmission rate based on the probability distribution information; and select the optimal transmission rate corresponding to a preset time based on the transmission success probability.

[0125] Optionally, the processor 510 is further configured to:

[0126] Based on the number of times each transmission rate is selected as the optimal transmission rate, determine whether to update the probability distribution information;

[0127] If it is determined that the probability distribution information should be updated, then the optimal transmission rate corresponding to the next preset time is selected based on the transmission success probability determined based on the updated probability distribution information.

[0128] If it is determined that the probability distribution information should not be updated, then the optimal transmission rate corresponding to the next preset time is selected based on the transmission success probability determined based on the probability distribution information.

[0129] Optionally, the processor 510 is further configured to: determine to update the probability distribution information when the number of times at least one transmission rate is selected as the optimal transmission rate is greater than the target number corresponding to the transmission rate.

[0130] Optionally, the target number satisfies the following formula:

[0131] Target number of times = 2^(l) i );

[0132] Among them, l i This represents the target value corresponding to the i-th transmission rate at the preset time, where i is the index value of the transmission rate, and i≥1.

[0133] Optionally, the processor 510 is further configured to: transfer the l i Updated to l i +1.

[0134] Optionally, the processor 510 is further configured to: obtain the product of each transmission rate and the corresponding transmission success probability; select the transmission rate corresponding to the largest product as the optimal transmission rate corresponding to the preset time.

[0135] Optionally, the processor 510 is further configured to: acquire transmission result information of transmission at the optimal transmission rate within the target time period before the probability distribution information is updated;

[0136] Based on the transmission result information, update the historical transmission result information corresponding to the optimal transmission rate;

[0137] The probability distribution information is updated based on the updated historical transmission results.

[0138] This device can implement all the implementation methods described in the above method embodiments, and will not be repeated here to avoid repetition.

[0139] One embodiment of the present invention provides a link rate determination device (applicable to terminals or network-side devices such as base stations), such as... Figure 6 As shown, it includes a transceiver 610, a processor 600, a memory 620, and a program or instructions stored in the memory 620 and executable on the processor 600; when the processor 600 executes the program or instructions, it implements the above-mentioned method for determining the link rate.

[0140] The transceiver 610 is used to receive and send data under the control of the processor 600.

[0141] Among them, Figure 6In this context, the bus architecture may include any number of interconnected buses and bridges, specifically linking various circuits together, represented by one or more processors (processor 600) and memory (memory 620). The bus architecture may also link together various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 610 may be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over a transmission medium. The processor 600 is responsible for managing the bus architecture and general processing, and the memory 620 may store data used by the processor 600 during operation.

[0142] This invention also provides a readable storage medium storing a program or instructions that, when executed by a processor, implement the steps in the link rate determination method described above and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0143] The processor mentioned above is the processor in the link rate determination device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0144] It should be further noted that the terminals described in this specification include, but are not limited to, smartphones, tablets, etc., and many of the functional components described are referred to as modules in order to emphasize the independence of their implementation.

[0145] In this embodiment of the invention, the module can be implemented in software so that it can be executed by various types of processors. For example, an identified executable code module may include one or more physical or logical blocks of computer instructions, which may be constructed as objects, procedures, or functions. Nevertheless, the executable code of the identified module does not need to be physically located together, but may include different instructions stored in different bits, which, when logically combined, constitute the module and achieve the module's intended purpose.

[0146] In practice, an executable code module can be a single instruction or many instructions, and can even be distributed across multiple different code segments, different programs, and across multiple memory devices. Similarly, operational data can be identified within the module and can be implemented in any suitable form and organized within any suitable type of data structure. This operational data can be collected as a single dataset or distributed across different locations (including different storage devices), and can exist, at least in part, solely as electronic signals within the system or network.

[0147] When a module can be implemented using software, considering the current level of hardware technology, modules that can be implemented in software can be implemented using hardware circuits by those skilled in the art to achieve the corresponding functions, without considering cost. These hardware circuits include conventional very-large-scale integrated circuits (VLSI) or gate arrays, as well as existing semiconductors such as logic chips and transistors, or other discrete components. Modules can also be implemented using programmable hardware devices, such as field-programmable gate arrays, programmable array logic, and programmable logic devices.

[0148] The exemplary embodiments described above are with reference to the accompanying drawings. Many different forms and embodiments are feasible without departing from the spirit and teachings of the invention. Therefore, the invention should not be construed as limiting the exemplary embodiments set forth herein. Rather, these exemplary embodiments are provided to make the invention complete and convey the scope of the invention to those skilled in the art. In these drawings, component dimensions and relative dimensions may be exaggerated for clarity. The terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. As used herein, unless clearly indicated otherwise, the singular forms “a,” “an,” and “the” are intended to include all such forms. It will be further understood that the terms “comprising” and / or “including”, when used in this specification, indicate the presence of the stated features, integers, steps, operations, components, and / or elements, but do not exclude the presence or addition of one or more other features, integers, steps, operations, components, and / or groups thereof. Unless otherwise indicated, when stated, a range of values ​​includes the upper and lower limits of the range and any subranges in between.

[0149] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for determining link speed, characterized in that, The method includes: Obtain the probability distribution information of the transmission success probability corresponding to each transmission rate. The probability distribution information is determined based on the historical transmission result information corresponding to the corresponding transmission rate. The historical transmission result information includes the number of successful transmissions and the number of failed transmissions. Based on the probability distribution information, obtain the transmission success probability corresponding to each transmission rate; Based on the transmission success probability, select the optimal transmission rate corresponding to the preset time. The method further includes: Based on the number of times each transmission rate is selected as the optimal transmission rate, determine whether to update the probability distribution information; If it is determined that the probability distribution information should be updated, then the optimal transmission rate corresponding to the next preset time is selected based on the transmission success probability determined based on the updated probability distribution information. If it is determined that the probability distribution information should not be updated, then the optimal transmission rate corresponding to the next preset time is selected based on the transmission success probability determined based on the probability distribution information.

2. The method according to claim 1, characterized in that, The step of determining whether to update the probability distribution information based on the number of times each transmission rate is selected as the optimal transmission rate includes: If the number of times at least one transmission rate is selected as the optimal transmission rate is greater than the target number corresponding to the transmission rate, the probability distribution information is determined to be updated.

3. The method according to claim 2, characterized in that, The target number satisfies the following formula: Target number of times = 2^(l) i ); Among them, l i This represents the target value corresponding to the i-th transmission rate at the preset time, where i is the index value of the transmission rate, i≥1, and ^ represents the exponentiation operator.

4. The method according to claim 3, characterized in that, After determining to update the probability distribution information, the method further includes: The l i Updated to l i +1.

5. The method according to claim 2, characterized in that, After determining to update the probability distribution information, the method further includes: Obtain the transmission result information of the transmission at the optimal transmission rate within the target time period before the probability distribution information is updated; Update the historical transmission result information corresponding to the optimal transmission rate based on the transmission result information; The probability distribution information is updated based on the updated historical transmission results.

6. The method according to claim 1, characterized in that, The step of selecting the optimal transmission rate corresponding to a preset time based on the transmission success probability includes: Obtain the product of each transmission rate and the corresponding probability of successful transmission; The transmission rate corresponding to the largest product is selected as the optimal transmission rate for the preset time.

7. A device for determining link rate, characterized in that, include: The first determining module is used to obtain the probability distribution information of the transmission success probability corresponding to each transmission rate. The probability distribution information is determined based on the historical transmission result information corresponding to the corresponding transmission rate. The historical transmission result information includes the number of successful transmissions and the number of failed transmissions. The second determining module is used to obtain the transmission success probability corresponding to each transmission rate based on the probability distribution information. The first selection module is used to select the optimal transmission rate corresponding to a preset time based on the transmission success probability. The device further includes: The third determining module is used to determine whether to update the probability distribution information based on the number of times each transmission rate is selected as the optimal transmission rate; The second selection module is used to select the optimal transmission rate corresponding to the next preset time based on the transmission success probability determined based on the updated probability distribution information if it is determined to update the probability distribution information. The third selection module is used to select the optimal transmission rate corresponding to the next preset time based on the transmission success probability determined by the probability distribution information if it is determined not to update the probability distribution information.

8. The apparatus according to claim 7, characterized in that, The third determining module is used to determine and update the probability distribution information when the number of times at least one transmission rate is selected as the optimal transmission rate is greater than the target number corresponding to the transmission rate.

9. A device for determining link rate, characterized in that, include: Transceiver and processor: The processor is used to obtain the probability distribution information of the transmission success probability corresponding to each transmission rate. The probability distribution information is determined based on the historical transmission result information corresponding to the corresponding transmission rate. The historical transmission result information includes the number of successful transmissions and the number of failed transmissions. Based on the probability distribution information, obtain the transmission success probability corresponding to each transmission rate; Based on the transmission success probability, select the optimal transmission rate corresponding to the preset time. The processor is further configured to: Based on the number of times each transmission rate is selected as the optimal transmission rate, determine whether to update the probability distribution information; If it is determined that the probability distribution information should be updated, then the optimal transmission rate corresponding to the next preset time is selected based on the transmission success probability determined based on the updated probability distribution information. If it is determined that the probability distribution information should not be updated, then the optimal transmission rate corresponding to the next preset time is selected based on the transmission success probability determined based on the probability distribution information.

10. A device for determining link rate, characterized in that, include: Transceiver, processor, memory, and programs or instructions stored in the memory and executable on the processor; When the processor executes the program or instructions, it implements the steps in the method for determining the link rate as described in any one of claims 1 to 6.

11. A readable storage medium, characterized in that, It stores a program or instructions that, when executed by a processor, implement the steps in the method for determining the link rate as described in any one of claims 1 to 6.

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