Wireless communication method, system, device, medium and program product

Abstract

The embodiment of the invention provides a wireless communication method, system and device, a medium and a program product. The method is applied to a communication system, the communication system comprises a control center and a communication terminal, the communication terminal comprises a plurality of sending ends and a plurality of receiving ends, and the method comprises the following steps: after the communication terminal receives a selection instruction issued by the control center, calculating a comprehensive score between each pair of sending end and receiving end, determining a first communication path based on the comprehensive score; the control center obtains current loads of the first sending end and the first receiving end, and performs load prediction based on the current loads and a load prediction model to obtain a load prediction result; the control center performs optimization processing on the first communication path based on the load prediction result and the current load to obtain a second communication path, and the optimization processing comprises resource allocation and load balancing; the communication terminal performs communication based on the second communication path. According to the method, the communication reliability and stability are improved.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a wireless communication method, system, device, medium and program product. Background Art

[0002] With the rapid development of information technology, the Industrial Internet, as a new generation of information infrastructure, is being widely used in production and management in various industries. 5G technology has become one of the key communication technologies in the Industrial Internet due to its high speed, low latency and large number of connections. In order to meet the needs of real-time data transmission and high reliability in the Industrial Internet, 5G wireless communication networks have put forward higher requirements in handling large-scale device connections, ultra-low latency, and efficient data transmission.

[0003] In traditional wireless communication systems, ensuring communication quality is always the core task, and resource allocation strategy plays a vital role in it. For a long time, such systems usually rely on static resource allocation strategies to provide a solid guarantee for communication quality.

[0004] However, this resource allocation strategy based on static configuration has obvious limitations. Since it fails to fully consider real-time load fluctuations, some network resources cannot be used efficiently, and even a communication path may be overloaded or resources may be wasted. Summary of the invention

[0005] Embodiments of the present application provide wireless communication methods, systems, devices, media, and program products to improve the reliability and stability of communications.

[0006] In a first aspect, an embodiment of the present application provides a wireless communication method, including: applied to a communication system, the communication system including a control center and a communication terminal, the communication terminal including multiple transmitting terminals and multiple receiving terminals, the method including:

[0007] After receiving the selection instruction sent by the control center, the communication terminal calculates a comprehensive score between each pair of the transmitting end and the receiving end, and determines a first communication path based on the comprehensive score, wherein the comprehensive score is used to indicate the communication performance between each pair of the transmitting end and the receiving end, and the first communication path includes the first transmitting end and the first receiving end;

[0008] The control center obtains the current load of the first transmitting end and the first receiving end, and performs load prediction based on the current load and a load prediction model to obtain a load prediction result, wherein the load prediction model is obtained by training based on historical load data, and the load prediction result is used to indicate a load change of the transmitting end or the receiving end within a preset time period;

[0009] The control center optimizes the first communication path based on the load prediction result and the current load to obtain a second communication path, wherein the optimization includes resource allocation and load balancing;

[0010] The communication terminal performs communication based on the second communication path.

[0011] In a possible implementation, calculating a comprehensive score between each pair of a sending end and a receiving end and determining a first communication path includes:

[0012] Determine a plurality of communication paths according to the plurality of transmitting ends and the plurality of receiving ends, each communication path including a transmitting end and a receiving end;

[0013] For any one of the multiple communication paths, the comprehensive score is calculated according to the communication performance influencing factors and the weights corresponding to each communication performance influencing factor, wherein the communication performance influencing factors include signal strength, bandwidth, load, distance, delay, and interference, and the weight is used to indicate the importance of each factor on the communication performance;

[0014] A highest comprehensive score is determined from the multiple comprehensive scores, and a communication path corresponding to the highest comprehensive score is used as the first communication path.

[0015] In a possible implementation, performing load prediction based on the current load and the load prediction model to obtain a load prediction result includes:

[0016] Based on the current loads of the first transmitting end and the first receiving end, load balancing is performed on the first transmitting end and the first receiving end, and the current loads of the first transmitting end and the first receiving end after the load balancing is determined;

[0017] The current loads of the first transmitting end and the first receiving end after the load balancing process are input into the load prediction model to perform load prediction and obtain a load prediction result.

[0018] In a possible implementation, optimizing the first communication path based on the load prediction result and the current load to obtain the second communication path includes:

[0019] Allocating resources to the first communication path according to the load prediction result;

[0020] Based on the first communication path after load balancing processing and resource allocation, the second communication path is obtained.

[0021] In a possible implementation manner, the communication terminal performs communication based on the second communication path, including:

[0022] Determine a plurality of power control strategies according to a preset rule, and determine a target transmit power from the plurality of power control strategies based on a first communication parameter, wherein the first communication parameter includes signal strength, interference, and noise;

[0023] Determining a preset number of gain vectors from a preset transmission gain range, and determining a target transmission gain based on a second communication parameter and the preset number of gain vectors, wherein the second communication parameter includes a network load, a signal quality, and an interference intensity;

[0024] The transmitting end sends a signal to the receiving end based on the second communication path, and the signal is determined by the transmitting end after adjustment according to the target transmission power and the target transmission gain.

[0025] In a possible implementation, determining the target transmit power from the multiple candidate transmit powers based on the first communication parameter includes:

[0026] Initialize a particle swarm, wherein the particle swarm includes a plurality of particles, and each particle corresponds to a power control strategy;

[0027] For any one of the plurality of particles, determining the fitness corresponding to the position of the particle according to the signal strength, interference, and noise;

[0028] The position and speed of the particle are updated according to a preset update rule, and based on the updated particle, the individual optimal position is determined;

[0029] Based on the individual best positions of multiple particles, a global best position is determined, and the global best position is used as the target emission power.

[0030] In a possible implementation, determining a target transmission gain based on the second communication parameter and the preset number of gain vectors includes:

[0031] For any one of the preset number of gain vectors, determining the fitness corresponding to the gain vector;

[0032] Based on the fitness, determining a selection probability of the gain vector;

[0033] Iteratively updating the preset number of gain vectors according to the selection probability until a preset condition is met;

[0034] A target transmission gain is determined based on the iteratively updated gain vector and the fitness corresponding to the iteratively updated gain vector.

[0035] In a second aspect, an embodiment of the present application provides a wireless communication system, including a control center and a communication terminal, wherein the communication terminal includes multiple transmitting terminals and multiple receiving terminals;

[0036] The communication terminal is used to calculate a comprehensive score between each pair of a transmitting end and a receiving end after receiving the selection instruction sent by the control center, and determine a first communication path, wherein the comprehensive score is used to indicate the communication performance between each pair of a transmitting end and a receiving end, and the first communication path includes a first transmitting end and a first receiving end;

[0037] The control center is used to obtain the current load of the first transmitting end and the first receiving end, and perform load prediction based on the current load and a load prediction model to obtain a load prediction result, wherein the load prediction model is obtained by training based on historical load data, and the load prediction result is used to indicate the load change of the transmitting end or the receiving end within a preset time period;

[0038] The control center is further configured to optimize the first communication path based on the load prediction result and the current load to obtain a second communication path, wherein the optimization includes resource allocation and load balancing;

[0039] The communication terminal is used for communicating based on the second communication path.

[0040] In one possible implementation, the communication terminal is used to determine multiple communication paths based on the multiple transmitting ends and the multiple receiving ends, each communication path includes a transmitting end and a receiving end; for any one of the multiple communication paths, the comprehensive score is calculated based on communication performance influencing factors and weights corresponding to each communication performance influencing factor, the communication performance influencing factors include signal strength, bandwidth, load, distance, delay, interference, and the weight is used to indicate the importance of each factor on the communication performance; from the multiple comprehensive scores, the highest comprehensive score is determined, and the communication path corresponding to the highest comprehensive score is used as the first communication path.

[0041] In one possible implementation, the control center is used to perform load balancing on the first transmitting end and the first receiving end based on the current loads of the first transmitting end and the first receiving end, and determine the current loads of the first transmitting end and the first receiving end after the load balancing process; input the current loads of the first transmitting end and the first receiving end after the load balancing process into the load prediction model, perform load prediction, and obtain a load prediction result.

[0042] In a possible implementation, the control center is configured to allocate resources to the first communication path according to the load prediction result; and obtain the second communication path based on the first communication path after load balancing processing and resource allocation.

[0043] In one possible implementation, a control center is used to determine a plurality of power control strategies according to preset rules, and determine a target transmit power from the plurality of power control strategies based on a first communication parameter, wherein the first communication parameter includes signal strength, interference, and noise; determine a preset number of gain vectors from a preset transmit gain range, and determine a target transmit gain based on a second communication parameter and the preset number of gain vectors, wherein the second communication parameter includes network load, signal quality, and interference strength; and a transmitting end sends a signal to a receiving end based on a second communication path, wherein the signal is determined by the transmitting end after adjustment based on the target transmit power and the target transmit gain.

[0044] In a possible implementation, a control center is used to initialize a particle swarm, wherein the particle swarm includes a plurality of particles, and each particle corresponds to a power control strategy; for any one of the plurality of particles, the fitness corresponding to the position of the particle is determined according to the signal strength, interference, and noise; the position and speed of the particle are updated according to a preset update rule, and an individual optimal position is determined based on the updated particle; a global optimal position is determined based on the individual optimal positions of the plurality of particles, and the global optimal position is used as the target transmission power.

[0045] In one possible implementation, the control center is used to determine the fitness corresponding to any one of the preset number of gain vectors; determine the selection probability of the gain vector based on the fitness; iteratively update the preset number of gain vectors according to the selection probability until a preset condition is met; and determine the target transmission gain based on the iteratively updated gain vector and the fitness corresponding to the iteratively updated gain vector.

[0046] In a third aspect, an embodiment of the present application provides a wireless communication device, including: a memory, a processor;

[0047] The memory stores computer-executable instructions;

[0048] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0049] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementations of the first aspect.

[0050] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0051] The wireless communication method, system, device, medium and program product provided in the embodiments of the present application estimate the performance of the transmitter and the receiver by calculating the scoring function between each pair of transmitters and receivers; determine the first communication path to achieve automatic selection of the optimal communication path; then perform load prediction based on the current load of the transmitter and the receiver and the load prediction model to obtain a load prediction result, so as to optimize the communication path and optimize the communication performance according to the load prediction result, and then communicate through the optimized second communication path, thereby improving the reliability and stability of communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0053] Figure 1 A wireless communication system architecture view provided for an embodiment of the present application;

[0054] Figure 2 A wireless communication method according to an embodiment of the present invention is provided. Figure 1 ;

[0055] Figure 3 A wireless communication method according to an embodiment of the present invention is provided. Figure 2 ;

[0056] Figure 4 A wireless communication method according to an embodiment of the present invention is provided. Figure 3 ;

[0057] Figure 5 A schematic diagram of the structure of a wireless communication device provided in an embodiment of the present application.

[0058] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0059] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0060] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein, for example. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, products or devices.

[0061] It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0062] With the rapid development of information technology, the Industrial Internet, as a new generation of information infrastructure, is being widely used in production and management in various industries. 5G technology has become one of the key communication technologies in the Industrial Internet due to its high speed, low latency and large number of connections. In order to meet the needs of real-time data transmission and high reliability in the Industrial Internet, 5G wireless communication networks have put forward higher requirements in handling large-scale device connections, ultra-low latency, and efficient data transmission.

[0063] In traditional wireless communication systems, ensuring communication quality is always the core task, and resource allocation strategy plays a vital role in it. For a long time, such systems usually rely on static resource allocation strategies to provide a solid guarantee for communication quality.

[0064] In the prior art, network load scheduling usually relies on static resource allocation strategies and fails to fully consider real-time load fluctuations, resulting in the inefficient use of some network resources and even the problem of overload or resource waste of a certain communication path.

[0065] The wireless communication method provided in the present application predicts the load changes of the transmitting end or the receiving end within a preset time period through the current load and the load prediction model, and optimizes the communication path according to the load changes within the preset time period, thereby solving the problem that some network resources cannot be efficiently utilized, resulting in overload or waste of resources on a certain communication path.

[0066] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0067] Figure 1 The wireless communication system architecture view provided in the embodiment of the present application is as follows: Figure 1 As shown, the communication system 1 includes a control center 10 and a communication terminal 11, and the communication terminal 11 includes multiple transmitting terminals 111 and multiple receiving terminals 112. When the communication terminal 11 receives the selection instruction issued by the control center 10, it determines the first communication path from the multiple transmitting terminals 111 and the multiple receiving terminals 112. The transmitting terminal 111 and the receiving terminal 112 both use independent core processors, and the core processor of the transmitting terminal and the core processor of the receiving terminal interact with each other. By selecting the transmitting terminal and the receiving terminal, the two core processors in the wireless communication terminal of the device are independently controlled.

[0068] Among them, the transmitting end can be, for example, a 5G wireless terminal transmitting end; the receiving end can be, for example, a 5G wireless terminal receiving end.

[0069] Figure 2 A wireless communication method according to an embodiment of the present invention is provided. Figure 1 ,like Figure 2 As shown, this method is applied to Figure 1 The communication system shown, the method comprising:

[0070] S201, after receiving the selection instruction sent by the control center, the communication terminal calculates the comprehensive score between each pair of the transmitting end and the receiving end, and determines the first communication path based on the comprehensive score;

[0071] The selection instruction is used to indicate the selection of a transmitting end and a receiving end; the comprehensive score is used to indicate the communication performance between each pair of transmitting ends and receiving ends, and the first communication path includes a first transmitting end and a first receiving end;

[0072] The remote control platform generates selection instructions for the transmitter and receiver as needed, and sends the selection instructions to the communication terminal through a wireless network or a wired connection. After receiving the selection instruction, the communication terminal calculates the comprehensive score between each pair of transmitters and receivers based on the built-in selection algorithm and the factors affecting the communication performance between the transmitter and receiver, and evaluates the performance of multiple transmitters and receivers to determine the first communication path.

[0073] In a possible implementation manner, a specific process of calculating a comprehensive score between each pair of a transmitting end and a receiving end and determining the first communication path is described in detail, including:

[0074] According to multiple transmitting ends and multiple receiving ends, multiple communication paths are determined; for any one of the multiple communication paths, a comprehensive score is calculated according to communication performance influencing factors and the weight corresponding to each communication performance influencing factor; from the multiple comprehensive scores, the highest comprehensive score is determined, and the communication path corresponding to the highest comprehensive score is used as the first communication path.

[0075] Among them, each communication path includes a transmitting end and a receiving end; factors affecting communication performance include signal strength, bandwidth, load, distance, delay, and interference, and the weight is used to indicate the importance of each factor on communication performance.

[0076] The scoring function is expressed as follows:

[0077]

[0078] in, For the sender With the receiving end The signal strength between is the maximum value of signal strength, is the bandwidth of the path, is the maximum value of bandwidth, is the load condition of the path; is the maximum load value, is the distance of the path, is the maximum value of the distance, is the delay of the path, is the maximum delay, is the interference degree of the path, is the maximum interference value, is the weight coefficient of each influencing factor, indicating the importance of each factor to the final selection. The weight coefficient can be adjusted according to specific application scenarios and requirements.

[0079] Exemplary: The communication terminal includes two transmitting terminals i=1, 2 and two receiving terminals j=1, 2, and the related parameters are as follows:

[0080] From sender 1 to receiver 1:

[0081]

[0082] From sender 1 to receiver 2:

[0083]

[0084] From sender 2 to receiver 1:

[0085]

[0086] From sender 2 to receiver 2:

[0087]

[0088] Assume the weight coefficient is:

[0089] The maximum values ​​are:

[0090]

[0091] Based on the above values ​​and the scoring function, the comprehensive score between each pair of senders and receivers is calculated:

[0092] From sender 1 to receiver 1:

[0093]

[0094] From sender 1 to receiver 2:

[0095]

[0096] From sender 2 to receiver 1:

[0097]

[0098] From sender 2 to receiver 2:

[0099]

[0100] According to the above scoring results, the best choice is sender 2 to receiver 1, which has the highest score P21=0.3475. The communication terminal evaluates the communication performance between each pair of senders and receivers through this selection algorithm, and finally automatically selects the best communication path.

[0101] S202: The control center obtains the current load of the first transmitting end and the first receiving end, and performs load prediction based on the current load and the load prediction model to obtain a load prediction result;

[0102] The load prediction model is trained based on historical load data, and the load prediction result is used to indicate the load change of the transmitter or receiver within a preset period of time;

[0103] The control center obtains the current load of the first transmitting end and the first receiving end in real time, and inputs the current load of the first transmitting end and the first receiving end into the load prediction model to perform load prediction. The output of the load prediction model is the load prediction result.

[0104] The control center can obtain the current load by receiving in real time the data sent by the first transmitting end and the first receiving end according to a preset period; the control center may include, for example, a load monitoring system, through which the current load of the first transmitting end and the first receiving end is collected in real time.

[0105] The load prediction model may be based on, for example, support vector machine (SVM) training or long short-term memory network (LSTM).

[0106] S203: The control center optimizes the first communication path based on the load prediction result and the current load to obtain a second communication path;

[0107] Among them, optimization processing includes resource allocation and load balancing;

[0108] According to the load prediction results, the control center optimizes the first communication path, including resource allocation and load balancing, to obtain the second communication path. The load prediction can help the control center determine the terminal load status in advance and avoid temporary overload.

[0109] In a possible implementation, the adjusted resource allocation is verified through a feedback mechanism to ensure that the adjusted load distribution is more reasonable.

[0110] The communication terminal sends the feedback information fed back by the receiving end to the control center. The feedback information includes transmission signal quality, interference, and throughput. The control center dynamically adjusts the selection strategy based on these feedbacks to achieve adaptive adjustment.

[0111] S204. The communication terminal communicates based on the second communication path.

[0112] The communication terminal communicates based on the second communication path, and the core processors of the sending and receiving ends exchange and synchronize data through an efficient protocol. The data interaction between the core processors needs to achieve timing synchronization to ensure real-time data transmission. The clock synchronization algorithm, such as the Network Time Protocol (NTP), is used to ensure the clock accuracy of the core processors at both ends to avoid data inconsistency caused by different delays.

[0113] The wireless communication method provided in the embodiment of the present application estimates the performance of the transmitter and the receiver by calculating the scoring function between each pair of transmitters and receivers; determines the first communication path and realizes the automatic selection of the best communication path; and then performs load prediction based on the current load of the transmitter and the receiver and the load prediction model to obtain the load prediction result, so as to optimize the communication path and the communication performance according to the load prediction result, and then communicates through the optimized second communication path, thereby improving the reliability and stability of communication.

[0114] Figure 3 A wireless communication method according to an embodiment of the present invention is provided. Figure 2 ,like Figure 3 As shown, in this embodiment Figure 2 Based on the embodiment, load prediction is performed based on the current load and the load prediction model to obtain a load prediction result, and based on the load prediction result and the current load, the first communication path is optimized to obtain a second communication path. The method includes:

[0115] S301, the control center obtains the current load of the first transmitting end and the first receiving end;

[0116] The method of obtaining the current load in step S301 is similar to that in step S202 and will not be described again here.

[0117] S302: Based on the current loads of the first transmitting end and the first receiving end, perform load balancing processing on the first transmitting end and the first receiving end, and determine the current loads of the first transmitting end and the first receiving end after the load balancing processing;

[0118] Set the load states of the sender and receiver to ,in is the load at the sending end, The load on the receiving end, the goal of load balancing is to minimize the load difference between the two, the specific balancing objective function can be expressed as:

[0119]

[0120] If the load on the sender Exceeding a certain threshold Then adjust the task allocation and transfer some tasks to the receiving end or other sending end until and Achieve a balance.

[0121] S303, inputting the current loads of the first transmitting end and the first receiving end after load balancing processing into a load prediction model, performing load prediction, and obtaining a load prediction result;

[0122] The load prediction model is usually trained based on historical load data. For example, load prediction is performed using a support vector machine (SVM). The regression model of SVM is expressed as: ,in, are input characteristics (such as current load, historical load, etc.), is the weight vector, is the bias term, is the predicted load value, and the SVM trains the model by minimizing the following loss function:

[0123]

[0124] in, is the regularization parameter, which controls the penalty of the error, It is the allowable error of each sample. By training the support vector machine model, the load of the terminal at a certain moment in the future is predicted, and the load adjustment is made in advance based on the prediction results.

[0125] S304, allocating resources to the first communication path according to the load prediction result;

[0126] Dynamically adjust the resource allocation of the sender and receiver based on the output of the load prediction model. For example: Assuming that the load of a certain terminal is predicted to exceed the threshold, dynamically adjust the power and bandwidth of the heavily loaded endpoint to prevent it from being overloaded; if the load prediction shows that the load of a certain path is too high, switch to an alternative path to avoid overloading a single path. In order to ensure the efficient execution of the adaptive path selection strategy, according to the load prediction of each terminal, select the path that minimizes the load difference between the sender and the receiver.

[0127] S305 . Obtain a second communication path based on the first communication path after load balancing and resource allocation.

[0128] The wireless communication method provided in the embodiment of the present application performs load balancing processing based on the current loads of the first transmitting end and the first receiving end obtained, so as to minimize the load difference between the first transmitting end and the first receiving end; predicts the load changes of the first transmitting end and the first receiving end through a load prediction model to obtain a load prediction result, so as to help the system judge the terminal load status in advance and avoid temporary overload; then allocates resources to the first communication path according to the load prediction result, and obtains the second communication path based on the first communication path after load balancing processing and resource allocation, so as to ensure the efficient execution of the adaptive path selection strategy and optimize the communication performance.

[0129] Figure 4 A wireless communication method according to an embodiment of the present invention is provided. Figure 3 ,like Figure 4 As shown, in this embodiment Figure 2 Based on the embodiment, the communication terminal performs communication based on the second communication path in detail. The method includes:

[0130] S401, determining a plurality of power control strategies according to a preset rule, and determining a target transmit power from the plurality of power control strategies based on a first communication parameter;

[0131] Wherein, the first communication parameter includes signal strength, interference, and noise;

[0132] The transmit power is calculated based on the following formula:

[0133]

[0134] in, is the minimum transmit power, is the signal attenuation factor, is the distance between the receiver and the transmitter, is the reference distance, is the path loss index, which ranges from 2 to 4 and represents the degree of signal propagation loss. is the interference correction factor calculated based on the current environment;

[0135] According to the distance of the receiving end and environmental signal attenuation , calculate the loss of the current path. The effects of signal attenuation and interference are combined to adjust the transmit power , to ensure that the receiving end can receive the signal with appropriate power.

[0136] In a possible implementation manner, a specific process of determining a target transmit power from a plurality of candidate transmit powers based on a first communication parameter is described in detail, including:

[0137] Initialize the particle swarm; for any particle among multiple particles, determine the fitness corresponding to the position of the particle according to the signal strength, interference, and noise; update the position and speed of the particle according to the preset update rules, and determine the individual best position based on the updated particles; determine the global best position based on the individual best positions of multiple particles, and use the global best position as the target transmission power.

[0138] The particle swarm includes multiple particles, each particle corresponds to a power control strategy; and the fitness is used to indicate the quality of the received signal.

[0139] Each particle represents a possible power control strategy. The position of the particle indicates the transmission power , and evaluate its fitness based on environmental factors (e.g., signal attenuation, interference);

[0140] The fitness function is used to evaluate whether the position of each particle can optimize the communication quality. The fitness function can be defined as a function of the quality of the received signal, expressed as:

[0141]

[0142] in, is the received signal strength, It's interference. It is noise;

[0143] S402: Update particle position and velocity

[0144] Each particle moves according to the current speed and position update rule, which is as follows:

[0145]

[0146]

[0147] in: is the velocity of the particle, is the particle's position (i.e., the emission power), is the inertia weight, which controls the decay of particle velocity. is the learning factor, controlling the particle to its optimal position and the global optimal position The speed of movement, It is a random number in the range of [0,1]. The particle adjusts its position according to the current fitness evaluation until the optimal emission power is found.

[0148] S402, determining a preset number of gain vectors from a preset transmission gain range, and determining a target transmission gain based on a second communication parameter and the preset number of gain vectors;

[0149] The second communication parameter includes network load, signal quality, and interference intensity;

[0150] Dynamically adjust the transmission gain based on network load, signal quality, and interference intensity. The purpose of adjusting the transmission gain is to optimize the signal propagation effect, improve the signal reception quality, and reduce interference.

[0151] Create a population, each individual in the population represents a possible solution, and the individuals in the population are created by random generation. For example, if the population size is set to 50, 50 gain vectors are randomly generated from the possible gain value range as the initial population.

[0152] In a possible implementation manner, a specific process of determining a target transmission gain based on a second communication parameter and a preset number of gain vectors is described in detail, including:

[0153] For any one of the preset number of gain vectors, determine the fitness corresponding to the gain vector; based on the fitness, determine the selection probability of the gain vector; according to the selection probability, iteratively update the preset number of gain vectors until a preset condition is met and stop; based on the iteratively updated gain vector and the fitness corresponding to the iteratively updated gain vector, determine the target transmission gain.

[0154] Evaluate the "goodness or badness" of each individual in the population, that is, calculate its fitness value based on the individual's solution. The fitness function is:

[0155]

[0156] in, is the received signal strength, It's interference. It is noise;

[0157] The probability of selection is determined using the following formula:

[0158]

[0159] in, Is an individual The probability of being selected, Is an individual The fitness value of is the population size. The operation of the genetic algorithm will end when the preset termination condition is met. The maximum number of generations for the algorithm to run is set. The algorithm is stopped after reaching this number of generations. The quality of the solution is continuously optimized through the genetic algorithm.

[0160] According to the fitness, a gain vector is selected, and a new gain vector is generated through the selected gain vector. It can be understood that the selection probability of a gain vector with a higher fitness value is higher. Based on the iteratively updated gain vector and the fitness corresponding to the iteratively updated gain vector, the target transmission gain is determined.

[0161] S403: The sending end sends a signal to the receiving end based on the second communication path.

[0162] The signal is determined by the transmitter after adjustment based on the target transmit power and the target transmit gain.

[0163] The wireless communication method provided in the embodiment of the present application determines the target transmission power from multiple power control strategies based on the first communication parameter, quickly determines the target transmission power in a dynamic environment, optimizes the quality of the received signal, maintains communication stability, and avoids interference or performance degradation caused by excessively high or low transmission power. Based on the second communication parameter, the transmission gain is adjusted to optimize the propagation effect of the signal, improve the reception quality of the signal, and reduce interference.

[0164] Continue to refer to Figure 1 , the wireless communication system 1 provided in this embodiment includes: a control center 10, a communication terminal 11, and the communication terminal 11 includes a plurality of transmitting terminals 111 and a plurality of receiving terminals 112;

[0165] The communication terminal 11 is used to calculate the comprehensive score between each pair of the transmitting end 111 and the receiving end 112 after receiving the selection instruction sent by the control center 10, and determine the first communication path, wherein the comprehensive score is used to indicate the communication performance between each pair of the transmitting end 111 and the receiving end 112, and the first communication path includes the first transmitting end and the first receiving end;

[0166] The control center 10 is used to obtain the current load of the first transmitting end and the first receiving end, and perform load prediction based on the current load and the load prediction model to obtain a load prediction result, wherein the load prediction model is obtained by training based on historical load data, and the load prediction result is used to indicate the load change of the transmitting end 111 or the receiving end 112 within a preset time period;

[0167] The control center 10 is further used to optimize the first communication path based on the load prediction result and the current load to obtain the second communication path, and the optimization process includes resource allocation and load balancing;

[0168] The communication terminal 11 is used for communicating based on the second communication path.

[0169] In one possible implementation, the communication terminal 11 is used to determine multiple communication paths based on multiple transmitting ends 111 and multiple receiving ends 112, each communication path includes a transmitting end 111 and a receiving end 112; for any one of the multiple communication paths, a comprehensive score is calculated based on communication performance influencing factors and weights corresponding to each communication performance influencing factor, the communication performance influencing factors include signal strength, bandwidth, load, distance, delay, interference, and the weight is used to indicate the importance of each factor on the communication performance; from the multiple comprehensive scores, the highest comprehensive score is determined, and the communication path corresponding to the highest comprehensive score is used as the first communication path.

[0170] In one possible implementation, the control center 10 is used to perform load balancing on the first transmitting end and the first receiving end based on the current loads of the first transmitting end and the first receiving end, and determine the current loads of the first transmitting end and the first receiving end after the load balancing process; input the current loads of the first transmitting end and the first receiving end after the load balancing process into the load prediction model, perform load prediction, and obtain a load prediction result.

[0171] In a possible implementation, the control center 10 is configured to allocate resources to the first communication path according to the load prediction result; and obtain the second communication path based on the first communication path after load balancing processing and resource allocation.

[0172] In one possible implementation, the control center 10 is used to determine multiple power control strategies according to preset rules, and determine the target transmission power from the multiple power control strategies based on a first communication parameter, the first communication parameter including signal strength, interference, and noise; determine a preset number of gain vectors from a preset transmission gain range, and determine the target transmission gain based on a second communication parameter and a preset number of gain vectors, the second communication parameter including network load, signal quality, and interference strength; the transmitting end 111 sends a signal to the receiving end 112 based on the second communication path, and the signal is determined by the transmitting end 111 after adjusting the target transmission power and the target transmission gain.

[0173] In a possible implementation, the control center 10 is used to initialize a particle swarm, wherein the particle swarm includes a plurality of particles, each particle corresponding to a power control strategy; for any one of the plurality of particles, the fitness corresponding to the position of the particle is determined according to signal strength, interference, and noise; the position and velocity of the particle are updated according to a preset update rule, and an individual optimal position is determined based on the updated particle; a global optimal position is determined based on the individual optimal positions of the plurality of particles, and the global optimal position is used as the target transmission power.

[0174] In a possible implementation, the control center 10 is used to determine the fitness corresponding to a gain vector for any one of a preset number of gain vectors; determine the selection probability of the gain vector based on the fitness; iteratively update the preset number of gain vectors according to the selection probability until a preset condition is met; and determine the target transmission gain based on the iteratively updated gain vector and the fitness corresponding to the iteratively updated gain vector.

[0175] The wireless communication system provided in this embodiment can execute the method provided in the above method embodiment, and its implementation principle and technical effect are similar, which will not be described in detail in this embodiment.

[0176] Figure 5 A schematic diagram of the structure of a wireless communication device provided in an embodiment of the present application. Figure 5 As shown, the electronic device 50 provided in this embodiment includes: at least one processor 501 and a memory 502. Optionally, the device 50 also includes a communication component 503. The processor 501, the memory 502 and the communication component 503 are connected via a bus 504.

[0177] In a specific implementation process, at least one processor 501 executes the computer-executable instructions stored in the memory 502, so that at least one processor 501 executes the above method.

[0178] The specific implementation process of the processor 501 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0179] In the above embodiments, it should be understood that the processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the invention can be directly implemented as a hardware processor, or can be implemented by a combination of hardware and software modules in the processor.

[0180] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk storage.

[0181] 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. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0182] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0183] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0184] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0185] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0186] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0187] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0188] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0189] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0190] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0191] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A wireless communication method, characterized in that: Applied to a communication system, the communication system includes a control center and a communication terminal, the communication terminal includes multiple transmitting terminals and multiple receiving terminals, and the method includes: After receiving the selection instruction sent by the control center, the communication terminal calculates a comprehensive score between each pair of the transmitting end and the receiving end, and determines a first communication path based on the comprehensive score, wherein the comprehensive score is used to indicate the communication performance between each pair of the transmitting end and the receiving end, and the first communication path includes the first transmitting end and the first receiving end; The control center obtains the current load of the first transmitting end and the first receiving end, and performs load prediction based on the current load and a load prediction model to obtain a load prediction result, wherein the load prediction model is obtained by training based on historical load data, and the load prediction result is used to indicate a load change of the transmitting end or the receiving end within a preset time period; The control center optimizes the first communication path based on the load prediction result and the current load to obtain a second communication path, wherein the optimization includes resource allocation and load balancing; The communication terminal performs communication based on the second communication path.

2. The method according to claim 1, characterized in that The step of calculating a comprehensive score between each pair of a transmitting end and a receiving end and determining a first communication path comprises: Determine a plurality of communication paths according to the plurality of transmitting ends and the plurality of receiving ends, each communication path including a transmitting end and a receiving end; For any one of the multiple communication paths, the comprehensive score is calculated according to the communication performance influencing factors and the weights corresponding to each communication performance influencing factor, wherein the communication performance influencing factors include signal strength, bandwidth, load, distance, delay, and interference, and the weight is used to indicate the importance of each factor on the communication performance; A highest comprehensive score is determined from the multiple comprehensive scores, and a communication path corresponding to the highest comprehensive score is used as the first communication path.

3. The method according to claim 1, characterized in that The performing load prediction based on the current load and the load prediction model to obtain a load prediction result includes: Based on the current loads of the first transmitting end and the first receiving end, load balancing is performed on the first transmitting end and the first receiving end, and the current loads of the first transmitting end and the first receiving end after the load balancing is determined; The current loads of the first transmitting end and the first receiving end after the load balancing process are input into the load prediction model to perform load prediction and obtain a load prediction result.

4. The method according to claim 3, characterized in that The optimizing the first communication path based on the load prediction result and the current load to obtain the second communication path includes: Allocating resources to the first communication path according to the load prediction result; Based on the first communication path after load balancing processing and resource allocation, the second communication path is obtained.

5. The method according to claim 1, characterized in that The communication terminal performs communication based on the second communication path, including: Determine a plurality of power control strategies according to a preset rule, and determine a target transmit power from the plurality of power control strategies based on a first communication parameter, wherein the first communication parameter includes signal strength, interference, and noise; Determining a preset number of gain vectors from a preset transmission gain range, and determining a target transmission gain based on a second communication parameter and the preset number of gain vectors, wherein the second communication parameter includes a network load, a signal quality, and an interference intensity; The transmitting end sends a signal to the receiving end based on the second communication path, and the signal is determined by the transmitting end after adjustment according to the target transmission power and the target transmission gain.

6. The method according to claim 5, characterized in that The determining the target transmit power from the plurality of candidate transmit powers based on the first communication parameter includes: Initialize a particle swarm, wherein the particle swarm includes a plurality of particles, and each particle corresponds to a power control strategy; For any one of the plurality of particles, determining the fitness corresponding to the position of the particle according to the signal strength, interference, and noise; The position and speed of the particle are updated according to a preset update rule, and based on the updated particle, the individual optimal position is determined; Based on the individual best positions of multiple particles, a global best position is determined, and the global best position is used as the target emission power.

7. The method according to claim 5, characterized in that The determining the target transmission gain based on the second communication parameter and the preset number of gain vectors includes: For any one of the preset number of gain vectors, determining the fitness corresponding to the gain vector; Based on the fitness, determining a selection probability of the gain vector; Iteratively updating the preset number of gain vectors according to the selection probability until a preset condition is met; A target transmission gain is determined based on the iteratively updated gain vector and the fitness corresponding to the iteratively updated gain vector.

8. A wireless communication system, characterized in that: The communication system includes a control center and a communication terminal, wherein the communication terminal includes a plurality of transmitting terminals and a plurality of receiving terminals; The communication terminal is used to calculate a comprehensive score between each pair of a transmitting end and a receiving end after receiving the selection instruction sent by the control center, and determine a first communication path, wherein the comprehensive score is used to indicate the communication performance between each pair of a transmitting end and a receiving end, and the first communication path includes a first transmitting end and a first receiving end; The control center is used to obtain the current load of the first transmitting end and the first receiving end, and perform load prediction based on the current load and a load prediction model to obtain a load prediction result, wherein the load prediction model is obtained by training based on historical load data, and the load prediction result is used to indicate the load change of the transmitting end or the receiving end within a preset time period; The control center is further configured to optimize the first communication path based on the load prediction result and the current load to obtain a second communication path, wherein the optimization includes resource allocation and load balancing; The communication terminal is used for communicating based on the second communication path.

9. A wireless communication device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

11. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 7 when being executed by a processor.

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