Underwater acoustic communication cooperative control method, device and equipment based on multiple parameters

Abstract

The invention relates to an underwater acoustic communication cooperative control method and device based on multiple parameters, equipment and a storage medium. The method comprises the steps of obtaining environmental parameters, calculating basic sound velocity data based on the environmental parameters, determining a sound velocity profile formula corresponding to the basic sound velocity data, correcting the basic sound velocity data based on the sound velocity profile formula to obtain corrected sound velocity, and determining the distance between an underwater node and a water surface base station. The method comprises the following steps: acquiring the corrected sound velocity, the distance, the data volume and the residual energy to be transmitted of an underwater node, inputting the corrected sound velocity, the distance, the data volume and the residual energy into a pre-constructed communication optimization model to obtain a target communication frequency and a target transmitting power, and controlling the underwater node to communicate with a water surface base station based on the target communication frequency and the target transmitting power. The communication efficiency can be improved, the communication conflict risk is reduced, the node endurance time is prolonged, and the communication stability and reliability are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of underwater communication, and in particular to a multi-parameter-based underwater acoustic communication cooperative control method and device, equipment and a storage medium. BACKGROUND

[0002] With the rapid development of underwater acoustic communication technology, the interaction demand between underwater mobile platforms and surface base stations is increasing. However, the existing underwater acoustic communication scheme relies on fixed interaction frequency and needs to pre-calculate redundant time slots manually, resulting in long communication waiting time and limited throughput. For example, in two-way communication, the superposition of maximum propagation delay and transmission delay makes the single communication delay as high as tens of seconds, which seriously restricts the real-time performance. Moreover, the existing underwater acoustic communication scheme does not consider the influence of water temperature, salinity and pressure on sound velocity, resulting in calculation error of propagation delay. For example, the change of sound velocity in the thermocline region may directly cause the misalignment of communication timing and cause data conflict. At the same time, there is a lack of dynamic perception of network topology, and local congestion occurs frequently, and the conflict probability increases exponentially with the number of nodes. In addition, the existing underwater acoustic communication scheme does not consider energy efficiency in the communication strategy. Due to the limited endurance of underwater equipment, it is difficult to support long-term tasks, resulting in low stability and reliability of underwater communication.

[0003] Therefore, how to improve the stability and reliability of underwater communication has become a technical problem to be solved by those skilled in the art. SUMMARY

[0004] In view of the above, the present application provides a multi-parameter-based underwater acoustic communication cooperative control method, device, equipment and storage medium, which aims to solve the above technical problems.

[0005] In a first aspect, the present application provides a multi-parameter-based underwater acoustic communication cooperative control method, which comprises:

[0006] obtaining an environmental parameter, and calculating basic sound velocity data based on the environmental parameter;

[0007] determining a sound velocity profile formula corresponding to the basic sound velocity data, and correcting the basic sound velocity data based on the sound velocity profile formula to obtain a corrected sound velocity;

[0008] determining the distance between the underwater node and the surface base station, and obtaining the data amount to be transmitted by the underwater node and the residual energy;

[0009] inputting the corrected sound velocity, the distance, the data amount and the residual energy into a pre-constructed communication optimization model to obtain a target communication frequency and a target transmission power;

[0010] controlling the underwater node and the surface base station to communicate based on the target communication frequency and the target transmission power.

[0011] In a second aspect, the present application provides a multi-parameter-based underwater acoustic communication collaborative control device, the multi-parameter-based underwater acoustic communication collaborative control device comprising:

[0012] Calculation module: used to obtain environmental parameters and calculate basic sound speed data based on the environmental parameters;

[0013] Correction module: used to determine the sound speed profile formula corresponding to the basic sound speed data, and correct the basic sound speed data based on the sound speed profile formula to obtain the corrected sound speed;

[0014] Acquisition module: used to determine the distance between the underwater node and the surface base station, and obtain the amount of data to be transmitted and the remaining energy of the underwater node;

[0015] Optimization module: used for inputting the corrected sound speed, the distance, the data volume and the residual energy into a pre-built communication optimization model to obtain a target communication frequency and a target transmission power;

[0016] Control module: used to control the underwater node to communicate with the surface base station based on the target communication frequency and the target transmission power.

[0017] In a third aspect, the present application provides an electronic device, comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0018] Memory for storing computer programs;

[0019] The processor is used to implement the steps of the underwater acoustic communication collaborative control method based on multiple parameters as described in any embodiment of the first aspect when executing the program stored in the memory.

[0020] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the multi-parameter-based underwater acoustic communication collaborative control method as described in any embodiment of the first aspect are implemented.

[0021] The above technical solution provided by the embodiment of the present application has the following advantages compared with the prior art:

[0022] The present application obtains environmental parameters, calculates basic sound speed data based on the environmental parameters, determines the sound speed profile formula corresponding to the basic sound speed data, corrects the basic sound speed data based on the sound speed profile formula to obtain a corrected sound speed, determines the distance between the underwater node and the surface base station, and obtains the amount of data to be transmitted and the remaining energy of the underwater node. The corrected sound speed, distance, data volume and remaining energy are input into a pre-built communication optimization model to obtain the target communication frequency and target transmission power. The target communication frequency and target transmission power output by the communication optimization model are used to collaboratively control the underwater node to communicate with the surface base station, which can improve communication efficiency, reduce conflict risks, extend node life time, and improve communication stability and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] 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.

[0024] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0025] Figure 1 This is a flowchart diagram of a preferred embodiment of the multi-parameter underwater acoustic communication cooperative control method of the present application;

[0026] Figure 2 This is a module diagram of a preferred embodiment of the multi-parameter underwater acoustic communication cooperative control device of the present application;

[0027] Figure 3 A schematic diagram of a preferred embodiment of the electronic device of the present application;

[0028] The realization of the objectives, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solutions and advantages of this application more clear, the present application is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0030] It should be noted that the descriptions of "first", "second", etc. in this application are for descriptive purposes only and should not be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" or "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but this must be based on the fact that they can be implemented by ordinary technicians in this field. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0031] Reference Figure 1 The figure shows a method flow diagram of an embodiment of the method for cooperative control of underwater acoustic communication based on multiple parameters of the present application. The method is executed by an electronic device, which can be implemented by a software system and / or a hardware system. The method for cooperative control of underwater acoustic communication based on multiple parameters includes:

[0032] Step S10: Acquire environmental parameters, and calculate basic sound speed data based on the environmental parameters;

[0033] Step S20: determining a sound velocity profile formula corresponding to the basic sound velocity data, and correcting the basic sound velocity data based on the sound velocity profile formula to obtain a corrected sound velocity;

[0034] Step S30: determining the distance between the underwater node and the surface base station, and obtaining the amount of data to be transmitted and the remaining energy of the underwater node;

[0035] Step S40: Inputting the corrected sound speed, the distance, the data volume, and the remaining energy into a pre-built communication optimization model to obtain a target communication frequency and a target transmission power;

[0036] Step S50: Based on the target communication frequency and the target transmission power, control the underwater node to communicate with the surface base station.

[0037] In this embodiment, underwater nodes are communication terminals or relay devices deployed underwater. They can include autonomous underwater vehicles, underwater gliders, underwater robots, underwater IoT terminals, and other devices. Surface base stations connect underwater nodes to land or satellite networks. They can include buoy-type base stations, ship / submersible-mounted base stations, offshore platform base stations, and other devices.

[0038] The current month is determined by the built-in real-time clock (RTC) or the mission preset timestamp, and a high-order linear equation mapping relationship between the month and the sound velocity profile formula is established based on historical ocean data. For example, in summer (June to August, corresponding to a temperature range of 25°C to 30°C), the sound velocity gradient coefficient increases significantly due to the increase in surface water temperature, while in winter (December to February, corresponding to a temperature range of 10°C to 15°C), the gradient tends to be gentle.

[0039] Since the speed of sound in underwater acoustic communication is affected by factors such as water temperature, salinity, and pressure, the basic speed of sound can be calculated based on these environmental parameters. Specifically, the acquisition of environmental parameters and the calculation of basic speed of sound data based on the environmental parameters include:

[0040] Obtain the water temperature, seawater salinity and static pressure of the underwater node at the current depth;

[0041] The basic sound speed data is calculated by using the water temperature at the current depth, the seawater salinity, and the static pressure and a preset formula.

[0042] Obtain the water temperature, seawater salinity, and static pressure of the underwater node at the current depth, and calculate the basic sound speed data according to the preset formula. The preset formula includes:

[0043] c=1450+4.21T-0.037T 2 +1.14(S-35)+0.175P

[0044] Among them, c represents the basic sound velocity data at the current depth, T represents the water temperature at the current depth, S represents the seawater salinity at the current depth, and P represents the static pressure at the current depth.

[0045] Since a single basic sound speed data cannot accurately reflect actual sound speed changes, such as sound speed changes in the thermocline region, which may cause communication timing misalignment and trigger data conflicts, correcting the sound speed can improve the accuracy of delay calculation and ensure communication reliability. After obtaining the basic sound speed data, the basic sound speed can be corrected according to the preset sound speed profile formula to obtain the corrected sound speed. For example, if the sound speed data with a basic sound speed calculation result of 1500m / s is corrected, if the sound speed profile formula for that month shows that the depth gradient coefficient is 2, at a depth of 10 meters, after correction, a more accurate sound speed data of 1505m / s is obtained.

[0046] Specifically, determining a sound speed profile formula corresponding to the basic sound speed data, and correcting the basic sound speed data based on the sound speed profile formula to obtain a corrected sound speed, includes:

[0047] According to the current month and the pre-established mapping relationship, determine the sound velocity profile formula corresponding to the basic sound velocity data;

[0048] According to the sound velocity profile formula, set the fitting sound velocity formula;

[0049] The basic sound velocity data is corrected based on the fitting sound velocity formula to obtain the corrected sound velocity.

[0050] By analyzing historical ocean data in advance, we establish a high-order linear equation mapping relationship between months and sound velocity profile formulas and store it in the database. Water temperature varies significantly in different seasons, and sound velocity is closely related to water temperature. By using the pre-established mapping relationship between months and sound velocity profile formulas, we can quickly obtain the sound velocity variation pattern that matches the current season. Suppose the high-order linear equation of the sound velocity profile formula for a certain month is:

[0051] c(z)=a0+a1z+a2z 2 +…+a n z n

[0052] Where z is the current depth, D is the total depth, and the fitting sound speed formula is:

[0053]

[0054] Substitute c(z) into the following formula and integrate it term by term to obtain the corrected sound speed, which provides more accurate sound speed data for subsequent communication delay calculation;

[0055]

[0056] c fit Indicates the corrected speed of sound.

[0057] Communication frequency and power need to be dynamically adjusted based on distance, data volume, and node energy. Distance affects signal propagation delay and energy consumption, data volume determines the urgency of the communication task, and remaining energy affects the node's endurance. Therefore, it is necessary to determine the distance between the underwater node and the surface base station and obtain the amount of data to be transmitted and the remaining energy. For example, GPS positioning or sonar ranging technology can be used to determine the real-time distance between the underwater node and the surface base station. The node's data acquisition module counts the amount of data to be transmitted in the buffer, and the energy monitoring module monitors the node's remaining energy in real time.

[0058] By building a communication optimization model that comprehensively considers factors such as sound speed, distance, data volume, and remaining energy, communication frequency and power can be optimized, thereby improving communication efficiency and energy management. For example, a communication optimization model can be built based on deep reinforcement learning, with inputs being the corrected sound speed, distance, data volume, and remaining energy, and outputting the target communication frequency and transmit power. Using a dual deep Q-network (DDQN) architecture for offline training and online optimization, the model weight parameters are updated every preset time (for example, every 5 minutes) to adapt to the dynamic environment.

[0059] Controlling communications according to optimized communication frequency and power can improve communication efficiency, reduce collision risk, and extend node lifespan, thereby enhancing communication stability and reliability. Specifically, based on the target communication frequency and target transmit power output by the model, the underwater node's communication module is controlled, causing the underwater node to transmit data at the target communication frequency and adjust its transmit power to the target transmit power. Simultaneously, carrier sensing dynamically allocates time slots to avoid collisions. For example, assuming a target communication frequency of 2 times per second and a target transmit power of 5 watts, underwater node A begins transmitting data to a surface base station. If it detects that the channel is occupied during transmission, node A delays transmission based on the carrier sensing results and resumes communication when the channel becomes free. If node A's remaining energy continues to decrease, reaching 30%, it automatically reduces its transmit power to 3 watts, and neighboring node B relays some of its data. Dynamically adjusting communication frequency and power improves communication efficiency, reduces collision risk, extends node lifespan, and enhances communication stability and reliability.

[0060] In one embodiment, the communication optimization model is obtained based on dual deep Q network training, and the training process of the communication optimization model includes:

[0061] Acquire historical communication data, and divide the historical communication data into a training set and a validation set;

[0062] Construct a joint reward function based on communication success rate, average latency, and total energy consumption;

[0063] Training a dual deep Q-network using the training set, and updating weight parameters of the dual deep Q-network based on a joint reward function;

[0064] Determining whether the joint reward function converges based on the verification set at every preset period;

[0065] If so, stop training to obtain the communication optimization model.

[0066] Collect historical underwater acoustic communication data, including key metrics such as communication success rate, latency, and energy consumption, as well as corresponding environmental parameters (water temperature, salinity, pressure, etc.), node distance, data volume, and remaining energy information. Divide the dataset into a training set and a validation set according to a preset ratio (e.g., 8:2). The training set is used to update model parameters, while the validation set is used to evaluate model performance. Assume that 10,000 sets of historical underwater acoustic communication data are collected, each containing information such as communication success or failure, send-receive interval, energy consumption, and environmental parameters. Randomly select 8,000 sets to form the training set, and the remaining 2,000 sets as the validation set.

[0067] Optimizing underwater acoustic communication requires balancing multiple objectives, including communication success rate, latency, and energy consumption. Optimizing a single metric can easily lead to poor communication quality or excessive energy consumption. By constructing a joint reward function, multiple metrics can be integrated to guide model optimization.

[0068] The formula of the joint reward function includes:

[0069] R = communication success rate - λ * average delay - μ * total energy consumption;

[0070] Among them, R represents the immediate reward, λ represents the penalty weight, and μ represents the exploration decay rate.

[0071] During training, we select 100 samples from the training set. The evaluation network predicts the Q-values ​​of these samples in their current state, and the maximum value is selected as the action Q-value. The target network predicts the Q-value of the next state, and the maximum value is selected as the Q-value. Using the Adam optimizer with a learning rate of 0.001, backpropagation is used to update the evaluation network weight parameters.

[0072] Every preset period (such as 500 training steps), the model performance is evaluated using the validation set, the mean and variance of the joint reward function value are calculated, and the convergence trend is observed. If the mean fluctuation is within the threshold and the variance is small, it is considered converged.

[0073] In one embodiment, controlling the underwater node to communicate with the surface base station based on the target communication frequency and the target transmit power includes:

[0074] Before the underwater node transmits data to the sleeping base station, it detects whether there is an idle channel;

[0075] If so, allocating a target time slot to the underwater node based on the target communication frequency;

[0076] According to the target time slot, the underwater node is controlled to communicate with the surface base station.

[0077] Due to the limited resources of underwater acoustic communication channels, multiple underwater nodes may compete for the channel simultaneously. Failure to check the channel status before transmission can easily lead to communication conflicts, causing data packets to interfere with each other and affecting communication efficiency. Using carrier sensing to detect whether the channel is idle can effectively avoid conflicts and improve communication success rates, especially in areas with high node density, where the probability of conflicts can be reduced. When an underwater node is preparing to transmit data, it activates the link layer's carrier sensing mechanism to monitor the channel status. If no other nodes are currently transmitting signals on the channel, the channel is considered idle; otherwise, the channel is considered busy and transmission must be delayed. For example, underwater node A has a data packet to send. Node A's communication module activates the carrier sensing function and continuously monitors the channel's electromagnetic wave signal characteristics. After a brief monitoring time slot (e.g., 0.1 seconds), if no other node transmission signals are detected, the channel is considered idle. This avoids blind transmission, reduces the probability of communication conflicts, and improves channel resource utilization.

[0078] In practical applications, even if an idle channel is detected, if data transmission time slots are not allocated, multiple nodes may still compete for the channel at similar times, increasing the risk of subsequent conflicts. Therefore, allocating time slots based on the target communication frequency can organize the order of node data transmission in an orderly manner to ensure smooth communication. Specifically, the communication cycle of each underwater node is calculated based on the target communication frequency output by the communication optimization model. The link layer dynamically allocates time slots to each underwater node based on this cycle and the node priority queue. Nodes with high priority (such as nodes transmitting emergency control instructions) are given priority to allocate earlier time slots.

[0079] For example, suppose the communication optimization model assigns a target communication frequency of 2 times / second and a communication cycle of 0.5 seconds to underwater node A. The current timestamp is t. The link layer assigns node A the next communication slot of t+0.5 seconds, the next of which is t+1.0 seconds, and so on. If there is also underwater node B, the target communication frequency is 1 time / second, and its communication cycle is 1.0 seconds. The system link layer allocates time slots based on the priorities of nodes A and B (assuming node A has a higher priority). Node A is assigned slots at t+0.5 seconds and t+1.0 seconds, while node B is assigned slots at t+1.0 seconds and t+2.0 seconds, etc. This achieves an orderly arrangement of multiple nodes in the time domain. By dynamically allocating time slots based on the target communication frequency and node priority, channel resources are fully utilized, multi-node communication is organized in an orderly manner, and the probability of communication conflicts is reduced.

[0080] Reasonable target time slot allocation depends not only on the target communication frequency, but also on the calculation of time slot length when multiple nodes communicate. The time slot length calculation formula is as follows:

[0081] Slot length = maximum propagation delay + maximum processing delay;

[0082] The maximum propagation delay represents the time corresponding to the longest communication distance between the underwater node and the surface base station.

[0083] The underwater node's communication module has a built-in timing control unit that starts an internal timer based on the assigned target time slot. The node begins transmitting data at the start of the target time slot and stops transmitting at the end of the time slot, regardless of whether the data has been sent. This ensures that the underwater node communicates strictly within the target time slot, further reducing the probability of communication conflicts.

[0084] The controlling of the underwater node to communicate with the surface base station includes:

[0085] During the communication between the underwater node and the surface base station, if it is detected that the number of consecutive packet losses is greater than the preset number, the node switches to the backup frequency band for communication.

[0086] In actual communications, data packets may be lost or damaged due to factors such as channel interference. A dynamic redundancy factor is used to adjust the forward error correction (FEC) strength. The redundancy factor is dynamically adjusted based on the real-time channel quality to enhance the error correction capability of the data packet. The redundancy factor is calculated as follows:

[0087]

[0088] Among them, retransmission interval = initial interval * 2 重传次数 ,When the packet loss exceeds 3 times in a row, it automatically switches to the backup frequency band to avoid channel congestion.

[0089] If underwater node A sends a data packet but doesn't receive an ACK from the surface base station, it considers the packet lost. Node A then uses a retransmission strategy with a first retransmission interval of 0.1 seconds, a second retransmission interval of 0.2 seconds, and a third retransmission interval of 0.4 seconds. If packet loss occurs three times in a row, node A automatically switches to a backup frequency band and recalculates the propagation delay. Dynamic redundancy and channel switching strategies enhance communication fault tolerance and adaptability, ensuring communication reliability in high bit error rate scenarios and ensuring data integrity.

[0090] Reference Figure 2 As shown, it is a functional module diagram of the underwater acoustic communication collaborative control device 100 based on multiple parameters of the present application.

[0091] The multi-parameter underwater acoustic communication collaborative control device 100 described in this application is installed in an electronic device. According to the functions to be implemented, the multi-parameter underwater acoustic communication collaborative control device 100 includes a calculation module 110, a correction module 120, an acquisition module 130, an optimization module 140, and a control module 150. The above modules can also be called units, which refer to a series of computer program segments that can be executed by the processor of an electronic device and can perform fixed functions, which are stored in the memory of the electronic device.

[0092] In this embodiment, the functions of each module / unit are as follows:

[0093] Calculation module 110: used to obtain environmental parameters and calculate basic sound speed data based on the environmental parameters;

[0094] Correction module 120: used to determine the sound speed profile formula corresponding to the basic sound speed data, and correct the basic sound speed data based on the sound speed profile formula to obtain a corrected sound speed;

[0095] Acquisition module 130: used to determine the distance between the underwater node and the surface base station, and obtain the amount of data to be transmitted and the remaining energy of the underwater node;

[0096] Optimization module 140: configured to input the corrected sound speed, the distance, the data volume, and the remaining energy into a pre-built communication optimization model to obtain a target communication frequency and a target transmission power;

[0097] Control module 150: used to control the underwater node to communicate with the surface base station based on the target communication frequency and the target transmission power.

[0098] In one embodiment, the obtaining of environmental parameters and calculating basic sound speed data based on the environmental parameters includes:

[0099] Obtain the water temperature, seawater salinity and static pressure of the underwater node at the current depth;

[0100] The basic sound speed data is calculated by using the water temperature at the current depth, the seawater salinity, and the static pressure and a preset formula.

[0101] In one embodiment, determining a sound speed profile formula corresponding to the basic sound speed data, and correcting the basic sound speed data based on the sound speed profile formula to obtain a corrected sound speed, includes:

[0102] According to the current month and the pre-established mapping relationship, determine the sound velocity profile formula corresponding to the basic sound velocity data;

[0103] According to the sound velocity profile formula, set the fitting sound velocity formula;

[0104] The basic sound velocity data is corrected based on the fitting sound velocity formula to obtain the corrected sound velocity.

[0105] In one embodiment, the communication optimization model is obtained based on dual deep Q network training, and the training process of the communication optimization model includes:

[0106] Acquire historical communication data, and divide the historical communication data into a training set and a validation set;

[0107] Construct a joint reward function based on communication success rate, average latency, and total energy consumption;

[0108] Training a dual deep Q-network using the training set, and updating weight parameters of the dual deep Q-network based on a joint reward function;

[0109] Determining whether the joint reward function converges based on the verification set at every preset period;

[0110] If so, stop training to obtain the communication optimization model.

[0111] In one embodiment, the formula of the joint reward function includes:

[0112] R = communication success rate - λ * average delay - μ * total energy consumption;

[0113] Among them, R represents the immediate reward, λ represents the penalty weight, and μ represents the exploration decay rate.

[0114] In one embodiment, controlling the underwater node to communicate with the surface base station based on the target communication frequency and the target transmit power includes:

[0115] Before the underwater node transmits data to the sleeping base station, it detects whether there is an idle channel;

[0116] If so, allocating a target time slot to the underwater node based on the target communication frequency;

[0117] According to the target time slot, the underwater node is controlled to communicate with the surface base station.

[0118] In one embodiment, controlling the underwater node to communicate with the surface base station includes:

[0119] During the communication between the underwater node and the surface base station, if it is detected that the number of consecutive packet losses is greater than the preset number, the node switches to the backup frequency band for communication.

[0120] Reference Figure 3 , which is a schematic diagram of a preferred embodiment of the electronic device of the present application.

[0121] The electronic device includes a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other via the communication bus 114;

[0122] Memory 113, for storing computer programs, for example, a multi-parameter-based underwater acoustic communication collaborative control program;

[0123] In some embodiments, the processor 111 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 111 is generally used to control the overall operation of the electronic device, such as performing control and processing related to data interaction or communication. In this embodiment, the processor 111 is used to execute program code stored in the memory 113 or process data.

[0124] The communication interface 112 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface). The communication interface 112 may also be used to establish a communication connection between the electronic device and other electronic devices.

[0125] The memory 113 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 113 can be an internal storage unit of the electronic device, such as the hard disk or memory of the electronic device. In other embodiments, the memory 113 can also be an external storage device of the electronic device, such as a plug-in hard disk equipped with the electronic device, a smart memory card (SMC), a secure digital (SD) card, a flash card, etc. Of course, the memory 113 can also include both the internal storage unit of the electronic device and its external storage device. In this embodiment, the memory 11 is generally used to store the operating system and various computer programs installed on the electronic device, such as the program code of the multi-parameter underwater acoustic communication cooperative control program. In addition, the memory 113 can also be used to temporarily store various types of data that have been output or are to be output.

[0126] Figure 3 Only an electronic device having components 111 - 114 is shown, but it is understood that implementing all of the shown components is not a requirement, and more or fewer components may alternatively be implemented.

[0127] In one embodiment of the present application, the processor 111 is configured to execute a program stored in the memory 113 to implement the multi-parameter-based underwater acoustic communication cooperative control method provided by any of the aforementioned method embodiments, including:

[0128] Acquiring environmental parameters, and calculating basic sound speed data based on the environmental parameters;

[0129] Determine a sound speed profile formula corresponding to the basic sound speed data, and correct the basic sound speed data based on the sound speed profile formula to obtain a corrected sound speed;

[0130] Determine the distance between the underwater node and the surface base station, and obtain the amount of data to be transmitted and the remaining energy of the underwater node;

[0131] Inputting the corrected sound speed, the distance, the data volume, and the remaining energy into a pre-built communication optimization model to obtain a target communication frequency and a target transmission power;

[0132] Based on the target communication frequency and the target transmission power, the underwater node is controlled to communicate with the surface base station.

[0133] For a detailed description of the above steps, please refer to the Figure 1 Description of a flowchart of an embodiment of a method for cooperative control of underwater acoustic communications based on multiple parameters.

[0134] In addition, an embodiment of the present application also proposes a computer-readable storage medium, which is non-volatile and volatile. The computer-readable storage medium is any one or any combination of a hard disk, a multimedia card, an SD card, a flash memory card, an SMC, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disk read-only memory (CD-ROM), a USB memory, etc. The computer-readable storage medium includes a data storage area and a program storage area. The program storage area stores a multi-parameter-based underwater acoustic communication collaborative control program 10. When the multi-parameter-based underwater acoustic communication collaborative control program 10 is executed by the processor, the following operations are implemented:

[0135] Acquiring environmental parameters, and calculating basic sound speed data based on the environmental parameters;

[0136] Determine a sound speed profile formula corresponding to the basic sound speed data, and correct the basic sound speed data based on the sound speed profile formula to obtain a corrected sound speed;

[0137] Determine the distance between the underwater node and the surface base station, and obtain the amount of data to be transmitted and the remaining energy of the underwater node;

[0138] Inputting the corrected sound speed, the distance, the data volume, and the remaining energy into a pre-built communication optimization model to obtain a target communication frequency and a target transmission power;

[0139] Based on the target communication frequency and the target transmission power, the underwater node is controlled to communicate with the surface base station.

[0140] The specific implementation of the computer-readable storage medium of the present application is roughly the same as the specific implementation of the above-mentioned multi-parameter-based underwater acoustic communication collaborative control method, and will not be repeated here.

[0141] It should be noted that the serial numbers of the embodiments of the present application are for description only and do not represent the advantages and disadvantages of the embodiments. In addition, the terms "including", "comprising" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "including a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0142] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware simulation platform, and of course, by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device to execute the methods described in each embodiment of the present application.

[0143] The above are only preferred embodiments of the present application and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A multi-parameter-based underwater acoustic communication cooperative control method, characterized in that: The method comprises: Acquiring environmental parameters, and calculating basic sound speed data based on the environmental parameters; Determine a sound speed profile formula corresponding to the basic sound speed data, and correct the basic sound speed data based on the sound speed profile formula to obtain a corrected sound speed; Determine the distance between the underwater node and the surface base station, and obtain the amount of data to be transmitted and the remaining energy of the underwater node; Inputting the corrected sound speed, the distance, the data volume, and the remaining energy into a pre-built communication optimization model to obtain a target communication frequency and a target transmission power; Based on the target communication frequency and the target transmission power, the underwater node is controlled to communicate with the surface base station.

2. The multi-parameter-based underwater acoustic communication cooperative control method according to claim 1, characterized in that: The obtaining of environmental parameters and calculating basic sound speed data based on the environmental parameters includes: Obtain the water temperature, seawater salinity and static pressure of the underwater node at the current depth; The basic sound speed data is calculated by using the water temperature at the current depth, the seawater salinity, and the static pressure and a preset formula.

3. The multi-parameter-based underwater acoustic communication cooperative control method according to claim 1, characterized in that: The step of determining a sound velocity profile formula corresponding to the basic sound velocity data and correcting the basic sound velocity data based on the sound velocity profile formula to obtain a corrected sound velocity includes: According to the current month and the pre-established mapping relationship, determine the sound velocity profile formula corresponding to the basic sound velocity data; According to the sound velocity profile formula, set the fitting sound velocity formula; The basic sound velocity data is corrected based on the fitting sound velocity formula to obtain the corrected sound velocity.

4. The multi-parameter-based underwater acoustic communication cooperative control method according to claim 1, characterized in that: The communication optimization model is obtained based on dual deep Q network training. The training process of the communication optimization model includes: Acquire historical communication data, and divide the historical communication data into a training set and a validation set; Construct a joint reward function based on communication success rate, average latency, and total energy consumption; Training a dual deep Q-network using the training set, and updating weight parameters of the dual deep Q-network based on a joint reward function; Determining whether the joint reward function converges based on the verification set at every preset period; If so, stop training to obtain the communication optimization model.

5. The multi-parameter-based underwater acoustic communication cooperative control method according to claim 4, characterized in that: The formula of the joint reward function includes: R = communication success rate - λ * average delay - μ * total energy consumption; Among them, R represents the immediate reward, λ represents the penalty weight, and μ represents the exploration decay rate.

6. The multi-parameter-based underwater acoustic communication cooperative control method according to claim 1, characterized in that: The controlling the underwater node to communicate with the surface base station based on the target communication frequency and the target transmit power includes: Before the underwater node transmits data to the sleeping base station, it detects whether there is an idle channel; If so, allocating a target time slot to the underwater node based on the target communication frequency; According to the target time slot, the underwater node is controlled to communicate with the surface base station.

7. The multi-parameter-based underwater acoustic communication cooperative control method according to any one of claims 1 to 6, characterized in that: The controlling the underwater node to communicate with the surface base station includes: During the communication between the underwater node and the surface base station, if it is detected that the number of consecutive packet losses is greater than the preset number, the node switches to the backup frequency band for communication.

8. A multi-parameter underwater acoustic communication cooperative control device, characterized in that: The device comprises: Calculation module: used to obtain environmental parameters and calculate basic sound speed data based on the environmental parameters; Correction module: used to determine the sound speed profile formula corresponding to the basic sound speed data, and correct the basic sound speed data based on the sound speed profile formula to obtain the corrected sound speed; Acquisition module: used to determine the distance between the underwater node and the surface base station, and obtain the amount of data to be transmitted and the remaining energy of the underwater node; Optimization module: used for inputting the corrected sound speed, the distance, the data volume and the residual energy into a pre-built communication optimization model to obtain a target communication frequency and a target transmission power; Control module: used to control the underwater node to communicate with the surface base station based on the target communication frequency and the target transmission power.

9. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; Memory for storing computer programs; The processor is configured to implement the multi-parameter-based underwater acoustic communication collaborative control method according to any one of claims 1 to 7 when executing the program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the multi-parameter-based underwater acoustic communication cooperative control method according to any one of claims 1 to 7 is implemented.

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