Underwater wireless optical communication networking method and system based on improved time slot ALOHA protocol

Abstract

The invention relates to an underwater wireless optical communication networking method and system based on an improved time slot ALOHA protocol. The method comprises the following steps: firstly, acquiring original audio and video data and processing the original audio and video data to obtain a frame coding signal; based on this, an initial time slot allocation scheme is generated by measuring the propagation time delay of an underwater node optical signal. Then, underwater environment data are collected, high-risk nodes are determined in combination with the initial time slot allocation scheme, and an optimized time slot allocation table is obtained; and then, extracting data from the optimized time slot distribution table, combining with a network load monitoring value, and optimizing a communication strategy by using a load balancing algorithm. And finally, monitoring the operation condition of the communication strategy to obtain real-time monitoring data, and performing optimization adjustment in combination with the channel state parameters to obtain final communication protocol parameters. According to the steps, data transmission conflicts are effectively reduced, the time slot utilization rate is improved, wireless optical communication networking can better adapt to the complex and changeable underwater environment, the signal interference and the packet loss rate are reduced, and stability and reliability of communication are guaranteed.

Description

Technical Field

[0001] The present invention belongs to the field of communication technologies, and particularly relates to an underwater wireless optical communication networking method and system based on an improved slotted ALOHA protocol. Background Art

[0002] With the development of communication technologies, an underwater wireless optical communication networking technology based on an improved slotted ALOHA protocol has emerged. With the acceleration of the process of ocean resource development, the importance of underwater wireless communication technologies has become increasingly prominent. Underwater wireless optical communication has become a research hotspot in the field of underwater communication due to its advantages such as large bandwidth, high speed, and high confidentiality. However, the special optical properties of water bodies, such as the absorption, scattering, and turbulence effects on light beams, severely limit the communication distance and quality, and the complex underwater environment also poses great challenges to system design and performance evaluation. Although the traditional slotted ALOHA protocol has improved the channel utilization rate to a certain extent, in a complex underwater environment with multiple nodes, it still faces problems such as data transmission conflicts and low node access efficiency, and it is difficult to meet the requirements of underwater communication for stability and efficiency. Summary of the Invention

[0003] Based on this, it is necessary to provide an underwater wireless optical communication networking method and system based on an improved slotted ALOHA protocol that can improve the overall efficiency of data transmission and ensure stable and reliable communication in view of the above technical problems.

[0004] In a first aspect, the present application provides an underwater wireless optical communication networking method based on an improved slotted ALOHA protocol, including:

[0005] Obtain original underwater audio and video data; process the original audio and video data to obtain a frame coding signal, and use a dynamic time slot allocation algorithm based on the underwater node optical signal propagation delay to obtain an initial time slot allocation scheme.

[0006] Obtain underwater environment data; determine high-risk nodes based on the environment data in combination with the initial time slot allocation scheme and adjust the time slot priorities to obtain an optimized time slot allocation table.

[0007] Extract data from the optimized time slot allocation table and use a load balancing algorithm in combination with the network load monitoring value to obtain a communication strategy after load adjustment.

[0008] Monitor the operation of the communication strategy to obtain real-time monitoring data, and combine it with channel state parameters to obtain the final communication protocol parameters.

[0009] In one embodiment, processing the original audio and video data to obtain a frame coding signal, and using a dynamic time slot allocation algorithm based on the underwater node optical signal propagation delay to obtain an initial time slot allocation scheme includes:

[0010] Real-time processing is performed on the original audio and video data using a field-programmable gate array to obtain a frame coding signal; the frame coding signal includes a preamble, a sending node number, a receiving node number, a data type, a data segment, and a check segment.

[0011] Obtain the propagation delay data of the underwater nodes transmitting and receiving optical signals and perform calculations to obtain the distance information between each underwater node; the propagation delay data is calculated from the underwater node position information and the optical signal transmission rate.

[0012] Calculate the distance difference between each node based on the distance information to construct a distance difference matrix and obtain the time delay compensation parameter.

[0013] Use the dynamic time slot allocation algorithm to process the time delay compensation parameter to allocate corresponding time slot lengths to different nodes and obtain a time slot allocation table including time window markers.

[0014] Perform timestamp synchronization processing on the frame coding signal based on the time slot allocation table and match it with the remaining energy parameter of the underwater node to obtain a time slot matching result.

[0015] Adjust the length of the time window marker in the time slot allocation table according to the time slot matching result to obtain an initial time slot allocation scheme.

[0016] In one embodiment, based on the environmental data and combined with the initial time slot allocation scheme, high-risk nodes are determined and the time slot priority is adjusted to obtain an optimized time slot allocation table, including:

[0017] Based on the environmental data, use the optical signal attenuation model to calculate the channel state change rate combined with the optical signal intensity scattering value to obtain the channel state parameter for evaluating the dynamic fluctuation degree of the channel quality.

[0018] Obtain the time slot occupancy rate and time slot interval parameter in the initial time slot allocation scheme; the time slot occupancy rate and time slot interval parameter are extracted from the time slot allocation record.

[0019] Input the channel state parameter and the time slot occupancy rate into the dynamic priority model to perform quantitative evaluation on each node according to the indicators to obtain high-risk nodes; the indicators include at least one factor among the data transmission success rate, transmission delay, and packet loss rate of the node under the current channel conditions.

[0020] Analyze the high-risk nodes according to their risk levels and the urgency of data transmission requirements to obtain the corresponding time slot weight sequence.

[0021] Update the time slot allocation order and length according to the time slot weight sequence and combine the time slot interval parameter to generate a conflict detection result.

[0022] Based on the conflict detection results, use the iterative optimization algorithm to eliminate the overlapping time slot intervals and obtain the optimized time slot allocation table; the optimized time slot allocation table includes the mapping relationship between the node identification number and the time slot start timestamp.

[0023] In one embodiment, the channel state change rate is calculated by the following formula:

[0024]

[0025] Where C rate represents the channel state change rate, I0 represents the initial intensity of the optical signal, d represents the transmission distance, I(t) represents the intensity of the optical signal received at time t, T represents the turbidity, v represents the ocean current speed, θ represents the angle between the ocean current speed and the optical signal transmission direction, k(λ) represents the attenuation coefficient related to the optical signal wavelength λ, m represents the scattering coefficient related to the scattering characteristics, and α, β, γ, and η represent the weight coefficients determined according to the actual environment and experimental data.

[0026] In one embodiment, perform data extraction on the optimized time slot allocation table and combine it with the network load monitoring value using the load balancing algorithm to obtain the communication strategy after load adjustment, including:

[0027] Obtain the time slot allocation parameters in the optimized time slot allocation table; the time slot allocation parameters include the priority weights of each time slot and the time slot data characteristics.

[0028] Extract the time slot occupancy rate matrix according to the time slot data characteristics; the time slot occupancy rate matrix includes the time slot occupancy status of each node within a preset period.

[0029] Obtain the load volatility in the network load monitoring value; the load volatility is calculated from the load differences of each node within consecutive monitoring periods.

[0030] Input the time slot occupancy rate matrix and the load volatility into the load balancing algorithm to obtain the policy adjustment parameters, and the policy adjustment parameters include the time slot reallocation ratio and the priority correction amount.

[0031] Perform a superposition operation on the policy adjustment parameters and the priority weights to obtain the updated set of time slot allocation parameters.

[0032] Generate the communication strategy after load adjustment according to the set of time slot allocation parameters; the communication strategy includes the policy effective delay and the policy execution sequence.

[0033] In one embodiment, monitor the operation of the communication strategy to obtain real-time monitoring data and combine it with the channel state parameters to obtain the final communication protocol parameters, including:

[0034] Extract the real-time transmission rate and the channel bit error rate of the communication strategy from the real-time monitoring data.

[0035] Calculate the dynamic bandwidth threshold based on the real-time transmission rate and the channel bit error rate; the dynamic bandwidth threshold uses a linear weighting model to fuse the channel interference index.

[0036] Obtain the spectrum occupancy rate and the delay fluctuation coefficient in the channel state parameters.

[0037] Input the dynamic bandwidth threshold and the spectrum occupancy rate into the protocol parameter adjustment model to obtain the adaptive weight coefficient.

[0038] Fuse the delay fluctuation coefficient and the adaptive weight coefficient to generate the final communication protocol parameters.

[0039] In a second aspect, the present application also provides an underwater wireless optical communication networking system based on an improved slotted ALOHA protocol. The system includes:

[0040] An initial time slot allocation module, configured to obtain underwater original audio and video data; and also configured to process the original audio and video data to obtain a frame coding signal and use a dynamic time slot allocation algorithm based on the underwater node optical signal propagation delay to obtain an initial time slot allocation scheme.

[0041] A time slot optimization module, configured to obtain underwater environment data; and also configured to determine high-risk nodes based on the environment data combined with the initial time slot allocation scheme and adjust the time slot priority to obtain an optimized time slot allocation table.

[0042] A communication protocol optimization module, configured to extract data from the optimized time slot allocation table and use a load balancing algorithm in combination with the network load monitoring value to obtain a communication strategy after load adjustment; and also configured to monitor the operation of the communication strategy to obtain real-time monitoring data and combine it with the channel state parameters to obtain the final communication protocol parameters.

[0043] In a third aspect, the present application also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it is as described in the previous method.

[0044] In a fourth aspect, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is as described in the previous method.

[0045] The above-mentioned underwater wireless optical communication networking method and system based on the improved slotted ALOHA protocol. First, obtain the original audio and video data, process and encapsulate it into a frame coding signal including specific information. At the same time, measure the propagation delay of the optical signal of the underwater node, and use the dynamic slot allocation algorithm to generate an initial slot allocation scheme. Then, collect the underwater environment data, determine the high-risk nodes in combination with the initial slot allocation scheme, adjust the slot priority according to the risk level and the urgency of data transmission, and obtain an optimized slot allocation table. Next, extract data from the optimized slot allocation table, and use the load balancing algorithm to optimize the communication strategy in combination with the network load monitoring value. Finally, monitor the operation of the communication strategy, obtain real-time monitoring data, and perform optimization and adjustment in combination with the channel state parameters to obtain the final communication protocol parameters. The above steps effectively reduce data transmission conflicts, improve slot utilization, make the network load more balanced, and improve the overall efficiency of data transmission. It enables the wireless optical communication network to better adapt to the complex and changeable underwater environment, reduce signal interference and packet loss rate, and ensure the stable and reliable communication. It provides a solid communication technology support for scenarios such as underwater unmanned vehicle operations and ocean scientific research, and promotes the development of the underwater communication field. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0047] Figure 1 It is the system overall design block diagram of the underwater wireless optical communication networking prototype provided by the embodiment of the present invention;

[0048] Figure 2 It is the flowchart of the slotted ALOHA protocol under the retransmission mechanism provided by the embodiment of the present invention;

[0049] Figure 3 It is the underwater wireless optical communication networking method based on the improved slotted ALOHA protocol provided by the embodiment of the present invention;

[0050] Figure 4 It is the structural block diagram of the underwater wireless optical communication networking system based on the improved slotted ALOHA protocol provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0051] In order to make the purpose, technical solutions and advantages of the present application clearer, the following will further describe the present application in detail with reference to the drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not used to limit the present application.

[0052] In one embodiment, as Figure 1 shown, the present application provides a system overall design block diagram of an underwater wireless optical communication networking prototype, which may include the following:

[0053] The system overall design block diagram of the underwater wireless optical communication networking prototype includes an optical transmitting end, an optical receiving end, and a power supply module. In the optical transmitting end, a camera and a microphone collect underwater audio and video data. The FPGA serves as the control core, drives and configures the audio codec chip, processes the collected data in real time and encapsulates it into a specific frame structure, which is used as a serial LED driving signal. The driving circuit controls the LED light source, and transmits the data in the form of optical signals through the underwater channel. In terms of the optical receiving end, the APD photodetector receives the optical signal transmitted through the underwater channel and converts it into a current signal, which is converted into a voltage signal by a transimpedance amplifier, and then collected by the FPGA-driven ADC and converted into a digital signal. Finally, the original data frame is restored by the FPGA digital signal processing module. The video data is displayed on the LCD screen, and the audio data is played through the earphone. Each part works together to achieve stable transmission of real-time audio and video data among multiple underwater users.

[0054] In one embodiment, as Figure 2 shown, the present application provides a flowchart of the slotted ALOHA protocol under the retransmission mechanism, which may include the following:

[0055] The flowchart of the slotted ALOHA protocol under the retransmission mechanism shows an optimized communication process. In this process, data packets first enter the buffer of the first first-in-first-out (FIFO) structure and queue up in chronological order. When the node detects the start of a time slot, the data packet moves from the first buffer to the second buffer to prepare for transmission. After the sender sends the data packet, it enters the waiting confirmation stage. If the data packet received by the receiver is error-free, an acknowledgement signal ACK will be sent to the sender, and at this time the data packet is deleted from the second buffer; if the sender does not receive the ACK, it is determined that the data packet transmission fails, and the data packet returns to the first buffer and enters the next retransmission loop, repeating this process until the data packet is successfully transmitted, ensuring that the data can be accurately delivered to the receiver in the underwater wireless optical communication environment.

[0056] In one embodiment, as Figure 3 shown, the present application provides an underwater wireless optical communication networking method based on an improved slotted ALOHA protocol, which may include the following steps:

[0057] Step S101, obtain the original underwater audio and video data; process the original underwater audio and video data to obtain a frame encoding signal, and use a dynamic time slot allocation algorithm based on the underwater node optical signal propagation delay to obtain an initial time slot allocation scheme.

[0058] Specifically, through professional underwater acquisition devices, such as high-definition underwater cameras and high-sensitivity underwater microphones, the original underwater audio and video data is obtained. These devices are deployed at specific underwater node positions to ensure that the sound and image information of the underwater scene can be comprehensively and accurately captured. Subsequently, the collected original audio and video data is deeply processed. The field-programmable gate array (FPGA) is used to parse, encode, and encapsulate the audio and video data to construct a frame encoding signal containing a preamble, the sending node number, the receiving node number, the data type, the data segment, and the check segment. At the same time, with the help of a high-precision optical signal transceiver device and a synchronous clock system, the propagation delay of the optical signal between underwater nodes is accurately measured to ensure the accuracy of the measurement. Based on these delay data, combined with the position information of each node, the dynamic time slot allocation algorithm is used. Considering the distance difference between nodes, communication requirements, and channel conditions, an initial time slot is reasonably allocated to each node, and finally an initial time slot allocation scheme is formed to achieve the preliminary time slot planning for underwater multi-node communication.

[0059] Step S102, obtain underwater environment data; based on the environment data and combined with the initial time slot allocation scheme, determine high-risk nodes and adjust the time slot priority to obtain an optimized time slot allocation table.

[0060] Preferably, a series of underwater sensors, including but not limited to water quality sensors, flow velocity sensors, and light attenuation sensors, etc., are used to monitor key environmental parameters such as underwater turbidity, ocean current speed and direction, and light signal attenuation degree in real time. The obtained underwater environment data is combined with the initial time slot allocation scheme for in-depth analysis. By establishing a complex risk assessment model, considering the impact of environmental factors on optical signal transmission, the data transmission volume of nodes, and the time slot allocation situation, high-risk nodes that may face communication risks are determined. For these high-risk nodes, according to their risk levels and the urgency of data transmission requirements, their time slot priorities are adjusted specifically. For example, for nodes with large environmental interference and urgent data transmission tasks, their time slot priorities are increased so that they can obtain communication resources first. After such adjustment, an optimized time slot allocation table is generated to improve the reliability and stability of the overall communication system.

[0061] Step S103, perform data extraction on the optimized time slot allocation table and combine it with the network load monitoring value using the load balancing algorithm to obtain a communication strategy with adjusted load.

[0062] Specifically, after obtaining the optimized time slot allocation table, key data is extracted from the table, including information such as the time slot allocation duration and priority of each node. At the same time, through dedicated network load monitoring devices and software, the network load monitoring values are obtained in real time to comprehensively understand information such as the data traffic, bandwidth occupancy, and network congestion degree of each node. The extracted time slot allocation data and network load monitoring values are input into the load balancing algorithm module. The algorithm dynamically adjusts the time slot usage strategy of each node according to the real-time changes in network load. For example, when a certain node has a high load, the algorithm will appropriately reduce the allocation duration of its subsequent time slots and allocate the time slot resources to nodes with lower loads to balance the network load and avoid local congestion. By optimizing the communication strategy in this way, the communication strategy after load adjustment is obtained, improving the resource utilization rate and data transmission efficiency of the entire underwater communication network.

[0063] Step S104: Monitor the operation of the communication strategy to obtain real-time monitoring data and combine it with channel state parameters to obtain the final communication protocol parameters.

[0064] To ensure that the communication strategy can continuously adapt to the complex and changeable underwater environment, it is necessary to monitor the operation of the communication strategy after load adjustment in real time. By deploying monitoring devices at each node, real-time monitoring data such as data transmission success rate, transmission delay, and data packet loss rate is collected. At the same time, channel state monitoring technology is used to obtain channel state parameters, including information such as optical signal intensity, channel bandwidth change, and noise interference degree. The real-time monitoring data and channel state parameters are input into the comprehensive analysis system, and data analysis algorithms and optimization models are used to evaluate and adjust the current communication strategy. After continuous iterative optimization, the final communication protocol parameters that meet the underwater communication requirements are finally determined to ensure that the communication system always maintains an efficient and stable operating state in the complex underwater environment.

[0065] The above-mentioned underwater wireless optical communication networking method based on the improved slotted ALOHA protocol first obtains the original audio and video data, processes and encapsulates it into a frame coding signal including specific information. At the same time, by measuring the propagation delay of the optical signal of the underwater node and using the dynamic time slot allocation algorithm, an initial time slot allocation scheme is generated. Then, the underwater environment data is collected, and the high-risk nodes are determined in combination with the initial time slot allocation scheme. The time slot priority is adjusted according to the risk level and the urgency of data transmission to obtain an optimized time slot allocation table. Then, the data is extracted from the optimized time slot allocation table, and the communication strategy is optimized by using the load balancing algorithm in combination with the network load monitoring value. Finally, the operation of the communication strategy is monitored, the real-time monitoring data is obtained, and the communication protocol parameters are optimized and adjusted in combination with the channel state parameters. The above steps effectively reduce data transmission conflicts, improve time slot utilization, make the network load more balanced, and improve the overall efficiency of data transmission. It enables the wireless optical communication network to better adapt to the complex and changeable underwater environment, reduces signal interference and packet loss rate, and ensures the stable and reliable communication. It provides solid communication technology support for scenarios such as underwater unmanned vehicle operations and ocean scientific research, and promotes the development of the underwater communication field.

[0066] In one embodiment, processing the original audio and video data to obtain a frame coding signal and using the dynamic time slot allocation algorithm based on the propagation delay of the optical signal of the underwater node to obtain an initial time slot allocation scheme may include the following steps:

[0067] Step S201, perform real-time processing on the original audio and video data using a field programmable gate array to obtain a frame coding signal; the frame coding signal includes a preamble, a sending node number, a receiving node number, a data type, a data segment, and a check segment.

[0068] Step S202, obtain the propagation delay data of the optical signal transmitted and received by the underwater node and perform calculations to obtain the distance information between each underwater node; the propagation delay data is calculated from the underwater node position information and the optical signal transmission rate.

[0069] Step S203, calculate the distance difference between each node according to the distance information to construct a distance difference matrix and obtain the delay compensation parameter.

[0070] Step S204, use the dynamic time slot allocation algorithm to process the delay compensation parameter to allocate corresponding time slot lengths to different nodes, and obtain a time slot allocation table including time window markers.

[0071] Step S205, perform timestamp synchronization processing on the frame coding signal based on the time slot allocation table and match it with the remaining energy parameter of the underwater node to obtain a time slot matching result.

[0072] Step S206: Adjust the length of the time window marker in the time slot allocation table according to the time slot matching result to obtain an initial time slot allocation scheme.

[0073] Specifically, first, the collected original audio and video data is processed in real time using a Field-Programmable Gate Array (FPGA). The FPGA encapsulates the original data into a frame coding signal containing a preamble, a sending node serial number, a receiving node serial number, a data type, a data segment, and a check segment according to specific coding rules. At the same time, by obtaining the propagation delay data of the underwater nodes transmitting and receiving optical signals, and calculating in combination with the underwater node position information and the optical signal transmission rate, the distance information between each underwater node is obtained. Based on this distance information, the distance difference between each node is calculated and a distance difference matrix is constructed, and then the delay compensation parameter is obtained. The dynamic time slot allocation algorithm is used to process the delay compensation parameter, allocate corresponding time slot lengths to different nodes, and generate a time slot allocation table with time window markers. Then, based on this time slot allocation table, timestamp synchronization processing is performed on the frame coding signal and matched with the remaining energy parameter of the underwater node to obtain a time slot matching result. Finally, according to the time slot matching result, the length of the time window marker in the time slot allocation table is adjusted to obtain an initial time slot allocation scheme.

[0074] In terms of communication efficiency in this embodiment, by using the FPGA to process data in real time to generate a frame coding signal, the standardization and accuracy of data transmission are guaranteed; by using the propagation delay data to construct a distance difference matrix and obtain the delay compensation parameter, combined with the dynamic time slot allocation algorithm, the time slot allocation is more in line with the actual distance difference between nodes, improving the utilization rate of communication resources. In terms of system stability, timestamp synchronization processing is performed on the frame coding signal and matched with the remaining energy parameter of the node, optimizing the time slot allocation, reducing data transmission conflicts, and being able to reasonably allocate resources according to the node energy situation, extending the service life of the entire underwater communication network, enhancing the stability and reliability of the system in a complex underwater environment, and providing a more reliable communication guarantee for underwater operations.

[0075] In one of the embodiments, based on the environmental data and combined with the initial time slot allocation scheme, high-risk nodes are determined and the time slot priority is adjusted to obtain an optimized time slot allocation table, which may include the following steps:

[0076] Step S301: Based on the environmental data, use the optical signal attenuation model to calculate the channel state change rate combined with the optical signal intensity scattering value to obtain a channel state parameter for evaluating the dynamic fluctuation degree of the channel quality.

[0077] Step S302: Obtain the time slot occupancy rate and time slot interval parameters in the initial time slot allocation scheme; the time slot occupancy rate and time slot interval parameters are extracted from the time slot allocation record.

[0078] Step S303: Input the channel state parameters and the time slot occupancy rate into the dynamic priority model to quantitatively evaluate each node according to the metrics, and obtain high-risk nodes; the metrics include at least one of the data transmission success rate, transmission delay, and packet loss rate of the node under the current channel conditions.

[0079] Step S304: Analyze the high-risk nodes according to their risk levels and the urgency of data transmission requirements to obtain the corresponding time slot weight sequence.

[0080] Step S305: Update the time slot allocation order and length according to the time slot weight sequence, and combine the time slot interval parameters to generate a collision detection result.

[0081] Step S306: Based on the collision detection result, use the iterative optimization algorithm to eliminate the time slot overlapping interval to obtain an optimized time slot allocation table; the optimized time slot allocation table includes the mapping relationship between the node identification number and the time slot start timestamp.

[0082] Specifically, first, use the underwater environment monitoring equipment to obtain comprehensive environmental data, which cover various aspects of information such as water temperature, water pressure, and water quality turbidity. Use the optical signal attenuation model and combine the optical signal intensity scattering value to deeply analyze and calculate the environmental data, so as to obtain the channel state parameters that can accurately evaluate the dynamic fluctuation degree of the channel quality. At the same time, extract the key time slot occupancy rate and time slot interval parameters from the time slot allocation records of the initial time slot allocation scheme. Input the channel state parameters and the time slot occupancy rate into the dynamic priority model, and quantitatively evaluate each node according to factors such as the data transmission success rate, transmission delay, and packet loss rate of the node under the current channel conditions, and then identify high-risk nodes. For these high-risk nodes, conduct in-depth analysis by comprehensively considering their risk levels and the urgency of data transmission requirements to obtain the corresponding time slot weight sequence. Update the time slot allocation order and length according to the time slot weight sequence, and perform collision detection in combination with the time slot interval parameters to generate a collision detection result. Finally, based on the collision detection result, use the iterative optimization algorithm to eliminate the time slot overlapping interval and construct an optimized time slot allocation table including the mapping relationship between the node identification number and the time slot start timestamp.

[0083] By accurately evaluating the channel state, combining the time slot parameters and node performance indicators to determine high-risk nodes, and adjusting the time slot weights accordingly, the rationality of time slot allocation is optimized, effectively reducing data transmission conflicts, improving the data transmission success rate, reducing the transmission delay and packet loss rate, and significantly enhancing the overall communication efficiency. The optimized time slot allocation table reasonably allocates time slot resources according to node requirements, avoids resource waste caused by time slot overlap, improves the utilization rate of channel resources, and enables the underwater wireless optical communication system to operate more efficiently and stably in the complex and changeable underwater environment.

[0084] In one embodiment, the channel state change rate can be calculated by the following formula:

[0085]

[0086] where C rate represents the channel state change rate, I0 represents the initial intensity of the optical signal, d represents the transmission distance, I(t) represents the intensity of the optical signal received at time t, T represents the turbidity, υ represents the ocean current speed, θ represents the angle between the ocean current speed and the optical signal transmission direction, k(λ) represents the attenuation coefficient related to the optical signal wavelength λ, m represents the scattering coefficient related to the scattering characteristics, and α, β, γ, and η represent the weight coefficients determined according to the actual environment and experimental data.

[0087] By comprehensively considering the influence of various factors such as the change of optical signal intensity over time, turbidity, ocean current speed, optical signal wavelength, and scattering on the channel state change rate, this embodiment can more accurately evaluate the dynamic change of the underwater optical communication channel. This enables the communication system to adjust communication parameters, such as signal transmission power, modulation method, etc., in a timely manner according to the real-time change of the channel state, thereby effectively improving the stability and reliability of communication, reducing data transmission errors and packet loss phenomena, and improving communication quality. In practical applications, for scenarios such as ocean monitoring and underwater operations that rely on underwater optical communication, this formula provides a scientific basis for system design and performance evaluation, helps to reasonably plan communication links, optimize equipment layout, reduce communication costs, and promote the wide application and development of underwater optical communication technology in various fields.

[0088] In one embodiment, data extraction from the optimized time slot allocation table is combined with the network load monitoring value using the load balancing algorithm to obtain the communication strategy after load adjustment, which may include the following steps:

[0089] Step S401, obtain the time slot allocation parameters in the optimized time slot allocation table; the time slot allocation parameters include the priority weights of each time slot and the time slot data characteristics.

[0090] Step S402, extract the time slot occupancy rate matrix according to the time slot data characteristics; the time slot occupancy rate matrix includes the time slot occupancy status of each node within a preset period.

[0091] Step S403, obtain the load volatility in the network load monitoring value; the load volatility is calculated from the load differences of each node within consecutive monitoring periods.

[0092] Step S404, input the time slot occupancy rate matrix and the load volatility into the load balancing algorithm to obtain the policy adjustment parameters, and the policy adjustment parameters include the time slot reallocation ratio and the priority correction amount.

[0093] Step S405: Perform a superposition operation on the policy adjustment parameters and the priority weights to obtain an updated set of time slot allocation parameters.

[0094] Step S406: Generate a communication policy with adjusted load according to the set of time slot allocation parameters; the communication policy includes the policy effective delay and the policy execution sequence.

[0095] First, accurately obtain the time slot allocation parameters from the optimized time slot allocation table. Then, extract the time slot occupancy rate matrix based on the time slot data characteristics. This matrix details the time slot occupancy status of each node within a preset period and visually presents the usage of network resources. At the same time, by calculating the load difference of each node within consecutive monitoring periods, the load volatility in the network load monitoring value is obtained to measure the dynamic change degree of the network load. Subsequently, input the time slot occupancy rate matrix and the load volatility into the load balancing algorithm. After complex operations and analyses, policy adjustment parameters are obtained, including the time slot reallocation ratio and the priority correction amount. Perform a superposition operation on these policy adjustment parameters and the original priority weights to obtain an updated set of time slot allocation parameters. Finally, generate a communication policy with adjusted load according to this set of time slot allocation parameters. This communication policy specifies the policy effective delay and the policy execution sequence.

[0096] In this embodiment, through the comprehensive analysis of the time slot occupancy rate and the load volatility, and using the load balancing algorithm for policy adjustment, it effectively avoids network congestion caused by excessive load on some nodes, balances the network load, and improves the overall throughput and transmission efficiency of the network. Reasonable time slot reallocation and priority correction enable the time slot resources to be more reasonably allocated to each node, improve the utilization rate of time slot resources, and reduce resource waste.

[0097] In one of the embodiments, to monitor the operation of the communication policy and obtain real-time monitoring data combined with channel state parameters to obtain the final communication protocol parameters, the following steps may be included:

[0098] Step S501: Extract the real-time transmission rate and the channel error rate of the communication policy from the real-time monitoring data.

[0099] Step S502: Calculate the dynamic bandwidth threshold according to the real-time transmission rate and the channel error rate; the dynamic bandwidth threshold uses a linear weighting model to fuse the channel interference index.

[0100] Step S503: Obtain the spectrum occupancy rate and the delay fluctuation coefficient in the channel state parameters.

[0101] Step S504: Input the dynamic bandwidth threshold and the spectrum occupancy rate into the protocol parameter adjustment model to obtain the adaptive weight coefficient.

[0102] Step S505: Integrate the delay fluctuation coefficient and the adaptive weight coefficient to generate the final communication protocol parameters.

[0103] First, extract the real-time monitoring data in detail to obtain the real-time transmission rate and channel bit error rate of the communication strategy. These two key indicators intuitively reflect the current operating conditions of the communication strategy. Then, using these two indicators, combined with the linear weighting model and integrating the channel interference index, calculate the dynamic bandwidth threshold. This threshold comprehensively considers various influencing factors in the communication process and can more accurately reflect the dynamic bandwidth requirements of the communication. At the same time, obtain the spectrum occupancy rate and delay fluctuation coefficient in the channel state parameters. The spectrum occupancy rate reflects the utilization of channel resources, and the delay fluctuation coefficient reflects the degree of change in the signal transmission delay. Then, input the dynamic bandwidth threshold and the spectrum occupancy rate into the protocol parameter adjustment model. After complex operations and analyses of the model, obtain the adaptive weight coefficient. Finally, integrate the delay fluctuation coefficient and the adaptive weight coefficient to generate the final communication protocol parameters.

[0104] Calculating the dynamic bandwidth threshold through real-time monitoring data and adjusting the communication protocol in combination with the channel state parameters can timely adapt to the dynamic changes of the channel, effectively reduce the channel bit error rate, improve the real-time transmission rate, and ensure the stability and reliability of communication. In terms of resource utilization, the analysis and processing of parameters such as the spectrum occupancy rate help to reasonably allocate channel resources, improve resource utilization rate, and avoid resource waste. This enables the underwater wireless optical communication system to always maintain a good operating state in the complex and changeable underwater environment, provide reliable communication guarantees for application scenarios such as underwater operations and ocean scientific research, and promote the further development and application of underwater communication technology.

[0105] In one embodiment, as Figure 4 shown, the present application also provides an underwater wireless optical communication networking system based on an improved slotted ALOHA protocol. The system may include:

[0106] An initial time slot allocation module 601, configured to obtain the original underwater audio and video data; and further configured to process the original audio and video data to obtain a frame coding signal and, based on the underwater node optical signal propagation delay, use a dynamic time slot allocation algorithm to obtain an initial time slot allocation scheme.

[0107] A time slot optimization module 602, configured to obtain the underwater environment data; and further configured to determine high-risk nodes based on the environment data in combination with the initial time slot allocation scheme and adjust the time slot priority to obtain an optimized time slot allocation table.

[0108] The communication protocol optimization module 603 is used to extract data from the optimized time slot allocation table, combine it with the network load monitoring value, and use the load balancing algorithm to obtain the communication strategy after load adjustment. It is also used to monitor the operation of the communication strategy, obtain real-time monitoring data, combine it with the channel state parameters, and obtain the final communication protocol parameters.

[0109] For the above-mentioned underwater wireless optical communication networking system based on the improved slotted ALOHA protocol, the initial time slot allocation module obtains the original underwater audio and video data through professional acquisition devices deployed underwater. These data are processed using technologies such as field programmable gate arrays and encapsulated into frame coding signals containing key information such as preambles and sending node numbers. At the same time, with the help of precise optical signal propagation delay measurement technology and combined with the dynamic time slot allocation algorithm, fully considering the distance differences and communication requirements between underwater nodes, an initial time slot allocation scheme is generated. The time slot optimization module uses the underwater sensor network to obtain comprehensive underwater environment data, combines these environment data with the initial time slot allocation scheme, and determines high-risk nodes that may affect communication quality by establishing a risk assessment model. According to the risk level of the nodes and the urgency of data transmission requirements, the time slot priority is reasonably adjusted to obtain the optimized time slot allocation table. The communication protocol optimization module extracts key data from the optimized time slot allocation table, combines it with the real-time network load monitoring value, and uses the load balancing algorithm to optimize the communication strategy to obtain the communication strategy after load adjustment. Moreover, this module continuously monitors the operation of the communication strategy, obtains real-time monitoring data, combines it with the channel state parameters, and through a complex analysis and optimization process, finally obtains the communication protocol parameters that are most suitable for the current underwater environment and communication requirements. The above steps effectively reduce data transmission conflicts, improve time slot utilization, make the network load more balanced, and enhance the overall efficiency of data transmission. It enables wireless optical communication networking to better adapt to the complex and changeable underwater environment, reduce signal interference and packet loss rate, and ensure stable and reliable communication. It provides strong communication technology support for scenarios such as underwater unmanned vehicle operations and ocean scientific research, and promotes the development of the underwater communication field.

[0110] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are shown sequentially according to the arrows, these steps do not necessarily have to be executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps does not have a strict order limit, and these steps can be executed in other orders. Moreover, at least some of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages do not necessarily have to be executed at the same time, but can be executed at different times. The execution order of these steps or stages does not necessarily have to be sequential, but can be executed alternately or alternately with at least some of the steps or stages in other steps or other steps.

[0111] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the underwater wireless optical communication networking method and system based on the improved slotted ALOHA protocol as described above are implemented.

[0112] In one embodiment, 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 in the above method embodiments are implemented.

[0113] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can be referred to the partial description of the method embodiment. The device embodiments described above are only illustrative. The components 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 to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the present disclosure solution. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0114] The above embodiments only represent several implementation manners of the embodiments of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the embodiments of the application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the embodiments of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the embodiments of the present application.

Claims

1. An underwater wireless optical communication networking method based on an improved time-slot ALOHA protocol is characterized in that: The method comprises: Acquire underwater original audio and video data; process the original audio and video data to obtain a frame coding signal and obtain an initial time slot allocation scheme using a dynamic time slot allocation algorithm based on the propagation delay of underwater node optical signals; Acquire underwater environmental data; determine high-risk nodes based on the environmental data and the initial time slot allocation scheme and adjust the time slot priority to obtain an optimized time slot allocation table; Extract data from the optimized time slot allocation table and use a load balancing algorithm in combination with the network load monitoring value to obtain a communication strategy after load adjustment; The operation of the communication strategy is monitored to obtain real-time monitoring data and combined with channel state parameters to obtain final communication protocol parameters.

2. The method according to claim 1, characterized in that The processing of the original audio and video data to obtain a frame coded signal and obtaining an initial time slot allocation scheme using a dynamic time slot allocation algorithm based on the propagation delay of an underwater node optical signal include: Based on the original audio and video data, a field programmable gate array is used to perform real-time processing to obtain a frame coded signal; the frame coded signal includes a preamble, a sending node sequence number, a receiving node sequence number, a data type, a data segment, and a check segment; Obtaining and calculating the propagation delay data of the underwater nodes transmitting and receiving optical signals to obtain the distance information between the underwater nodes; the propagation delay data is calculated from the underwater node position information and the optical signal transmission rate; Calculate the distance difference between each node according to the distance information to construct a distance difference matrix and obtain a delay compensation parameter; Processing the delay compensation parameters using a dynamic time slot allocation algorithm to allocate corresponding time slot lengths to different nodes, and obtaining a time slot allocation table including a time window mark; Performing time stamp synchronization processing on the frame coded signal based on the time slot allocation table and matching it with the residual energy parameter of the underwater node to obtain a time slot matching result; The length of the time window mark in the time slot allocation table is adjusted according to the time slot matching result to obtain an initial time slot allocation scheme.

3. The method according to claim 1, characterized in that The step of determining high-risk nodes based on the environmental data in combination with the initial time slot allocation scheme and adjusting time slot priorities to obtain an optimized time slot allocation table includes: Based on the environmental data, the channel state change rate is calculated by using an optical signal attenuation model in combination with an optical signal intensity scattering value to obtain a channel state parameter for evaluating the dynamic fluctuation degree of channel quality; Obtaining the time slot occupancy rate and time slot interval parameters in the initial time slot allocation scheme; the time slot occupancy rate and time slot interval parameters are extracted from the time slot allocation record; Inputting the channel state parameter and the time slot occupancy rate into a dynamic priority model to quantitatively evaluate each node according to an indicator to obtain a high-risk node; the indicator includes at least one factor of the node's data transmission success rate, transmission delay and packet loss rate under the current channel conditions; Analyze the high-risk nodes according to their risk levels and the urgency of data transmission requirements to obtain corresponding time slot weight sequences; Update the time slot allocation order and length according to the time slot weight sequence and generate a conflict detection result in combination with the time slot interval parameter; Based on the conflict detection result, an iterative optimization algorithm is used to eliminate overlapping time slot intervals to obtain an optimized time slot allocation table; the optimized time slot allocation table includes a mapping relationship between a node identification number and a time slot start timestamp.

4. The method according to claim 3, characterized in that The channel state change rate is calculated by the following formula: Among them, C rate represents the rate of change of channel state, I0 represents the initial intensity of optical signal, d represents the transmission distance, I(t) represents the intensity of optical signal received at time t, T represents turbidity, υ represents the ocean current speed, θ represents the angle between the ocean current speed and the transmission direction of optical signal, k(λ) represents the attenuation coefficient related to the wavelength λ of optical signal, m represents the scattering coefficient related to scattering characteristics, α, β, γ and η represent weight coefficients determined according to actual environment and experimental data.

5. The method according to claim 1, characterized in that: The extracting data from the optimized time slot allocation table and combining the network load monitoring value with the load balancing algorithm to obtain the communication strategy after load adjustment includes: Obtaining time slot allocation parameters in the optimized time slot allocation table; the time slot allocation parameters include priority weights and time slot data features of each time slot; A time slot occupancy matrix is ​​obtained according to the time slot data feature extraction; the time slot occupancy matrix includes the time slot occupancy status of each node within a preset period; Obtaining a load fluctuation rate in the network load monitoring value; the load fluctuation rate is calculated by the load difference of each node in a continuous monitoring cycle; Inputting the time slot occupancy matrix and the load fluctuation rate into a load balancing algorithm to obtain a strategy adjustment parameter, wherein the strategy adjustment parameter includes a time slot reallocation ratio and a priority correction amount; Performing a superposition operation on the policy adjustment parameter and the priority weight to obtain an updated time slot allocation parameter set; A load-adjusted communication strategy is generated according to the time slot allocation parameter set; the communication strategy includes a strategy effective delay and a strategy execution sequence.

6. The method according to claim 1, characterized in that The monitoring of the operation of the communication strategy to obtain real-time monitoring data and combining it with channel state parameters to obtain final communication protocol parameters includes: Extracting the real-time monitoring data to obtain the real-time transmission rate and channel bit error rate of the communication strategy; A dynamic bandwidth threshold is calculated according to the real-time transmission rate and the channel bit error rate; the dynamic bandwidth threshold is integrated with the channel interference index using a linear weighted model; Obtaining spectrum occupancy and delay fluctuation coefficient in the channel state parameters; Inputting the dynamic bandwidth threshold and spectrum occupancy rate into a protocol parameter adjustment model to obtain an adaptive weight coefficient; The delay fluctuation coefficient and the adaptive weight coefficient are merged to generate final communication protocol parameters.

7. The underwater wireless optical communication networking system based on the improved time-slot ALOHA protocol is characterized by: The system comprises: An initial time slot allocation module is used to obtain underwater original audio and video data; it is also used to process the original audio and video data to obtain a frame coding signal and obtain an initial time slot allocation scheme based on the underwater node optical signal propagation delay using a dynamic time slot allocation algorithm; A time slot optimization module, used to obtain underwater environmental data; and also used to determine high-risk nodes and adjust time slot priorities based on the environmental data combined with the initial time slot allocation scheme to obtain an optimized time slot allocation table; The communication protocol optimization module is used to extract data from the optimized time slot allocation table and use a load balancing algorithm to obtain a load-adjusted communication strategy; it is also used to monitor the operation of the communication strategy to obtain real-time monitoring data and combine it with channel state parameters to obtain the final communication protocol parameters.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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